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...tmlx_1_1core_1_1metal_1_1_device_stream.js | 1 + ...re_1_1numeric__limits_3_01double_01_4.html | 129 + ...ore_1_1numeric__limits_3_01double_01_4.png | Bin 0 -> 777 bytes docs/build/html/transforms_8h_source.html | 2 +- docs/build/html/usage/compile.html | 15 +- docs/build/html/usage/distributed.html | 15 +- docs/build/html/usage/export.html | 15 +- .../build/html/usage/function_transforms.html | 15 +- docs/build/html/usage/indexing.html | 15 +- docs/build/html/usage/lazy_evaluation.html | 15 +- docs/build/html/usage/numpy.html | 57 +- docs/build/html/usage/quick_start.html | 15 +- docs/build/html/usage/saving_and_loading.html | 15 +- docs/build/html/usage/unified_memory.html | 15 +- docs/build/html/usage/using_streams.html | 15 +- docs/build/html/utils_8h.html | 6 +- docs/build/html/utils_8h.js | 3 +- docs/build/html/utils_8h_source.html | 222 +- 748 files changed, 24254 insertions(+), 13906 deletions(-) create mode 100644 docs/build/html/_sources/python/_autosummary/mlx.core.bitwise_invert.rst create mode 100644 docs/build/html/_sources/python/_autosummary/mlx.core.linalg.lu.rst create mode 100644 docs/build/html/_sources/python/_autosummary/mlx.core.linalg.lu_factor.rst create mode 100644 docs/build/html/_sources/python/_autosummary/mlx.core.linalg.solve.rst create mode 100644 docs/build/html/_sources/python/_autosummary/mlx.core.linalg.solve_triangular.rst create mode 100644 docs/build/html/classmlx_1_1core_1_1_bitwise_invert-members.html create mode 100644 docs/build/html/classmlx_1_1core_1_1_bitwise_invert.html create mode 100644 docs/build/html/classmlx_1_1core_1_1_bitwise_invert.js create mode 100644 docs/build/html/classmlx_1_1core_1_1_bitwise_invert.png create mode 100644 docs/build/html/classmlx_1_1core_1_1_l_u_f-members.html create mode 100644 docs/build/html/classmlx_1_1core_1_1_l_u_f.html create mode 100644 docs/build/html/classmlx_1_1core_1_1_l_u_f.js create mode 100644 docs/build/html/classmlx_1_1core_1_1_l_u_f.png create mode 100644 docs/build/html/python/_autosummary/mlx.core.bitwise_invert.html create mode 100644 docs/build/html/python/_autosummary/mlx.core.linalg.lu.html create mode 100644 docs/build/html/python/_autosummary/mlx.core.linalg.lu_factor.html create mode 100644 docs/build/html/python/_autosummary/mlx.core.linalg.solve.html create mode 100644 docs/build/html/python/_autosummary/mlx.core.linalg.solve_triangular.html create mode 100644 docs/build/html/struct_bitwise_invert-members.html create mode 100644 docs/build/html/struct_bitwise_invert.html create mode 100644 docs/build/html/struct_bitwise_invert.js create mode 100644 docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert-members.html create mode 100644 docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert.html create mode 100644 docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert.js create mode 100644 docs/build/html/structmlx_1_1core_1_1numeric__limits_3_01double_01_4.html create mode 100644 docs/build/html/structmlx_1_1core_1_1numeric__limits_3_01double_01_4.png diff --git a/docs/build/html/.buildinfo b/docs/build/html/.buildinfo index e5591e92d..3e7897cbc 100644 --- a/docs/build/html/.buildinfo +++ b/docs/build/html/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 81aaeaba965ad2156af7b499f90bc0e9 +config: 3de7e28b53786b931963de5ee3424408 tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/docs/build/html/_sources/python/_autosummary/mlx.core.bitwise_invert.rst b/docs/build/html/_sources/python/_autosummary/mlx.core.bitwise_invert.rst new file mode 100644 index 000000000..12985b819 --- /dev/null +++ b/docs/build/html/_sources/python/_autosummary/mlx.core.bitwise_invert.rst @@ -0,0 +1,6 @@ +mlx.core.bitwise\_invert +======================== + +.. currentmodule:: mlx.core + +.. autofunction:: bitwise_invert \ No newline at end of file diff --git a/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.lu.rst b/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.lu.rst new file mode 100644 index 000000000..15755b2a6 --- /dev/null +++ b/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.lu.rst @@ -0,0 +1,6 @@ +mlx.core.linalg.lu +================== + +.. currentmodule:: mlx.core.linalg + +.. autofunction:: lu \ No newline at end of file diff --git a/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.lu_factor.rst b/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.lu_factor.rst new file mode 100644 index 000000000..8ea5ae596 --- /dev/null +++ b/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.lu_factor.rst @@ -0,0 +1,6 @@ +mlx.core.linalg.lu\_factor +========================== + +.. currentmodule:: mlx.core.linalg + +.. autofunction:: lu_factor \ No newline at end of file diff --git a/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.solve.rst b/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.solve.rst new file mode 100644 index 000000000..c63af6b2f --- /dev/null +++ b/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.solve.rst @@ -0,0 +1,6 @@ +mlx.core.linalg.solve +===================== + +.. currentmodule:: mlx.core.linalg + +.. autofunction:: solve \ No newline at end of file diff --git a/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.solve_triangular.rst b/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.solve_triangular.rst new file mode 100644 index 000000000..2ab9fe9bd --- /dev/null +++ b/docs/build/html/_sources/python/_autosummary/mlx.core.linalg.solve_triangular.rst @@ -0,0 +1,6 @@ +mlx.core.linalg.solve\_triangular +================================= + +.. currentmodule:: mlx.core.linalg + +.. autofunction:: solve_triangular \ No newline at end of file diff --git a/docs/build/html/_sources/python/data_types.rst b/docs/build/html/_sources/python/data_types.rst index c75bfcb9d..4c4a5910d 100644 --- a/docs/build/html/_sources/python/data_types.rst +++ b/docs/build/html/_sources/python/data_types.rst @@ -51,11 +51,20 @@ The default floating point type is ``float32`` and the default integer type is * - ``float32`` - 4 - 32-bit float + * - ``float64`` + - 4 + - 64-bit double * - ``complex64`` - 8 - 64-bit complex float +.. note:: + + Arrays with type ``float64`` only work with CPU operations. Using + ``float64`` arrays on the GPU will result in an exception. + + Data type are aranged in a hierarchy. See the :obj:`DtypeCategory` object documentation for more information. Use :func:`issubdtype` to determine if one ``dtype`` (or category) is a subtype of another category. diff --git a/docs/build/html/_sources/python/linalg.rst b/docs/build/html/_sources/python/linalg.rst index f6c51ed0b..769f4bbb1 100644 --- a/docs/build/html/_sources/python/linalg.rst +++ b/docs/build/html/_sources/python/linalg.rst @@ -5,8 +5,8 @@ Linear Algebra .. currentmodule:: mlx.core.linalg -.. autosummary:: - :toctree: _autosummary +.. autosummary:: + :toctree: _autosummary inv tri_inv @@ -18,3 +18,7 @@ Linear Algebra svd eigvalsh eigh + lu + lu_factor + solve + solve_triangular diff --git a/docs/build/html/_sources/python/ops.rst b/docs/build/html/_sources/python/ops.rst index 248028575..c0d098b21 100644 --- a/docs/build/html/_sources/python/ops.rst +++ b/docs/build/html/_sources/python/ops.rst @@ -32,6 +32,7 @@ Operations atleast_2d atleast_3d bitwise_and + bitwise_invert bitwise_or bitwise_xor block_masked_mm diff --git a/docs/build/html/_sources/usage/numpy.rst b/docs/build/html/_sources/usage/numpy.rst index c589f1887..09b36ddbd 100644 --- a/docs/build/html/_sources/usage/numpy.rst +++ b/docs/build/html/_sources/usage/numpy.rst @@ -21,11 +21,13 @@ Let's convert an array to NumPy and back. .. note:: - Since NumPy does not support ``bfloat16`` arrays, you will need to convert to ``float16`` or ``float32`` first: - ``np.array(a.astype(mx.float32))``. - Otherwise, you will receive an error like: ``Item size 2 for PEP 3118 buffer format string does not match the dtype V item size 0.`` + Since NumPy does not support ``bfloat16`` arrays, you will need to convert + to ``float16`` or ``float32`` first: ``np.array(a.astype(mx.float32))``. + Otherwise, you will receive an error like: ``Item size 2 for PEP 3118 + buffer format string does not match the dtype V item size 0.`` -By default, NumPy copies data to a new array. This can be prevented by creating an array view: +By default, NumPy copies data to a new array. This can be prevented by creating +an array view: .. code-block:: python @@ -35,10 +37,16 @@ By default, NumPy copies data to a new array. This can be prevented by creating a_view[0] = 1 print(a[0].item()) # 1 -A NumPy array view is a normal NumPy array, except that it does not own its memory. -This means writing to the view is reflected in the original array. +.. note:: -While this is quite powerful to prevent copying arrays, it should be noted that external changes to the memory of arrays cannot be reflected in gradients. + NumPy arrays with type ``float64`` will be default converted to MLX arrays + with type ``float32``. + +A NumPy array view is a normal NumPy array, except that it does not own its +memory. This means writing to the view is reflected in the original array. + +While this is quite powerful to prevent copying arrays, it should be noted that +external changes to the memory of arrays cannot be reflected in gradients. Let's demonstrate this in an example: @@ -56,11 +64,12 @@ Let's demonstrate this in an example: The function ``f`` indirectly modifies the array ``x`` through a memory view. -However, this modification is not reflected in the gradient, as seen in the last line outputting ``1.0``, -representing the gradient of the sum operation alone. -The squaring of ``x`` occurs externally to MLX, meaning that no gradient is incorporated. -It's important to note that a similar issue arises during array conversion and copying. -For instance, a function defined as ``mx.array(np.array(x)**2).sum()`` would also result in an incorrect gradient, +However, this modification is not reflected in the gradient, as seen in the +last line outputting ``1.0``, representing the gradient of the sum operation +alone. The squaring of ``x`` occurs externally to MLX, meaning that no +gradient is incorporated. It's important to note that a similar issue arises +during array conversion and copying. For instance, a function defined as +``mx.array(np.array(x)**2).sum()`` would also result in an incorrect gradient, even though no in-place operations on MLX memory are executed. PyTorch @@ -71,7 +80,8 @@ PyTorch PyTorch Support for :obj:`memoryview` is experimental and can break for multi-dimensional arrays. Casting to NumPy first is advised for now. -PyTorch supports the buffer protocol, but it requires an explicit :obj:`memoryview`. +PyTorch supports the buffer protocol, but it requires an explicit +:obj:`memoryview`. .. code-block:: python @@ -82,7 +92,8 @@ PyTorch supports the buffer protocol, but it requires an explicit :obj:`memoryvi b = torch.tensor(memoryview(a)) c = mx.array(b.numpy()) -Conversion from PyTorch tensors back to arrays must be done via intermediate NumPy arrays with ``numpy()``. +Conversion from PyTorch tensors back to arrays must be done via intermediate +NumPy arrays with ``numpy()``. JAX --- @@ -100,7 +111,8 @@ JAX fully supports the buffer protocol. TensorFlow ---------- -TensorFlow supports the buffer protocol, but it requires an explicit :obj:`memoryview`. +TensorFlow supports the buffer protocol, but it requires an explicit +:obj:`memoryview`. .. code-block:: python diff --git a/docs/build/html/_static/documentation_options.js b/docs/build/html/_static/documentation_options.js index bd3b55de9..ef92f28fa 100644 --- a/docs/build/html/_static/documentation_options.js +++ b/docs/build/html/_static/documentation_options.js @@ -1,5 +1,5 @@ const DOCUMENTATION_OPTIONS = { - VERSION: '0.22.1', + VERSION: '0.23.0', LANGUAGE: 'en', COLLAPSE_INDEX: false, BUILDER: 'html', diff --git a/docs/build/html/accelerate__fp16__simd_8h_source.html b/docs/build/html/accelerate__fp16__simd_8h_source.html index 41a4802ac..3c6f9e36d 100644 --- a/docs/build/html/accelerate__fp16__simd_8h_source.html +++ b/docs/build/html/accelerate__fp16__simd_8h_source.html @@ -187,7 +187,7 @@ $(function(){initNavTree('accelerate__fp16__simd_8h_source.html',''); initResiza
mlx::core::simd::atan
Simd< float16_t, N > atan(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:33
mlx::core::simd::asinh
Simd< float16_t, N > asinh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:32
mlx::core::simd::remainder
Simd< float16_t, N > remainder(Simd< float16_t, N > x, Simd< float16_t, N > y)
Definition accelerate_fp16_simd.h:53
-
mlx::core::simd::max_size
static constexpr int max_size
Definition base_simd.h:13
+
mlx::core::simd::max_size
static constexpr int max_size
Definition base_simd.h:14
mlx::core::simd::log1p
Simd< float16_t, N > log1p(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:40
mlx::core::simd::acos
Simd< float16_t, N > acos(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:29
mlx::core::simd::cosh
Simd< float16_t, N > cosh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:35
diff --git a/docs/build/html/accelerate__simd_8h.html b/docs/build/html/accelerate__simd_8h.html index 0139cf13d..c5a899bd9 100644 --- a/docs/build/html/accelerate__simd_8h.html +++ b/docs/build/html/accelerate__simd_8h.html @@ -226,6 +226,9 @@ Functions template<typename T, int N> Simd< T, N > mlx::core::simd::operator- (Simd< T, N > v)   +template<typename T, int N> +Simd< T, N > mlx::core::simd::operator~ (Simd< T, N > v) +  template<typename T, int N> Simd< bool, N > mlx::core::simd::isnan (Simd< T, N > v)   diff --git a/docs/build/html/accelerate__simd_8h.js b/docs/build/html/accelerate__simd_8h.js index 0a2068f72..46a096c3d 100644 --- a/docs/build/html/accelerate__simd_8h.js +++ b/docs/build/html/accelerate__simd_8h.js @@ -88,6 +88,7 @@ var accelerate__simd_8h = [ "mlx::core::simd::operator||", "namespacemlx_1_1core_1_1simd.html#ab380b8f73672727a38ea0931e731fe4a", null ], [ "mlx::core::simd::operator||", "namespacemlx_1_1core_1_1simd.html#ab2bc61c02b9096163e9db91a3f88788f", null ], [ "mlx::core::simd::operator||", "namespacemlx_1_1core_1_1simd.html#ac34f6b278627949d2ee68cdbf3d2f50f", null ], + [ "mlx::core::simd::operator~", "namespacemlx_1_1core_1_1simd.html#a290787dda17296d27af7afdef3c732a9", null ], [ "mlx::core::simd::pow", "namespacemlx_1_1core_1_1simd.html#ab18b3a88a2439fd026b6551b38d1f14a", null ], [ "mlx::core::simd::prod", "namespacemlx_1_1core_1_1simd.html#a271cedfc48efc69db43813e8c424bf7c", null ], [ "mlx::core::simd::recip", "namespacemlx_1_1core_1_1simd.html#ae344abefc91c7d9c0a9506c868a84d61", null ], diff --git a/docs/build/html/accelerate__simd_8h_source.html b/docs/build/html/accelerate__simd_8h_source.html index ef1d9e513..2dcaf3d84 100644 --- a/docs/build/html/accelerate__simd_8h_source.html +++ b/docs/build/html/accelerate__simd_8h_source.html @@ -268,257 +268,265 @@ $(function(){initNavTree('accelerate__simd_8h_source.html',''); initResizable(tr
139
140template <typename T, int N>
-
141Simd<bool, N> isnan(Simd<T, N> v) {
-
142 return asd::convert<char>(v.value != v.value);
+
141Simd<T, N> operator~(Simd<T, N> v) {
+
142 return ~v.value;
143}
144
-
145// No simd_boolN in accelerate, use int8_t instead
-
146template <typename T, int N>
-
-
147Simd<bool, N> operator!(Simd<T, N> v) {
-
148 return asd::convert<char>(!v.value);
-
149}
+
145template <typename T, int N>
+
+
146Simd<bool, N> isnan(Simd<T, N> v) {
+
147 return asd::convert<char>(v.value != v.value);
+
148}
-
150
-
-
151#define SIMD_DEFAULT_BINARY(OP) \
-
152 template <typename T, typename U, int N> \
-
153 Simd<T, N> operator OP(Simd<T, N> x, U y) { \
-
154 return asd::convert<typename Simd<T, N>::scalar_t>(x.value OP y); \
-
155 } \
-
156 template <typename T1, typename T2, int N> \
-
157 Simd<T2, N> operator OP(T1 x, Simd<T2, N> y) { \
-
158 return asd::convert<typename Simd<T2, N>::scalar_t>(x OP y.value); \
-
159 } \
-
160 template <typename T1, typename T2, int N> \
-
161 Simd<T1, N> operator OP(Simd<T1, N> x, Simd<T2, N> y) { \
-
162 return asd::convert<typename Simd<T1, N>::scalar_t>(x.value OP y.value); \
-
163 }
+
149
+
150// No simd_boolN in accelerate, use int8_t instead
+
151template <typename T, int N>
+
+
152Simd<bool, N> operator!(Simd<T, N> v) {
+
153 return asd::convert<char>(!v.value);
+
154}
-
164
-
165SIMD_DEFAULT_BINARY(+)
-
166SIMD_DEFAULT_BINARY(-)
-
167SIMD_DEFAULT_BINARY(/)
-
168SIMD_DEFAULT_BINARY(*)
-
169SIMD_DEFAULT_BINARY(<<)
-
170SIMD_DEFAULT_BINARY(>>)
-
171SIMD_DEFAULT_BINARY(|)
-
172SIMD_DEFAULT_BINARY(^)
-
173SIMD_DEFAULT_BINARY(&)
-
174SIMD_DEFAULT_BINARY(&&)
-
175SIMD_DEFAULT_BINARY(||)
-
176
-
-
177#define SIMD_DEFAULT_COMPARISONS(OP) \
-
178 template <int N, typename T, typename U> \
-
179 Simd<bool, N> operator OP(Simd<T, N> a, U b) { \
-
180 return asd::convert<char>(a.value OP b); \
-
181 } \
-
182 template <int N, typename T, typename U> \
-
183 Simd<bool, N> operator OP(T a, Simd<U, N> b) { \
-
184 return asd::convert<char>(a OP b.value); \
-
185 } \
-
186 template <int N, typename T1, typename T2> \
-
187 Simd<bool, N> operator OP(Simd<T1, N> a, Simd<T2, N> b) { \
-
188 return asd::convert<char>(a.value OP b.value); \
-
189 }
+
155
+
+
156#define SIMD_DEFAULT_BINARY(OP) \
+
157 template <typename T, typename U, int N> \
+
158 Simd<T, N> operator OP(Simd<T, N> x, U y) { \
+
159 return asd::convert<typename Simd<T, N>::scalar_t>(x.value OP y); \
+
160 } \
+
161 template <typename T1, typename T2, int N> \
+
162 Simd<T2, N> operator OP(T1 x, Simd<T2, N> y) { \
+
163 return asd::convert<typename Simd<T2, N>::scalar_t>(x OP y.value); \
+
164 } \
+
165 template <typename T1, typename T2, int N> \
+
166 Simd<T1, N> operator OP(Simd<T1, N> x, Simd<T2, N> y) { \
+
167 return asd::convert<typename Simd<T1, N>::scalar_t>(x.value OP y.value); \
+
168 }
-
190
-
-
191SIMD_DEFAULT_COMPARISONS(>)
-
192SIMD_DEFAULT_COMPARISONS(<)
+
169
+
170SIMD_DEFAULT_BINARY(+)
+
171SIMD_DEFAULT_BINARY(-)
+
172SIMD_DEFAULT_BINARY(/)
+
173SIMD_DEFAULT_BINARY(*)
+
174SIMD_DEFAULT_BINARY(<<)
+
175SIMD_DEFAULT_BINARY(>>)
+
176SIMD_DEFAULT_BINARY(|)
+
177SIMD_DEFAULT_BINARY(^)
+
178SIMD_DEFAULT_BINARY(&)
+
179SIMD_DEFAULT_BINARY(&&)
+
180SIMD_DEFAULT_BINARY(||)
+
181
+
+
182#define SIMD_DEFAULT_COMPARISONS(OP) \
+
183 template <int N, typename T, typename U> \
+
184 Simd<bool, N> operator OP(Simd<T, N> a, U b) { \
+
185 return asd::convert<char>(a.value OP b); \
+
186 } \
+
187 template <int N, typename T, typename U> \
+
188 Simd<bool, N> operator OP(T a, Simd<U, N> b) { \
+
189 return asd::convert<char>(a OP b.value); \
+
190 } \
+
191 template <int N, typename T1, typename T2> \
+
192 Simd<bool, N> operator OP(Simd<T1, N> a, Simd<T2, N> b) { \
+
193 return asd::convert<char>(a.value OP b.value); \
+
194 }
-
-
193SIMD_DEFAULT_COMPARISONS(>=)
-
194SIMD_DEFAULT_COMPARISONS(<=)
+
195
+ -
195SIMD_DEFAULT_COMPARISONS(==)
-
196SIMD_DEFAULT_COMPARISONS(!=)
-
197
-
198template <typename T, int N>
-
-
199Simd<T, N> atan2(Simd<T, N> a, Simd<T, N> b) {
-
200 return asd::atan2(a.value, b.value);
-
201}
+ +
200SIMD_DEFAULT_COMPARISONS(==)
+
201SIMD_DEFAULT_COMPARISONS(!=)
202
-
203template <typename T, int N>
+
203template <typename T, int N>
-
204Simd<T, N> maximum(Simd<T, N> a, Simd<T, N> b) {
-
205 // TODO add isnan
-
206 return asd::max(a.value, b.value);
-
207}
+
204Simd<T, N> atan2(Simd<T, N> a, Simd<T, N> b) {
+
205 return asd::atan2(a.value, b.value);
+
206}
-
208
-
209template <typename T, int N>
-
-
210Simd<T, N> minimum(Simd<T, N> a, Simd<T, N> b) {
-
211 // TODO add isnan
-
212 return asd::min(a.value, b.value);
-
213}
+
207
+
208template <typename T, int N>
+
+
209Simd<T, N> maximum(Simd<T, N> a, Simd<T, N> b) {
+
210 // TODO add isnan
+
211 return asd::max(a.value, b.value);
+
212}
-
214
-
215template <typename T, int N>
-
-
216Simd<T, N> remainder(Simd<T, N> a, Simd<T, N> b) {
-
217 Simd<T, N> r;
-
218 if constexpr (!std::is_integral_v<T>) {
-
219 r = asd::remainder(a.value, b.value);
-
220 } else {
-
221 r = a - b * (a / b);
-
222 }
-
223 if constexpr (std::is_signed_v<T>) {
-
224 auto mask = r != 0 && (r < 0 != b < 0);
-
225 r = select(mask, r + b, r);
-
226 }
-
227 return r;
-
228}
+
213
+
214template <typename T, int N>
+
+
215Simd<T, N> minimum(Simd<T, N> a, Simd<T, N> b) {
+
216 // TODO add isnan
+
217 return asd::min(a.value, b.value);
+
218}
-
229
-
230template <typename MaskT, typename T1, typename T2, int N>
-
-
231Simd<T1, N> select(Simd<MaskT, N> mask, Simd<T1, N> x, Simd<T2, N> y) {
-
232 if constexpr (sizeof(T1) == 1) {
-
233 return asd::bitselect(y.value, x.value, asd::convert<char>(mask.value));
-
234 } else if constexpr (sizeof(T1) == 2) {
-
235 return asd::bitselect(y.value, x.value, asd::convert<short>(mask.value));
-
236 } else if constexpr (sizeof(T1) == 4) {
-
237 return asd::bitselect(y.value, x.value, asd::convert<int>(mask.value));
-
238 } else {
-
239 return asd::bitselect(y.value, x.value, asd::convert<long>(mask.value));
-
240 }
-
241}
+
219
+
220template <typename T, int N>
+
+
221Simd<T, N> remainder(Simd<T, N> a, Simd<T, N> b) {
+
222 Simd<T, N> r;
+
223 if constexpr (!std::is_integral_v<T>) {
+
224 r = asd::remainder(a.value, b.value);
+
225 } else {
+
226 r = a - b * (a / b);
+
227 }
+
228 if constexpr (std::is_signed_v<T>) {
+
229 auto mask = r != 0 && (r < 0 != b < 0);
+
230 r = select(mask, r + b, r);
+
231 }
+
232 return r;
+
233}
-
242
-
243template <typename T, int N>
-
-
244Simd<T, N> pow(Simd<T, N> base, Simd<T, N> exp) {
-
245 if constexpr (!std::is_integral_v<T>) {
-
246 return asd::pow(base.value, exp.value);
-
247 } else {
-
248 Simd<T, N> res = 1;
-
249 while (any(exp)) {
-
250 res = select(exp & 1, res * base, res);
-
251 base = select(exp, base * base, base);
-
252 exp = exp >> 1;
-
253 }
-
254 return res;
-
255 }
-
256}
+
234
+
235template <typename MaskT, typename T1, typename T2, int N>
+
+
236Simd<T1, N> select(Simd<MaskT, N> mask, Simd<T1, N> x, Simd<T2, N> y) {
+
237 if constexpr (sizeof(T1) == 1) {
+
238 return asd::bitselect(y.value, x.value, asd::convert<char>(mask.value));
+
239 } else if constexpr (sizeof(T1) == 2) {
+
240 return asd::bitselect(y.value, x.value, asd::convert<short>(mask.value));
+
241 } else if constexpr (sizeof(T1) == 4) {
+
242 return asd::bitselect(y.value, x.value, asd::convert<int>(mask.value));
+
243 } else {
+
244 return asd::bitselect(y.value, x.value, asd::convert<long>(mask.value));
+
245 }
+
246}
-
257
-
258template <typename T, int N>
-
-
259Simd<T, N> clamp(Simd<T, N> v, Simd<T, N> min, Simd<T, N> max) {
-
260 return asd::clamp(v.value, min.value, max.value);
+
247
+
248template <typename T, int N>
+
+
249Simd<T, N> pow(Simd<T, N> base, Simd<T, N> exp) {
+
250 if constexpr (!std::is_integral_v<T>) {
+
251 return asd::pow(base.value, exp.value);
+
252 } else {
+
253 Simd<T, N> res = 1;
+
254 while (any(exp)) {
+
255 res = select(exp & 1, res * base, res);
+
256 base = select(exp, base * base, base);
+
257 exp = exp >> 1;
+
258 }
+
259 return res;
+
260 }
261}
262
-
263template <typename T, typename U, int N>
+
263template <typename T, int N>
-
264Simd<T, N> fma(Simd<T, N> x, Simd<T, N> y, U z) {
-
265 return asd::muladd(x.value, y.value, Simd<T, N>(z).value);
+
264Simd<T, N> clamp(Simd<T, N> v, Simd<T, N> min, Simd<T, N> max) {
+
265 return asd::clamp(v.value, min.value, max.value);
266}
267
-
268// Reductions
-
269
-
270template <typename T, int N>
-
-
271bool all(Simd<T, N> x) {
-
272 return asd::all(x.value);
-
273}
+
268template <typename T, typename U, int N>
+
+
269Simd<T, N> fma(Simd<T, N> x, Simd<T, N> y, U z) {
+
270 return asd::muladd(x.value, y.value, Simd<T, N>(z).value);
+
271}
-
274template <typename T, int N>
-
-
275bool any(Simd<T, N> x) {
-
276 return asd::any(x.value);
-
277}
+
272
+
273// Reductions
+
274
+
275template <typename T, int N>
+
+
276bool all(Simd<T, N> x) {
+
277 return asd::all(x.value);
+
278}
-
278template <typename T, int N>
-
-
279T sum(Simd<T, N> x) {
-
280 return asd::reduce_add(x.value);
-
281}
+
279template <typename T, int N>
+
+
280bool any(Simd<T, N> x) {
+
281 return asd::any(x.value);
+
282}
-
282template <typename T, int N>
-
-
283T max(Simd<T, N> x) {
-
284 return asd::reduce_max(x.value);
-
285}
+
283template <typename T, int N>
+
+
284T sum(Simd<T, N> x) {
+
285 return asd::reduce_add(x.value);
+
286}
-
286template <typename T, int N>
-
-
287T min(Simd<T, N> x) {
-
288 return asd::reduce_min(x.value);
-
289}
+
287template <typename T, int N>
+
+
288T max(Simd<T, N> x) {
+
289 return asd::reduce_max(x.value);
+
290}
-
290
291template <typename T, int N>
-
292T prod(Simd<T, N> x) {
-
293 auto ptr = (T*)&x;
-
294 auto lhs = load<T, N / 2>(ptr);
-
295 auto rhs = load<T, N / 2>(ptr + N / 2);
-
296 return prod(lhs * rhs);
-
297}
+
292T min(Simd<T, N> x) {
+
293 return asd::reduce_min(x.value);
+
294}
-
298
-
299} // namespace mlx::core::simd
-
300
-
301#if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-
302#include "mlx/backend/cpu/simd/accelerate_fp16_simd.h"
-
303#endif
+
295
+
296template <typename T, int N>
+
+
297T prod(Simd<T, N> x) {
+
298 auto ptr = (T*)&x;
+
299 auto lhs = load<T, N / 2>(ptr);
+
300 auto rhs = load<T, N / 2>(ptr + N / 2);
+
301 return prod(lhs * rhs);
+
302}
+
+
303
+
304} // namespace mlx::core::simd
+
305
+
306#if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+
307#include "mlx/backend/cpu/simd/accelerate_fp16_simd.h"
+
308#endif
accelerate_fp16_simd.h
SIMD_DEFAULT_UNARY
#define SIMD_DEFAULT_UNARY(name, op)
Definition accelerate_simd.h:106
-
SIMD_DEFAULT_BINARY
#define SIMD_DEFAULT_BINARY(OP)
Definition accelerate_simd.h:151
-
SIMD_DEFAULT_COMPARISONS
#define SIMD_DEFAULT_COMPARISONS(OP)
Definition accelerate_simd.h:177
+
SIMD_DEFAULT_BINARY
#define SIMD_DEFAULT_BINARY(OP)
Definition accelerate_simd.h:156
+
SIMD_DEFAULT_COMPARISONS
#define SIMD_DEFAULT_COMPARISONS(OP)
Definition accelerate_simd.h:182
base_simd.h
mlx::core::simd
Definition accelerate_fp16_simd.h:9
-
mlx::core::simd::isnan
Simd< bool, N > isnan(Simd< T, N > v)
Definition accelerate_simd.h:141
+
mlx::core::simd::isnan
Simd< bool, N > isnan(Simd< T, N > v)
Definition accelerate_simd.h:146
mlx::core::simd::sinh
Simd< float16_t, N > sinh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:41
mlx::core::simd::N
constexpr int N
Definition neon_fp16_simd.h:9
mlx::core::simd::atanh
Simd< float16_t, N > atanh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:34
-
mlx::core::simd::minimum
Simd< T, N > minimum(Simd< T, N > a, Simd< T, N > b)
Definition accelerate_simd.h:210
+
mlx::core::simd::minimum
Simd< T, N > minimum(Simd< T, N > a, Simd< T, N > b)
Definition accelerate_simd.h:215
mlx::core::simd::pow
Simd< float16_t, N > pow(Simd< float16_t, N > x, Simd< float16_t, N > y)
Definition accelerate_fp16_simd.h:54
mlx::core::simd::atan2
Simd< float16_t, N > atan2(Simd< float16_t, N > x, Simd< float16_t, N > y)
Definition accelerate_fp16_simd.h:52
-
mlx::core::simd::prod
T prod(Simd< T, N > x)
Definition accelerate_simd.h:292
+
mlx::core::simd::prod
T prod(Simd< T, N > x)
Definition accelerate_simd.h:297
+
mlx::core::simd::operator~
Simd< T, N > operator~(Simd< T, N > v)
Definition accelerate_simd.h:141
mlx::core::simd::log10
Simd< float16_t, N > log10(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:39
mlx::core::simd::rint
Simd< T, N > rint(Simd< T, N > v)
Definition accelerate_simd.h:127
-
mlx::core::simd::load
Simd< T, N > load(const T *x)
Definition base_simd.h:27
+
mlx::core::simd::load
Simd< T, N > load(const T *x)
Definition base_simd.h:28
mlx::core::simd::tan
Simd< float16_t, N > tan(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:42
mlx::core::simd::abs
Simd< T, N > abs(Simd< T, N > v)
Definition accelerate_simd.h:112
mlx::core::simd::acosh
Simd< float16_t, N > acosh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:30
-
mlx::core::simd::all
bool all(Simd< T, N > x)
Definition accelerate_simd.h:271
-
mlx::core::simd::sum
T sum(Simd< T, N > x)
Definition accelerate_simd.h:279
+
mlx::core::simd::all
bool all(Simd< T, N > x)
Definition accelerate_simd.h:276
+
mlx::core::simd::sum
T sum(Simd< T, N > x)
Definition accelerate_simd.h:284
mlx::core::simd::log2
Simd< float16_t, N > log2(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:38
-
mlx::core::simd::max
T max(Simd< T, N > x)
Definition accelerate_simd.h:283
-
mlx::core::simd::operator!
Simd< bool, N > operator!(Simd< T, N > v)
Definition accelerate_simd.h:147
-
mlx::core::simd::maximum
Simd< T, N > maximum(Simd< T, N > a, Simd< T, N > b)
Definition accelerate_simd.h:204
+
mlx::core::simd::max
T max(Simd< T, N > x)
Definition accelerate_simd.h:288
+
mlx::core::simd::operator!
Simd< bool, N > operator!(Simd< T, N > v)
Definition accelerate_simd.h:152
+
mlx::core::simd::maximum
Simd< T, N > maximum(Simd< T, N > a, Simd< T, N > b)
Definition accelerate_simd.h:209
mlx::core::simd::exp
Simd< T, N > exp(Simd< T, N > in)
Compute exp(x) in an optimizer friendly way as follows:
Definition math.h:28
mlx::core::simd::log
Simd< float16_t, N > log(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:37
mlx::core::simd::floor
Simd< T, N > floor(Simd< T, N > v)
Definition accelerate_simd.h:113
mlx::core::simd::expm1
Simd< float16_t, N > expm1(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:36
mlx::core::simd::asin
Simd< float16_t, N > asin(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:31
-
mlx::core::simd::any
bool any(Simd< T, N > x)
Definition accelerate_simd.h:275
-
mlx::core::simd::fma
Simd< T, N > fma(Simd< T, N > x, Simd< T, N > y, U z)
Definition accelerate_simd.h:264
+
mlx::core::simd::any
bool any(Simd< T, N > x)
Definition accelerate_simd.h:280
+
mlx::core::simd::fma
Simd< T, N > fma(Simd< T, N > x, Simd< T, N > y, U z)
Definition accelerate_simd.h:269
mlx::core::simd::tanh
Simd< float16_t, N > tanh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:43
mlx::core::simd::atan
Simd< float16_t, N > atan(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:33
mlx::core::simd::asinh
Simd< float16_t, N > asinh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:32
mlx::core::simd::remainder
Simd< float16_t, N > remainder(Simd< float16_t, N > x, Simd< float16_t, N > y)
Definition accelerate_fp16_simd.h:53
-
mlx::core::simd::max_size
static constexpr int max_size
Definition base_simd.h:13
-
mlx::core::simd::min
T min(Simd< T, N > x)
Definition accelerate_simd.h:287
+
mlx::core::simd::max_size
static constexpr int max_size
Definition base_simd.h:14
+
mlx::core::simd::min
T min(Simd< T, N > x)
Definition accelerate_simd.h:292
mlx::core::simd::log1p
Simd< float16_t, N > log1p(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:40
mlx::core::simd::ceil
Simd< T, N > ceil(Simd< T, N > v)
Definition accelerate_simd.h:120
mlx::core::simd::recip
Simd< T, N > recip(Simd< T, N > v)
Definition accelerate_simd.h:131
mlx::core::simd::sqrt
Simd< T, N > sqrt(Simd< T, N > v)
Definition accelerate_simd.h:129
-
mlx::core::simd::clamp
Simd< T, N > clamp(Simd< T, N > v, Simd< T, N > min, Simd< T, N > max)
Definition accelerate_simd.h:259
+
mlx::core::simd::clamp
Simd< T, N > clamp(Simd< T, N > v, Simd< T, N > min, Simd< T, N > max)
Definition accelerate_simd.h:264
mlx::core::simd::acos
Simd< float16_t, N > acos(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:29
mlx::core::simd::rsqrt
Simd< T, N > rsqrt(Simd< T, N > v)
Definition accelerate_simd.h:130
mlx::core::simd::cosh
Simd< float16_t, N > cosh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:35
-
mlx::core::simd::select
Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
Definition accelerate_simd.h:231
+
mlx::core::simd::select
Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
Definition accelerate_simd.h:236
mlx::core::simd::ScalarT< bool, N >::v
char v
Definition accelerate_simd.h:39
mlx::core::simd::ScalarT< int64_t, N >::v
long v
Definition accelerate_simd.h:51
mlx::core::simd::ScalarT< int8_t, N >::v
char v
Definition accelerate_simd.h:43
diff --git a/docs/build/html/annotated.html b/docs/build/html/annotated.html index cfe35a9a1..dca09161f 100644 --- a/docs/build/html/annotated.html +++ b/docs/build/html/annotated.html @@ -134,57 +134,58 @@ $(function(){initNavTree('annotated.html',''); initResizable(true); });  CArcTan2  CArcTanh  CBitwiseAnd - CBitwiseOr - CBitwiseXor - CCeil - CConjugate - CCos - CCosh - CDivide - CEqual - CErf - CErfInv - CExp - CExpm1 - CFloor - CGreater - CGreaterEqual - CImag - CInTracing - CLeftShift - CLess - CLessEqual - CLog - CLog10 - CLog1p - CLog2 - CLogAddExp - CLogicalAnd - CLogicalNot - CLogicalOr - CMaximum - CMinimum - CMultiply - CNaNEqual - CNegative - CNotEqual - CPower - CReal - CRemainder - CRetainGraph - CRightShift - CRound - CRsqrt - CSelect - CSigmoid - CSign - CSin - CSinh - CSqrt - CSquare - CSubtract - CTan - CTanh + CBitwiseInvert + CBitwiseOr + CBitwiseXor + CCeil + CConjugate + CCos + CCosh + CDivide + CEqual + CErf + CErfInv + CExp + CExpm1 + CFloor + CGreater + CGreaterEqual + CImag + CInTracing + CLeftShift + CLess + CLessEqual + CLog + CLog10 + CLog1p + CLog2 + CLogAddExp + CLogicalAnd + CLogicalNot + CLogicalOr + CMaximum + CMinimum + CMultiply + CNaNEqual + CNegative + CNotEqual + CPower + CReal + CRemainder + CRetainGraph + CRightShift + CRound + CRsqrt + CSelect + CSigmoid + CSign + CSin + CSinh + CSqrt + CSquare + CSubtract + CTan + CTanh  ►Ndistributed  ►Ndetail  CGroupImplAbstract base class of a distributed group implementation @@ -256,124 +257,127 @@ $(function(){initNavTree('annotated.html',''); initResizable(true); });  CAsStrided  CAsType  CBitwiseBinary - CBlockMaskedMM - CBroadcast - CBroadcastAxes - CCeil - CCholesky - ►CCommandEncoder - CConcurrentContext - CCompiled - Ccomplex128_t - Ccomplex64_t - CConcatenate - CConjugate - CContiguous - CContiguousIterator - CConvolution - CCopy - CCos - CCosh - CCustomTransforms - CDepends - CDevice - CDivide - CDivMod - CDtype - CDynamicSlice - CDynamicSliceUpdate - CEigh - CEqual - CErf - CErfInv - CEvent - CExp - CExpandDims - CExpm1 - CFence - CFFT - CfinfoHolds information about floating-point types - CFlatten - CFloor - CFull - CFunctionExporter - CGather - CGatherAxis - CGatherMM - CGatherQMM - CGreater - CGreaterEqual - CHadamard - CImag - CImportedFunction - CInverse - CJitCompiler - CLess - CLessEqual - CLoad - CLog - CLog1p - CLogAddExp - CLogicalAnd - CLogicalNot - CLogicalOr - CMatmul - CMaximum - CMinimum - CMultiply - CNegative - CNodeNamer - CNotEqual - CNumberOfElements - Cnumeric_limits - Cnumeric_limits< bfloat16_t > - Cnumeric_limits< float > - Cnumeric_limits< float16_t > - CPad - CPartition - CPower - CPrimitive - CPrintFormatter - CQRF - CQuantizedMatmul - CRandomBits - CReal - CReduce - CReductionPlan - CRemainder - CReshape - CRound - CScalarVector - CScan - CScatter - CScatterAxis - CSelect - CSigmoid - CSign - CSin - CSinh - CSlice - CSliceUpdate - CSoftmax - CSort - CSplit - CSqrt - CSquare - CSqueeze - CStopGradient - CStream - CStreamContext - CSubtract - CSVD - CTan - CTanh - CTranspose - CTypeToDtype - CUnaryPrimitive - CUnflatten - CVectorScalar - CVectorVector - CView + CBitwiseInvert + CBlockMaskedMM + CBroadcast + CBroadcastAxes + CCeil + CCholesky + ►CCommandEncoder + CConcurrentContext + CCompiled + Ccomplex128_t + Ccomplex64_t + CConcatenate + CConjugate + CContiguous + CContiguousIterator + CConvolution + CCopy + CCos + CCosh + CCustomTransforms + CDepends + CDevice + CDivide + CDivMod + CDtype + CDynamicSlice + CDynamicSliceUpdate + CEigh + CEqual + CErf + CErfInv + CEvent + CExp + CExpandDims + CExpm1 + CFence + CFFT + CfinfoHolds information about floating-point types + CFlatten + CFloor + CFull + CFunctionExporter + CGather + CGatherAxis + CGatherMM + CGatherQMM + CGreater + CGreaterEqual + CHadamard + CImag + CImportedFunction + CInverse + CJitCompiler + CLess + CLessEqual + CLoad + CLog + CLog1p + CLogAddExp + CLogicalAnd + CLogicalNot + CLogicalOr + CLUF + CMatmul + CMaximum + CMinimum + CMultiply + CNegative + CNodeNamer + CNotEqual + CNumberOfElements + Cnumeric_limits + Cnumeric_limits< bfloat16_t > + Cnumeric_limits< double > + Cnumeric_limits< float > + Cnumeric_limits< float16_t > + CPad + CPartition + CPower + CPrimitive + CPrintFormatter + CQRF + CQuantizedMatmul + CRandomBits + CReal + CReduce + CReductionPlan + CRemainder + CReshape + CRound + CScalarVector + CScan + CScatter + CScatterAxis + CSelect + CSigmoid + CSign + CSin + CSinh + CSlice + CSliceUpdate + CSoftmax + CSort + CSplit + CSqrt + CSquare + CSqueeze + CStopGradient + CStream + CStreamContext + CSubtract + CSVD + CTan + CTanh + CTranspose + CTypeToDtype + CUnaryPrimitive + CUnflatten + CVectorScalar + CVectorVector + CView  ►Nsteel  CAccumHelper  CAttnParams @@ -462,111 +466,112 @@ $(function(){initNavTree('annotated.html',''); initResizable(true); });  CArcTan2  CArcTanh  CBitwiseAnd - CBitwiseOr - CBitwiseXor - CBlockMergeSort - Cbool4_or_uint - CCeil - Ccomplex64_t - CConditionalType - CConditionalType< true, T, U > - CConjugate - CCos - CCosh - CCumMax - CCumMin - CCumProd - CCumProd< bool > - CCumSum - CDivide - CDivMod - CDivOp - CEqual - CErf - CErfInv - CExp - CExpm1 - CExpSubOp - CFloor - CFloorDivide - CGEMVKernel - CGEMVTKernelVector matrix multiplication - CGreater - CGreaterEqual - CImag - CIndices - CKernelMergeSort - CKernelMultiBlockMergeSort - CLeftShift - CLess - CLessEqual - CLessThan - CLimits - CLimits< bfloat16_t > - CLimits< bool > - CLimits< complex64_t > - CLimits< float > - CLimits< half > - CLimits< int16_t > - CLimits< int32_t > - CLimits< int64_t > - CLimits< int8_t > - CLimits< uint16_t > - CLimits< uint32_t > - CLimits< uint64_t > - CLimits< uint8_t > - CLog - CLog10 - CLog1p - CLog2 - CLogAddExp - CLogicalAnd - CLogicalNot - CLogicalOr - CLoopedElemToLoc - CLoopedElemToLoc< 1, OffsetT, false > - CLoopedElemToLoc< 1, OffsetT, true > - CMax - CMaximum - CMaxOp - CMin - CMinimum - Cmlx_atomic - Cmlx_atomic< T, enable_if_t< is_metal_atomic< T > > > - CMLXConvParams - CMulOp - CMultiply - CNaNEqual - CNegative - CNone - CNotEqual - COr - CPower - CProd - CQuantizedBlockLoader - CReadWriter - CReal - CRemainder - CRightShift - CRound - CRsqrt - CScaleOp - CSelect - CSigmoid - CSign - CSin - CSinh - CSqrt - CSquare - CSubOp - CSubtract - CSum - CSumOp - CTan - CTanh - CThreadPool - CThreadSort - CTransformScale + CBitwiseInvert + CBitwiseOr + CBitwiseXor + CBlockMergeSort + Cbool4_or_uint + CCeil + Ccomplex64_t + CConditionalType + CConditionalType< true, T, U > + CConjugate + CCos + CCosh + CCumMax + CCumMin + CCumProd + CCumProd< bool > + CCumSum + CDivide + CDivMod + CDivOp + CEqual + CErf + CErfInv + CExp + CExpm1 + CExpSubOp + CFloor + CFloorDivide + CGEMVKernel + CGEMVTKernelVector matrix multiplication + CGreater + CGreaterEqual + CImag + CIndices + CKernelMergeSort + CKernelMultiBlockMergeSort + CLeftShift + CLess + CLessEqual + CLessThan + CLimits + CLimits< bfloat16_t > + CLimits< bool > + CLimits< complex64_t > + CLimits< float > + CLimits< half > + CLimits< int16_t > + CLimits< int32_t > + CLimits< int64_t > + CLimits< int8_t > + CLimits< uint16_t > + CLimits< uint32_t > + CLimits< uint64_t > + CLimits< uint8_t > + CLog + CLog10 + CLog1p + CLog2 + CLogAddExp + CLogicalAnd + CLogicalNot + CLogicalOr + CLoopedElemToLoc + CLoopedElemToLoc< 1, OffsetT, false > + CLoopedElemToLoc< 1, OffsetT, true > + CMax + CMaximum + CMaxOp + CMin + CMinimum + Cmlx_atomic + Cmlx_atomic< T, enable_if_t< is_metal_atomic< T > > > + CMLXConvParams + CMulOp + CMultiply + CNaNEqual + CNegative + CNone + CNotEqual + COr + CPower + CProd + CQuantizedBlockLoader + CReadWriter + CReal + CRemainder + CRightShift + CRound + CRsqrt + CScaleOp + CSelect + CSigmoid + CSign + CSin + CSinh + CSqrt + CSquare + CSubOp + CSubtract + CSum + CSumOp + CTan + CTanh + CThreadPool + CThreadSort + CTransformScale
diff --git a/docs/build/html/annotated_dup.js b/docs/build/html/annotated_dup.js index 766f5fb1d..47263365a 100644 --- a/docs/build/html/annotated_dup.js +++ b/docs/build/html/annotated_dup.js @@ -29,6 +29,7 @@ var annotated_dup = [ "ArcTan2", "structmlx_1_1core_1_1detail_1_1_arc_tan2.html", "structmlx_1_1core_1_1detail_1_1_arc_tan2" ], [ "ArcTanh", "structmlx_1_1core_1_1detail_1_1_arc_tanh.html", "structmlx_1_1core_1_1detail_1_1_arc_tanh" ], [ "BitwiseAnd", "structmlx_1_1core_1_1detail_1_1_bitwise_and.html", "structmlx_1_1core_1_1detail_1_1_bitwise_and" ], + [ "BitwiseInvert", "structmlx_1_1core_1_1detail_1_1_bitwise_invert.html", "structmlx_1_1core_1_1detail_1_1_bitwise_invert" ], [ "BitwiseOr", "structmlx_1_1core_1_1detail_1_1_bitwise_or.html", "structmlx_1_1core_1_1detail_1_1_bitwise_or" ], [ "BitwiseXor", "structmlx_1_1core_1_1detail_1_1_bitwise_xor.html", "structmlx_1_1core_1_1detail_1_1_bitwise_xor" ], [ "Ceil", "structmlx_1_1core_1_1detail_1_1_ceil.html", "structmlx_1_1core_1_1detail_1_1_ceil" ], @@ -156,6 +157,7 @@ var annotated_dup = [ "AsStrided", "classmlx_1_1core_1_1_as_strided.html", "classmlx_1_1core_1_1_as_strided" ], [ "AsType", "classmlx_1_1core_1_1_as_type.html", "classmlx_1_1core_1_1_as_type" ], [ "BitwiseBinary", "classmlx_1_1core_1_1_bitwise_binary.html", "classmlx_1_1core_1_1_bitwise_binary" ], + [ "BitwiseInvert", "classmlx_1_1core_1_1_bitwise_invert.html", "classmlx_1_1core_1_1_bitwise_invert" ], [ "BlockMaskedMM", "classmlx_1_1core_1_1_block_masked_m_m.html", "classmlx_1_1core_1_1_block_masked_m_m" ], [ "Broadcast", "classmlx_1_1core_1_1_broadcast.html", "classmlx_1_1core_1_1_broadcast" ], [ "BroadcastAxes", "classmlx_1_1core_1_1_broadcast_axes.html", "classmlx_1_1core_1_1_broadcast_axes" ], @@ -216,6 +218,7 @@ var annotated_dup = [ "LogicalAnd", "classmlx_1_1core_1_1_logical_and.html", "classmlx_1_1core_1_1_logical_and" ], [ "LogicalNot", "classmlx_1_1core_1_1_logical_not.html", "classmlx_1_1core_1_1_logical_not" ], [ "LogicalOr", "classmlx_1_1core_1_1_logical_or.html", "classmlx_1_1core_1_1_logical_or" ], + [ "LUF", "classmlx_1_1core_1_1_l_u_f.html", "classmlx_1_1core_1_1_l_u_f" ], [ "Matmul", "classmlx_1_1core_1_1_matmul.html", "classmlx_1_1core_1_1_matmul" ], [ "Maximum", "classmlx_1_1core_1_1_maximum.html", "classmlx_1_1core_1_1_maximum" ], [ "Minimum", "classmlx_1_1core_1_1_minimum.html", "classmlx_1_1core_1_1_minimum" ], @@ -226,6 +229,7 @@ var annotated_dup = [ "NumberOfElements", "classmlx_1_1core_1_1_number_of_elements.html", "classmlx_1_1core_1_1_number_of_elements" ], [ "numeric_limits", "structmlx_1_1core_1_1numeric__limits.html", null ], [ "numeric_limits< bfloat16_t >", "structmlx_1_1core_1_1numeric__limits_3_01bfloat16__t_01_4.html", "structmlx_1_1core_1_1numeric__limits_3_01bfloat16__t_01_4" ], + [ "numeric_limits< double >", "structmlx_1_1core_1_1numeric__limits_3_01double_01_4.html", null ], [ "numeric_limits< float >", "structmlx_1_1core_1_1numeric__limits_3_01float_01_4.html", null ], [ "numeric_limits< float16_t >", "structmlx_1_1core_1_1numeric__limits_3_01float16__t_01_4.html", "structmlx_1_1core_1_1numeric__limits_3_01float16__t_01_4" ], [ "Pad", "classmlx_1_1core_1_1_pad.html", "classmlx_1_1core_1_1_pad" ], @@ -365,6 +369,7 @@ var annotated_dup = [ "ArcTan2", "struct_arc_tan2.html", "struct_arc_tan2" ], [ "ArcTanh", "struct_arc_tanh.html", "struct_arc_tanh" ], [ "BitwiseAnd", "struct_bitwise_and.html", "struct_bitwise_and" ], + [ "BitwiseInvert", "struct_bitwise_invert.html", "struct_bitwise_invert" ], [ "BitwiseOr", "struct_bitwise_or.html", "struct_bitwise_or" ], [ "BitwiseXor", "struct_bitwise_xor.html", "struct_bitwise_xor" ], [ "BlockMergeSort", "struct_block_merge_sort.html", "struct_block_merge_sort" ], diff --git a/docs/build/html/array_8h_source.html b/docs/build/html/array_8h_source.html index efcd19057..b4507c380 100644 --- a/docs/build/html/array_8h_source.html +++ b/docs/build/html/array_8h_source.html @@ -368,448 +368,461 @@ $(function(){initNavTree('array_8h_source.html',''); initResizable(true); });
244 };
245
-
-
247 Primitive& primitive() const {
-
248 return *(array_desc_->primitive);
-
249 }
+
249 explicit array(
+
250 allocator::Buffer data,
+
251 Shape shape,
+
252 Dtype dtype,
+
253 Strides strides,
+
254 size_t data_size,
+
255 Flags flags,
+
256 Deleter deleter = allocator::free);
+
257
+
+
259 Primitive& primitive() const {
+
260 return *(array_desc_->primitive);
+
261 }
-
250
-
-
252 std::shared_ptr<Primitive>& primitive_ptr() const {
-
253 return array_desc_->primitive;
-
254 }
+
262
+
+
264 std::shared_ptr<Primitive>& primitive_ptr() const {
+
265 return array_desc_->primitive;
+
266 }
-
255
-
-
257 bool has_primitive() const {
-
258 return array_desc_->primitive != nullptr;
-
259 }
+
267
+
+
269 bool has_primitive() const {
+
270 return array_desc_->primitive != nullptr;
+
271 }
-
260
-
-
262 const std::vector<array>& inputs() const {
-
263 return array_desc_->inputs;
-
264 }
+
272
+
+
274 const std::vector<array>& inputs() const {
+
275 return array_desc_->inputs;
+
276 }
-
265
-
-
266 std::vector<array>& inputs() {
-
267 return array_desc_->inputs;
-
268 }
+
277
+
+
278 std::vector<array>& inputs() {
+
279 return array_desc_->inputs;
+
280 }
-
269
-
-
271 bool is_donatable() const {
-
272 return array_desc_.use_count() == 1 && (array_desc_->data.use_count() == 1);
-
273 }
+
281
+
+
283 bool is_donatable() const {
+
284 return array_desc_.use_count() == 1 && (array_desc_->data.use_count() == 1);
+
285 }
-
274
-
-
276 const std::vector<array>& siblings() const {
-
277 return array_desc_->siblings;
-
278 }
+
286
+
+
288 const std::vector<array>& siblings() const {
+
289 return array_desc_->siblings;
+
290 }
-
279
-
-
281 std::vector<array>& siblings() {
-
282 return array_desc_->siblings;
-
283 }
+
291
+
+
293 std::vector<array>& siblings() {
+
294 return array_desc_->siblings;
+
295 }
-
284
-
-
285 void set_siblings(std::vector<array> siblings, uint16_t position) {
-
286 array_desc_->siblings = std::move(siblings);
-
287 array_desc_->position = position;
-
288 }
-
-
289
-
-
292 std::vector<array> outputs() const {
-
293 auto idx = array_desc_->position;
-
294 std::vector<array> outputs;
-
295 outputs.reserve(siblings().size() + 1);
-
296 outputs.insert(outputs.end(), siblings().begin(), siblings().begin() + idx);
-
297 outputs.push_back(*this);
-
298 outputs.insert(outputs.end(), siblings().begin() + idx, siblings().end());
-
299 return outputs;
+
296
+
+
297 void set_siblings(std::vector<array> siblings, uint16_t position) {
+
298 array_desc_->siblings = std::move(siblings);
+
299 array_desc_->position = position;
300 }
301
-
303 void detach();
-
304
-
-
306 const Flags& flags() const {
-
307 return array_desc_->flags;
-
308 }
+
+
304 std::vector<array> outputs() const {
+
305 auto idx = array_desc_->position;
+
306 std::vector<array> outputs;
+
307 outputs.reserve(siblings().size() + 1);
+
308 outputs.insert(outputs.end(), siblings().begin(), siblings().begin() + idx);
+
309 outputs.push_back(*this);
+
310 outputs.insert(outputs.end(), siblings().begin() + idx, siblings().end());
+
311 return outputs;
+
312 }
-
309
-
-
320 size_t data_size() const {
-
321 return array_desc_->data_size;
-
322 }
+
313
+
315 void detach();
+
316
+
+
318 const Flags& flags() const {
+
319 return array_desc_->flags;
+
320 }
-
323
-
-
324 allocator::Buffer& buffer() {
-
325 return array_desc_->data->buffer;
-
326 }
+
321
+
+
332 size_t data_size() const {
+
333 return array_desc_->data_size;
+
334 }
-
-
327 const allocator::Buffer& buffer() const {
-
328 return array_desc_->data->buffer;
-
329 }
+
335
+
+
336 allocator::Buffer& buffer() {
+
337 return array_desc_->data->buffer;
+
338 }
-
330
-
-
331 size_t buffer_size() const {
-
332 return allocator::allocator().size(buffer());
-
333 }
+
+
339 const allocator::Buffer& buffer() const {
+
340 return array_desc_->data->buffer;
+
341 }
-
334
-
335 // Return a copy of the shared pointer
-
336 // to the array::Data struct
-
-
337 std::shared_ptr<Data> data_shared_ptr() const {
-
338 return array_desc_->data;
-
339 }
+
342
+
+
343 size_t buffer_size() const {
+
344 return allocator::allocator().size(buffer());
+
345 }
-
340 // Return a raw pointer to the arrays data
-
341 template <typename T>
-
-
342 T* data() {
-
343 return static_cast<T*>(array_desc_->data_ptr);
-
344 }
+
346
+
347 // Return a copy of the shared pointer
+
348 // to the array::Data struct
+
+
349 std::shared_ptr<Data> data_shared_ptr() const {
+
350 return array_desc_->data;
+
351 }
-
345
-
346 template <typename T>
-
-
347 const T* data() const {
-
348 return static_cast<T*>(array_desc_->data_ptr);
-
349 }
+
352 // Return a raw pointer to the arrays data
+
353 template <typename T>
+
+
354 T* data() {
+
355 return static_cast<T*>(array_desc_->data_ptr);
+
356 }
-
350
-
-
351 enum Status {
-
352 // The ouptut of a computation which has not been scheduled.
-
353 // For example, the status of `x` in `auto x = a + b`.
-
354 unscheduled,
-
355
-
356 // The ouptut of a computation which has been scheduled but `eval_*` has
-
357 // not yet been called on the array's primitive. A possible
-
358 // status of `x` in `auto x = a + b; eval(x);`
-
359 scheduled,
-
360
-
361 // The array's `eval_*` function has been run, but the computation is not
-
362 // necessarily complete. The array will have memory allocated and if it is
-
363 // not a tracer then it will be detached from the graph.
-
364 evaluated,
-
365
-
366 // If the array is the output of a computation then the computation
-
367 // is complete. Constant arrays are always available (e.g. `array({1, 2,
-
368 // 3})`)
-
369 available
-
370 };
+
357
+
358 template <typename T>
+
+
359 const T* data() const {
+
360 return static_cast<T*>(array_desc_->data_ptr);
+
361 }
-
371
-
372 // Check if the array is safe to read.
-
373 bool is_available() const;
-
374
-
375 // Wait on the array to be available. After this `is_available` returns
-
376 // `true`.
-
377 void wait();
-
378
-
-
379 Status status() const {
-
380 return array_desc_->status;
-
381 }
-
-
382
-
-
383 void set_status(Status s) const {
-
384 array_desc_->status = s;
-
385 }
+
362
+
+
363 enum Status {
+
364 // The ouptut of a computation which has not been scheduled.
+
365 // For example, the status of `x` in `auto x = a + b`.
+
366 unscheduled,
+
367
+
368 // The ouptut of a computation which has been scheduled but `eval_*` has
+
369 // not yet been called on the array's primitive. A possible
+
370 // status of `x` in `auto x = a + b; eval(x);`
+
371 scheduled,
+
372
+
373 // The array's `eval_*` function has been run, but the computation is not
+
374 // necessarily complete. The array will have memory allocated and if it is
+
375 // not a tracer then it will be detached from the graph.
+
376 evaluated,
+
377
+
378 // If the array is the output of a computation then the computation
+
379 // is complete. Constant arrays are always available (e.g. `array({1, 2,
+
380 // 3})`)
+
381 available
+
382 };
+
383
+
384 // Check if the array is safe to read.
+
385 bool is_available() const;
386
-
387 // Get the array's shared event
-
-
388 Event& event() const {
-
389 return array_desc_->event;
-
390 }
+
387 // Wait on the array to be available. After this `is_available` returns
+
388 // `true`.
+
389 void wait();
+
390
+
+
391 Status status() const {
+
392 return array_desc_->status;
+
393 }
-
391
-
392 // Attach an event to a not yet evaluated array
-
-
393 void attach_event(Event e) const {
-
394 array_desc_->event = std::move(e);
-
395 }
+
394
+
+
395 void set_status(Status s) const {
+
396 array_desc_->status = s;
+
397 }
-
396
-
397 // Mark the array as a tracer array (true) or not.
-
-
398 void set_tracer(bool is_tracer) {
-
399 array_desc_->is_tracer = is_tracer;
-
400 }
+
398
+
399 // Get the array's shared event
+
+
400 Event& event() const {
+
401 return array_desc_->event;
+
402 }
-
401 // Check if the array is a tracer array
-
402 bool is_tracer() const;
403
-
404 void set_data(allocator::Buffer buffer, Deleter d = allocator::free);
-
405
-
406 void set_data(
-
407 allocator::Buffer buffer,
-
408 size_t data_size,
-
409 Strides strides,
-
410 Flags flags,
-
411 Deleter d = allocator::free);
-
412
-
413 void copy_shared_buffer(
-
414 const array& other,
-
415 const Strides& strides,
-
416 Flags flags,
-
417 size_t data_size,
-
418 size_t offset = 0);
-
419
-
420 void copy_shared_buffer(const array& other);
-
421
-
422 void move_shared_buffer(
-
423 array other,
-
424 const Strides& strides,
-
425 Flags flags,
-
426 size_t data_size,
-
427 size_t offset = 0);
-
428
-
429 void move_shared_buffer(array other);
-
430
-
-
431 void overwrite_descriptor(const array& other) {
-
432 array_desc_ = other.array_desc_;
-
433 }
+
404 // Attach an event to a not yet evaluated array
+
+
405 void attach_event(Event e) const {
+
406 array_desc_->event = std::move(e);
+
407 }
-
434
-
435 ~array();
-
436
-
437 private:
-
438 // Initialize the arrays data
-
439 template <typename It>
-
440 void init(const It src);
-
441
-
442 struct ArrayDesc {
-
443 Shape shape;
-
444 Strides strides;
-
445 size_t size;
-
446 Dtype dtype;
-
447 std::shared_ptr<Primitive> primitive;
+
408
+
409 // Mark the array as a tracer array (true) or not.
+
+
410 void set_tracer(bool is_tracer) {
+
411 array_desc_->is_tracer = is_tracer;
+
412 }
+
+
413 // Check if the array is a tracer array
+
414 bool is_tracer() const;
+
415
+
416 void set_data(allocator::Buffer buffer, Deleter d = allocator::free);
+
417
+
418 void set_data(
+
419 allocator::Buffer buffer,
+
420 size_t data_size,
+
421 Strides strides,
+
422 Flags flags,
+
423 Deleter d = allocator::free);
+
424
+
425 void copy_shared_buffer(
+
426 const array& other,
+
427 const Strides& strides,
+
428 Flags flags,
+
429 size_t data_size,
+
430 size_t offset = 0);
+
431
+
432 void copy_shared_buffer(const array& other);
+
433
+
434 void move_shared_buffer(
+
435 array other,
+
436 const Strides& strides,
+
437 Flags flags,
+
438 size_t data_size,
+
439 size_t offset = 0);
+
440
+
441 void move_shared_buffer(array other);
+
442
+
+
443 void overwrite_descriptor(const array& other) {
+
444 array_desc_ = other.array_desc_;
+
445 }
+
+
446
+
447 ~array();
448
-
449 Status status;
-
450
-
451 // An event on the array used for synchronization
-
452 Event event;
+
449 private:
+
450 // Initialize the arrays data
+
451 template <typename It>
+
452 void init(const It src);
453
-
454 // Indicates an array is being used in a graph transform
-
455 // and should not be detached from the graph
-
456 bool is_tracer{false};
-
457
-
458 // This is a shared pointer so that *different* arrays
-
459 // can share the underlying data buffer.
-
460 std::shared_ptr<Data> data;
-
461
-
462 // Properly offset data pointer
-
463 void* data_ptr{nullptr};
-
464
-
465 // The size in elements of the data buffer the array accesses
-
466 size_t data_size;
-
467
-
468 // Contains useful meta data about the array
-
469 Flags flags;
-
470
-
471 std::vector<array> inputs;
-
472 // An array to keep track of the siblings from a multi-output
-
473 // primitive.
-
474 std::vector<array> siblings;
-
475 // The arrays position in the output list
-
476 uint32_t position{0};
-
477
-
478 explicit ArrayDesc(Shape shape, Dtype dtype);
+
454 struct ArrayDesc {
+
455 Shape shape;
+
456 Strides strides;
+
457 size_t size;
+
458 Dtype dtype;
+
459 std::shared_ptr<Primitive> primitive;
+
460
+
461 Status status;
+
462
+
463 // An event on the array used for synchronization
+
464 Event event;
+
465
+
466 // Indicates an array is being used in a graph transform
+
467 // and should not be detached from the graph
+
468 bool is_tracer{false};
+
469
+
470 // This is a shared pointer so that *different* arrays
+
471 // can share the underlying data buffer.
+
472 std::shared_ptr<Data> data;
+
473
+
474 // Properly offset data pointer
+
475 void* data_ptr{nullptr};
+
476
+
477 // The size in elements of the data buffer the array accesses
+
478 size_t data_size;
479
-
480 explicit ArrayDesc(
-
481 Shape shape,
-
482 Dtype dtype,
-
483 std::shared_ptr<Primitive> primitive,
-
484 std::vector<array> inputs);
-
485
-
486 ~ArrayDesc();
-
487
-
488 private:
-
489 // Initialize size, strides, and other metadata
-
490 void init();
-
491 };
-
492
-
493 // The ArrayDesc contains the details of the materialized array including the
-
494 // shape, strides, the data type. It also includes
-
495 // the primitive which knows how to compute the array's data from its inputs
-
496 // and the list of array's inputs for the primitive.
-
497 std::shared_ptr<ArrayDesc> array_desc_;
-
498};
-
+
480 // Contains useful meta data about the array
+
481 Flags flags;
+
482
+
483 std::vector<array> inputs;
+
484 // An array to keep track of the siblings from a multi-output
+
485 // primitive.
+
486 std::vector<array> siblings;
+
487 // The arrays position in the output list
+
488 uint32_t position{0};
+
489
+
490 explicit ArrayDesc(Shape shape, Dtype dtype);
+
491
+
492 explicit ArrayDesc(
+
493 Shape shape,
+
494 Dtype dtype,
+
495 std::shared_ptr<Primitive> primitive,
+
496 std::vector<array> inputs);
+
497
+
498 ~ArrayDesc();
499
-
500template <typename T>
-
-
501array::array(T val, Dtype dtype /* = TypeToDtype<T>() */)
-
502 : array_desc_(std::make_shared<ArrayDesc>(Shape{}, dtype)) {
-
503 init(&val);
-
504}
+
500 private:
+
501 // Initialize size, strides, and other metadata
+
502 void init();
+
503 };
+
504
+
505 // The ArrayDesc contains the details of the materialized array including the
+
506 // shape, strides, the data type. It also includes
+
507 // the primitive which knows how to compute the array's data from its inputs
+
508 // and the list of array's inputs for the primitive.
+
509 std::shared_ptr<ArrayDesc> array_desc_;
+
510};
-
505
-
506template <typename It>
-
-
507array::array(
-
508 It data,
-
509 Shape shape,
-
510 Dtype dtype /* = TypeToDtype<typename std::iterator_traits<It>::value_type>() */) :
-
511 array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
-
512 init(data);
-
513}
+
511
+
512template <typename T>
+
+
513array::array(T val, Dtype dtype /* = TypeToDtype<T>() */)
+
514 : array_desc_(std::make_shared<ArrayDesc>(Shape{}, dtype)) {
+
515 init(&val);
+
516}
-
514
-
515template <typename T>
-
-
516array::array(
-
517 std::initializer_list<T> data,
-
518 Dtype dtype /* = TypeToDtype<T>() */)
-
519 : array_desc_(std::make_shared<ArrayDesc>(
-
520 Shape{static_cast<ShapeElem>(data.size())},
-
521 dtype)) {
-
522 init(data.begin());
-
523}
+
517
+
518template <typename It>
+
+
519array::array(
+
520 It data,
+
521 Shape shape,
+
522 Dtype dtype /* = TypeToDtype<typename std::iterator_traits<It>::value_type>() */) :
+
523 array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
+
524 init(data);
+
525}
-
524
-
525template <typename T>
-
-
526array::array(
-
527 std::initializer_list<T> data,
-
528 Shape shape,
-
529 Dtype dtype /* = TypeToDtype<T>() */)
-
530 : array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
-
531 if (data.size() != size()) {
-
532 throw std::invalid_argument(
-
533 "Data size and provided shape mismatch in array construction.");
-
534 }
-
535 init(data.begin());
-
536}
+
526
+
527template <typename T>
+
+
528array::array(
+
529 std::initializer_list<T> data,
+
530 Dtype dtype /* = TypeToDtype<T>() */)
+
531 : array_desc_(std::make_shared<ArrayDesc>(
+
532 Shape{static_cast<ShapeElem>(data.size())},
+
533 dtype)) {
+
534 init(data.begin());
+
535}
-
537
-
538template <typename T>
-
-
539T array::item() {
-
540 if (size() != 1) {
-
541 throw std::invalid_argument("item can only be called on arrays of size 1.");
-
542 }
-
543 eval();
-
544 return *data<T>();
-
545}
+
536
+
537template <typename T>
+
+
538array::array(
+
539 std::initializer_list<T> data,
+
540 Shape shape,
+
541 Dtype dtype /* = TypeToDtype<T>() */)
+
542 : array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
+
543 if (data.size() != size()) {
+
544 throw std::invalid_argument(
+
545 "Data size and provided shape mismatch in array construction.");
+
546 }
+
547 init(data.begin());
+
548}
-
546
-
547template <typename T>
-
-
548T array::item() const {
-
549 if (size() != 1) {
-
550 throw std::invalid_argument("item can only be called on arrays of size 1.");
-
551 }
-
552 if (status() == Status::unscheduled) {
-
553 throw std::invalid_argument(
-
554 "item() const can only be called on evaled arrays");
-
555 }
-
556 const_cast<array*>(this)->eval();
-
557 return *data<T>();
-
558}
+
549
+
550template <typename T>
+
+
551T array::item() {
+
552 if (size() != 1) {
+
553 throw std::invalid_argument("item can only be called on arrays of size 1.");
+
554 }
+
555 eval();
+
556 return *data<T>();
+
557}
-
559
-
560template <typename It>
-
561void array::init(It src) {
-
562 set_data(allocator::malloc(size() * size_of(dtype())));
-
563 switch (dtype()) {
-
564 case bool_:
-
565 std::copy(src, src + size(), data<bool>());
-
566 break;
-
567 case uint8:
-
568 std::copy(src, src + size(), data<uint8_t>());
-
569 break;
-
570 case uint16:
-
571 std::copy(src, src + size(), data<uint16_t>());
-
572 break;
-
573 case uint32:
-
574 std::copy(src, src + size(), data<uint32_t>());
-
575 break;
-
576 case uint64:
-
577 std::copy(src, src + size(), data<uint64_t>());
+
558
+
559template <typename T>
+
+
560T array::item() const {
+
561 if (size() != 1) {
+
562 throw std::invalid_argument("item can only be called on arrays of size 1.");
+
563 }
+
564 if (status() == Status::unscheduled) {
+
565 throw std::invalid_argument(
+
566 "item() const can only be called on evaled arrays");
+
567 }
+
568 const_cast<array*>(this)->eval();
+
569 return *data<T>();
+
570}
+
+
571
+
572template <typename It>
+
573void array::init(It src) {
+
574 set_data(allocator::malloc(size() * size_of(dtype())));
+
575 switch (dtype()) {
+
576 case bool_:
+
577 std::copy(src, src + size(), data<bool>());
578 break;
-
579 case int8:
-
580 std::copy(src, src + size(), data<int8_t>());
+
579 case uint8:
+
580 std::copy(src, src + size(), data<uint8_t>());
581 break;
-
582 case int16:
-
583 std::copy(src, src + size(), data<int16_t>());
+
582 case uint16:
+
583 std::copy(src, src + size(), data<uint16_t>());
584 break;
-
585 case int32:
-
586 std::copy(src, src + size(), data<int32_t>());
+
585 case uint32:
+
586 std::copy(src, src + size(), data<uint32_t>());
587 break;
-
588 case int64:
-
589 std::copy(src, src + size(), data<int64_t>());
+
588 case uint64:
+
589 std::copy(src, src + size(), data<uint64_t>());
590 break;
-
591 case float16:
-
592 std::copy(src, src + size(), data<float16_t>());
+
591 case int8:
+
592 std::copy(src, src + size(), data<int8_t>());
593 break;
-
594 case float32:
-
595 std::copy(src, src + size(), data<float>());
+
594 case int16:
+
595 std::copy(src, src + size(), data<int16_t>());
596 break;
-
597 case bfloat16:
-
598 std::copy(src, src + size(), data<bfloat16_t>());
+
597 case int32:
+
598 std::copy(src, src + size(), data<int32_t>());
599 break;
-
600 case complex64:
-
601 std::copy(src, src + size(), data<complex64_t>());
+
600 case int64:
+
601 std::copy(src, src + size(), data<int64_t>());
602 break;
-
603 }
-
604}
-
605
-
606/* Utilities for determining whether a template parameter is array. */
-
607template <typename T>
-
608inline constexpr bool is_array_v =
-
609 std::is_same_v<std::remove_cv_t<std::remove_reference_t<T>>, array>;
-
610
-
611template <typename... T>
-
612inline constexpr bool is_arrays_v = (is_array_v<T> && ...);
-
613
-
614template <typename... T>
-
615using enable_for_arrays_t = typename std::enable_if_t<is_arrays_v<T...>>;
-
616
-
617} // namespace mlx::core
+
603 case float16:
+
604 std::copy(src, src + size(), data<float16_t>());
+
605 break;
+
606 case float32:
+
607 std::copy(src, src + size(), data<float>());
+
608 break;
+
609 case float64:
+
610 std::copy(src, src + size(), data<double>());
+
611 break;
+
612 case bfloat16:
+
613 std::copy(src, src + size(), data<bfloat16_t>());
+
614 break;
+
615 case complex64:
+
616 std::copy(src, src + size(), data<complex64_t>());
+
617 break;
+
618 }
+
619}
+
620
+
621/* Utilities for determining whether a template parameter is array. */
+
622template <typename T>
+
623inline constexpr bool is_array_v =
+
624 std::is_same_v<std::remove_cv_t<std::remove_reference_t<T>>, array>;
+
625
+
626template <typename... T>
+
627inline constexpr bool is_arrays_v = (is_array_v<T> && ...);
+
628
+
629template <typename... T>
+
630using enable_for_arrays_t = typename std::enable_if_t<is_arrays_v<T...>>;
+
631
+
632} // namespace mlx::core
mlx::core::Event
Definition event.h:11
mlx::core::Primitive
Definition primitives.h:48
mlx::core::allocator::Allocator::size
virtual size_t size(Buffer buffer) const =0
mlx::core::allocator::Buffer
Definition allocator.h:12
mlx::core::array
Definition array.h:24
-
mlx::core::array::attach_event
void attach_event(Event e) const
Definition array.h:393
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:306
-
mlx::core::array::event
Event & event() const
Definition array.h:388
-
mlx::core::array::Status
Status
Definition array.h:351
-
mlx::core::array::available
@ available
Definition array.h:369
-
mlx::core::array::evaluated
@ evaluated
Definition array.h:364
-
mlx::core::array::unscheduled
@ unscheduled
Definition array.h:354
-
mlx::core::array::scheduled
@ scheduled
Definition array.h:359
+
mlx::core::array::attach_event
void attach_event(Event e) const
Definition array.h:405
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
+
mlx::core::array::event
Event & event() const
Definition array.h:400
+
mlx::core::array::Status
Status
Definition array.h:363
+
mlx::core::array::available
@ available
Definition array.h:381
+
mlx::core::array::evaluated
@ evaluated
Definition array.h:376
+
mlx::core::array::unscheduled
@ unscheduled
Definition array.h:366
+
mlx::core::array::scheduled
@ scheduled
Definition array.h:371
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
+
mlx::core::array::array
array(allocator::Buffer data, Shape shape, Dtype dtype, Strides strides, size_t data_size, Flags flags, Deleter deleter=allocator::free)
Build an array from all the info held by the array description.
mlx::core::array::eval
void eval()
Evaluate the array.
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
-
mlx::core::array::inputs
const std::vector< array > & inputs() const
The array's inputs.
Definition array.h:262
+
mlx::core::array::inputs
const std::vector< array > & inputs() const
The array's inputs.
Definition array.h:274
mlx::core::array::array
array(const array &other)=default
-
mlx::core::array::outputs
std::vector< array > outputs() const
The outputs of the array's primitive (i.e.
Definition array.h:292
+
mlx::core::array::outputs
std::vector< array > outputs() const
The outputs of the array's primitive (i.e.
Definition array.h:304
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
mlx::core::array::move_shared_buffer
void move_shared_buffer(array other)
mlx::core::array::make_arrays
static std::vector< array > make_arrays(std::vector< Shape > shapes, const std::vector< Dtype > &dtypes, const std::shared_ptr< Primitive > &primitive, const std::vector< array > &inputs)
mlx::core::array::array
array(std::initializer_list< float > data)
-
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:271
+
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:283
mlx::core::array::array
array(allocator::Buffer data, Shape shape, Dtype dtype, Deleter deleter=allocator::free)
-
mlx::core::array::primitive_ptr
std::shared_ptr< Primitive > & primitive_ptr() const
A shared pointer to the array's primitive.
Definition array.h:252
+
mlx::core::array::primitive_ptr
std::shared_ptr< Primitive > & primitive_ptr() const
A shared pointer to the array's primitive.
Definition array.h:264
mlx::core::array::ndim
size_t ndim() const
The number of dimensions of the array.
Definition array.h:98
mlx::core::array::size
size_t size() const
The number of elements in the array.
Definition array.h:88
mlx::core::array::operator=
array & operator=(array &&other) &&=delete
@@ -817,45 +830,45 @@ $(function(){initNavTree('array_8h_source.html',''); initResizable(true); });
mlx::core::array::end
ArrayIterator end() const
Definition array.h:180
mlx::core::array::array
array(std::initializer_list< int > data, Dtype dtype)
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, size_t data_size, Strides strides, Flags flags, Deleter d=allocator::free)
-
mlx::core::array::buffer
const allocator::Buffer & buffer() const
Definition array.h:327
-
mlx::core::array::set_status
void set_status(Status s) const
Definition array.h:383
+
mlx::core::array::buffer
const allocator::Buffer & buffer() const
Definition array.h:339
+
mlx::core::array::set_status
void set_status(Status s) const
Definition array.h:395
mlx::core::array::array
array(const std::complex< float > &val, Dtype dtype=complex64)
-
mlx::core::array::status
Status status() const
Definition array.h:379
-
mlx::core::array::siblings
std::vector< array > & siblings()
The array's siblings.
Definition array.h:281
-
mlx::core::array::data
T * data()
Definition array.h:342
-
mlx::core::array::array
array(T val, Dtype dtype=TypeToDtype< T >())
Construct a scalar array with zero dimensions.
Definition array.h:501
+
mlx::core::array::status
Status status() const
Definition array.h:391
+
mlx::core::array::siblings
std::vector< array > & siblings()
The array's siblings.
Definition array.h:293
+
mlx::core::array::data
T * data()
Definition array.h:354
+
mlx::core::array::array
array(T val, Dtype dtype=TypeToDtype< T >())
Construct a scalar array with zero dimensions.
Definition array.h:513
mlx::core::array::begin
ArrayIterator begin() const
Definition array.h:177
-
mlx::core::array::primitive
Primitive & primitive() const
The array's primitive.
Definition array.h:247
+
mlx::core::array::primitive
Primitive & primitive() const
The array's primitive.
Definition array.h:259
mlx::core::array::detach
void detach()
Detach the array from the graph.
mlx::core::array::operator=
array & operator=(const array &other) &&=delete
Assignment to rvalue does not compile.
-
mlx::core::array::set_siblings
void set_siblings(std::vector< array > siblings, uint16_t position)
Definition array.h:285
-
mlx::core::array::item
T item()
Get the value from a scalar array.
Definition array.h:539
-
mlx::core::array::buffer_size
size_t buffer_size() const
Definition array.h:331
+
mlx::core::array::set_siblings
void set_siblings(std::vector< array > siblings, uint16_t position)
Definition array.h:297
+
mlx::core::array::item
T item()
Get the value from a scalar array.
Definition array.h:551
+
mlx::core::array::buffer_size
size_t buffer_size() const
Definition array.h:343
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other)
-
mlx::core::array::overwrite_descriptor
void overwrite_descriptor(const array &other)
Definition array.h:431
-
mlx::core::array::data
const T * data() const
Definition array.h:347
-
mlx::core::array::has_primitive
bool has_primitive() const
Check if the array has an attached primitive or is a leaf node.
Definition array.h:257
-
mlx::core::array::buffer
allocator::Buffer & buffer()
Definition array.h:324
+
mlx::core::array::overwrite_descriptor
void overwrite_descriptor(const array &other)
Definition array.h:443
+
mlx::core::array::data
const T * data() const
Definition array.h:359
+
mlx::core::array::has_primitive
bool has_primitive() const
Check if the array has an attached primitive or is a leaf node.
Definition array.h:269
+
mlx::core::array::buffer
allocator::Buffer & buffer()
Definition array.h:336
mlx::core::array::array
array(array &&other)=default
-
mlx::core::array::data_shared_ptr
std::shared_ptr< Data > data_shared_ptr() const
Definition array.h:337
+
mlx::core::array::data_shared_ptr
std::shared_ptr< Data > data_shared_ptr() const
Definition array.h:349
mlx::core::array::array
array(Shape shape, Dtype dtype, std::shared_ptr< Primitive > primitive, std::vector< array > inputs)
The following methods should be used with caution.
mlx::core::array::shape
auto shape(int dim) const
Get the size of the corresponding dimension.
Definition array.h:112
mlx::core::array::strides
auto strides(int dim) const
Get the stride of the corresponding dimension.
Definition array.h:126
-
mlx::core::array::siblings
const std::vector< array > & siblings() const
The array's siblings.
Definition array.h:276
-
mlx::core::array::inputs
std::vector< array > & inputs()
Definition array.h:266
+
mlx::core::array::siblings
const std::vector< array > & siblings() const
The array's siblings.
Definition array.h:288
+
mlx::core::array::inputs
std::vector< array > & inputs()
Definition array.h:278
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::operator=
array & operator=(array &&other) &=default
Default copy and move constructors otherwise.
mlx::core::array::move_shared_buffer
void move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::id
std::uintptr_t id() const
A unique identifier for an array.
Definition array.h:203
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
mlx::core::array::is_available
bool is_available() const
-
mlx::core::array::set_tracer
void set_tracer(bool is_tracer)
Definition array.h:398
+
mlx::core::array::set_tracer
void set_tracer(bool is_tracer)
Definition array.h:410
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
mlx::core::array::primitive_id
std::uintptr_t primitive_id() const
A unique identifier for an arrays primitive.
Definition array.h:208
mlx::core::array::is_tracer
bool is_tracer() const
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:320
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
mlx::core::std
array std(const array &a, bool keepdims, int ddof=0, StreamOrDevice s={})
Computes the standard deviation of the elements of an array.
@@ -863,29 +876,30 @@ $(function(){initNavTree('array_8h_source.html',''); initResizable(true); });
mlx::core::allocator::free
void free(Buffer buffer)
mlx::core::allocator::allocator
Allocator & allocator()
mlx::core
Definition allocator.h:7
-
mlx::core::is_array_v
constexpr bool is_array_v
Definition array.h:608
-
mlx::core::bool_
constexpr Dtype bool_
Definition dtype.h:67
+
mlx::core::is_array_v
constexpr bool is_array_v
Definition array.h:623
+
mlx::core::bool_
constexpr Dtype bool_
Definition dtype.h:68
mlx::core::ShapeElem
int32_t ShapeElem
Definition array.h:20
-
mlx::core::uint64
constexpr Dtype uint64
Definition dtype.h:72
-
mlx::core::uint16
constexpr Dtype uint16
Definition dtype.h:70
-
mlx::core::bfloat16
constexpr Dtype bfloat16
Definition dtype.h:81
-
mlx::core::int32
constexpr Dtype int32
Definition dtype.h:76
-
mlx::core::float32
constexpr Dtype float32
Definition dtype.h:80
+
mlx::core::uint64
constexpr Dtype uint64
Definition dtype.h:73
+
mlx::core::uint16
constexpr Dtype uint16
Definition dtype.h:71
+
mlx::core::float64
constexpr Dtype float64
Definition dtype.h:82
+
mlx::core::bfloat16
constexpr Dtype bfloat16
Definition dtype.h:83
+
mlx::core::int32
constexpr Dtype int32
Definition dtype.h:77
+
mlx::core::float32
constexpr Dtype float32
Definition dtype.h:81
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
-
mlx::core::int16
constexpr Dtype int16
Definition dtype.h:75
+
mlx::core::int16
constexpr Dtype int16
Definition dtype.h:76
mlx::core::Strides
std::vector< int64_t > Strides
Definition array.h:22
-
mlx::core::int8
constexpr Dtype int8
Definition dtype.h:74
-
mlx::core::int64
constexpr Dtype int64
Definition dtype.h:77
-
mlx::core::is_arrays_v
constexpr bool is_arrays_v
Definition array.h:612
-
mlx::core::uint8
constexpr Dtype uint8
Definition dtype.h:69
-
mlx::core::float16
constexpr Dtype float16
Definition dtype.h:79
-
mlx::core::uint32
constexpr Dtype uint32
Definition dtype.h:71
-
mlx::core::size_of
uint8_t size_of(const Dtype &t)
Definition dtype.h:102
+
mlx::core::int8
constexpr Dtype int8
Definition dtype.h:75
+
mlx::core::int64
constexpr Dtype int64
Definition dtype.h:78
+
mlx::core::is_arrays_v
constexpr bool is_arrays_v
Definition array.h:627
+
mlx::core::uint8
constexpr Dtype uint8
Definition dtype.h:70
+
mlx::core::float16
constexpr Dtype float16
Definition dtype.h:80
+
mlx::core::uint32
constexpr Dtype uint32
Definition dtype.h:72
+
mlx::core::size_of
uint8_t size_of(const Dtype &t)
Definition dtype.h:104
mlx::core::Deleter
std::function< void(allocator::Buffer)> Deleter
Definition array.h:19
-
mlx::core::enable_for_arrays_t
typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
Definition array.h:615
-
mlx::core::complex64
constexpr Dtype complex64
Definition dtype.h:82
+
mlx::core::enable_for_arrays_t
typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
Definition array.h:630
+
mlx::core::complex64
constexpr Dtype complex64
Definition dtype.h:84
mlx::core::Dtype
Definition dtype.h:13
-
mlx::core::TypeToDtype
Definition dtype.h:109
+
mlx::core::TypeToDtype
Definition dtype.h:111
mlx::core::array::ArrayIterator
Definition array.h:145
mlx::core::array::ArrayIterator::operator==
friend bool operator==(const ArrayIterator &a, const ArrayIterator &b)
Definition array.h:165
diff --git a/docs/build/html/backend_2common_2utils_8h_source.html b/docs/build/html/backend_2common_2utils_8h_source.html index 92db3c02d..f347cbbfb 100644 --- a/docs/build/html/backend_2common_2utils_8h_source.html +++ b/docs/build/html/backend_2common_2utils_8h_source.html @@ -310,12 +310,12 @@ $(function(){initNavTree('backend_2common_2utils_8h_source.html',''); initResiza
177} // namespace mlx::core
mlx::core::array
Definition array.h:24
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:306
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
-
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:271
-
mlx::core::array::buffer_size
size_t buffer_size() const
Definition array.h:331
+
mlx::core::array::is_donatable
bool is_donatable() const
True indicates the arrays buffer is safe to reuse.
Definition array.h:283
+
mlx::core::array::buffer_size
size_t buffer_size() const
Definition array.h:343
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
mlx::core
Definition allocator.h:7
mlx::core::make_contiguous_strides
Strides make_contiguous_strides(const Shape &shape)
Definition utils.h:29
@@ -328,7 +328,7 @@ $(function(){initNavTree('backend_2common_2utils_8h_source.html',''); initResiza
mlx::core::shared_buffer_reshape
void shared_buffer_reshape(const array &in, const Strides &out_strides, array &out)
mlx::core::check_contiguity
auto check_contiguity(const Shape &shape, const Strides &strides)
Definition utils.h:134
mlx::core::is_donatable
bool is_donatable(const array &in, const array &out)
Definition utils.h:155
-
mlx::core::enable_for_arrays_t
typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
Definition array.h:615
+
mlx::core::enable_for_arrays_t
typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
Definition array.h:630
mlx::core::ContiguousIterator::loc
int64_t loc
Definition utils.h:126
mlx::core::ContiguousIterator::ContiguousIterator
ContiguousIterator()
Definition utils.h:104
mlx::core::ContiguousIterator::ContiguousIterator
ContiguousIterator(const Shape &shape, const Strides &strides, int dims)
Definition utils.h:114
diff --git a/docs/build/html/backend_2metal_2device_8h_source.html b/docs/build/html/backend_2metal_2device_8h_source.html index c939ba18f..89269d2d8 100644 --- a/docs/build/html/backend_2metal_2device_8h_source.html +++ b/docs/build/html/backend_2metal_2device_8h_source.html @@ -147,303 +147,306 @@ $(function(){initNavTree('backend_2metal_2device_8h_source.html',''); initResiza
38using MTLFCList =
39 std::vector<std::tuple<const void*, MTL::DataType, NS::UInteger>>;
40
-
-
41struct CommandEncoder {
-
42 CommandEncoder(MTL::CommandBuffer* cbuf);
-
43 CommandEncoder(const CommandEncoder&) = delete;
-
44 CommandEncoder& operator=(const CommandEncoder&) = delete;
-
45
-
-
46 struct ConcurrentContext {
-
-
47 ConcurrentContext(CommandEncoder& enc) : enc(enc) {
-
48 enc.concurrent_ = true;
-
49 }
+
41struct DeviceStream;
+
42
+
+
43struct CommandEncoder {
+
44 explicit CommandEncoder(DeviceStream& stream);
+
45 CommandEncoder(const CommandEncoder&) = delete;
+
46 CommandEncoder& operator=(const CommandEncoder&) = delete;
+
47
+
+
48 struct ConcurrentContext {
+
+
49 ConcurrentContext(CommandEncoder& enc) : enc(enc) {
+
50 enc.concurrent_ = true;
+
51 }
-
-
50 ~ConcurrentContext() {
-
51 enc.concurrent_ = false;
-
52 enc.prev_outputs_.insert(
-
53 enc.concurrent_outputs_.begin(), enc.concurrent_outputs_.end());
-
54 enc.concurrent_outputs_.clear();
-
55 }
+
+
52 ~ConcurrentContext() {
+
53 enc.concurrent_ = false;
+
54 enc.prev_outputs_.insert(
+
55 enc.concurrent_outputs_.begin(), enc.concurrent_outputs_.end());
+
56 enc.concurrent_outputs_.clear();
+
57 }
-
56
-
57 private:
-
58 CommandEncoder& enc;
-
59 };
+
58
+
59 private:
+
60 CommandEncoder& enc;
+
61 };
-
60
-
61 void set_input_array(const array& a, int idx, int64_t offset = 0);
-
62 void set_output_array(array& a, int idx, int64_t offset = 0);
-
63 void register_output_array(array& a);
-
64 void dispatch_threadgroups(MTL::Size grid_dims, MTL::Size group_dims);
-
65 void dispatch_threads(MTL::Size grid_dims, MTL::Size group_dims);
-
66 void maybeInsertBarrier();
-
67 void set_buffer(const MTL::Buffer* buf, int idx, int64_t offset = 0);
-
68
-
-
69 void set_compute_pipeline_state(MTL::ComputePipelineState* kernel) {
-
70 enc_->setComputePipelineState(kernel);
-
71 }
+
62
+
63 void set_input_array(const array& a, int idx, int64_t offset = 0);
+
64 void set_output_array(array& a, int idx, int64_t offset = 0);
+
65 void register_output_array(array& a);
+
66 void dispatch_threadgroups(MTL::Size grid_dims, MTL::Size group_dims);
+
67 void dispatch_threads(MTL::Size grid_dims, MTL::Size group_dims);
+
68 void maybeInsertBarrier();
+
69 void set_buffer(const MTL::Buffer* buf, int idx, int64_t offset = 0);
+
70
+
+
71 void set_compute_pipeline_state(MTL::ComputePipelineState* kernel) {
+
72 enc_->setComputePipelineState(kernel);
+
73 }
-
72
-
-
73 void wait_for_fence(MTL::Fence* fence) {
-
74 enc_->waitForFence(fence);
-
75 }
+
74
+
+
75 void wait_for_fence(MTL::Fence* fence) {
+
76 enc_->waitForFence(fence);
+
77 }
-
76
-
-
77 void update_fence(MTL::Fence* fence) {
-
78 enc_->updateFence(fence);
-
79 }
+
78
+
+
79 void update_fence(MTL::Fence* fence) {
+
80 enc_->updateFence(fence);
+
81 }
-
80
-
81 template <typename T>
-
-
82 void set_vector_bytes(const std::vector<T>& vec, size_t nelems, int idx) {
-
83 enc_->setBytes(vec.data(), nelems * sizeof(T), idx);
-
84 }
+
82
+
83 template <typename T>
+
+
84 void set_vector_bytes(const std::vector<T>& vec, size_t nelems, int idx) {
+
85 enc_->setBytes(vec.data(), nelems * sizeof(T), idx);
+
86 }
-
85 template <typename T>
-
-
86 void set_vector_bytes(const std::vector<T>& vec, int idx) {
-
87 return set_vector_bytes(vec, vec.size(), idx);
-
88 }
+
87 template <typename T>
+
+
88 void set_vector_bytes(const std::vector<T>& vec, int idx) {
+
89 return set_vector_bytes(vec, vec.size(), idx);
+
90 }
-
89
-
90 template <typename T>
-
-
91 void set_bytes(const T* v, int n, int idx) {
-
92 return enc_->setBytes(v, n * sizeof(T), idx);
-
93 }
+
91
+
92 template <typename T>
+
+
93 void set_bytes(const T* v, int n, int idx) {
+
94 return enc_->setBytes(v, n * sizeof(T), idx);
+
95 }
-
94
-
95 template <typename T>
-
-
96 void set_bytes(const T& v, int idx) {
-
97 return enc_->setBytes(&v, sizeof(T), idx);
-
98 }
+
96
+
97 template <typename T>
+
+
98 void set_bytes(const T& v, int idx) {
+
99 return enc_->setBytes(&v, sizeof(T), idx);
+
100 }
-
99
-
-
100 ConcurrentContext start_concurrent() {
-
101 return ConcurrentContext(*this);
-
102 }
+
101
+
+
102 ConcurrentContext start_concurrent() {
+
103 return ConcurrentContext(*this);
+
104 }
-
103 ~CommandEncoder();
-
104
-
105 // Inputs to all kernels in the encoder including temporaries
-
-
106 std::unordered_set<const void*>& inputs() {
-
107 return all_inputs_;
-
108 };
+
105 ~CommandEncoder();
+
106
+
107 // Inputs to all kernels in the encoder including temporaries
+
+
108 std::unordered_set<const void*>& inputs() {
+
109 return all_inputs_;
+
110 };
-
109
-
110 // Outputs of all kernels in the encoder including temporaries
-
-
111 std::unordered_set<const void*> outputs() {
-
112 return all_outputs_;
-
113 };
+
111
+
112 // Outputs of all kernels in the encoder including temporaries
+
+
113 std::unordered_set<const void*> outputs() {
+
114 return all_outputs_;
+
115 };
-
114
-
115 void barrier();
116
-
117 private:
-
118 MTL::ComputeCommandEncoder* enc_;
-
119 bool needs_barrier_{false};
-
120 bool concurrent_{false};
-
121 std::unordered_set<MTL::Resource*> prev_outputs_;
-
122 std::unordered_set<MTL::Resource*> next_outputs_;
-
123 std::unordered_set<MTL::Resource*> concurrent_outputs_;
-
124 std::unordered_set<const void*> all_inputs_;
-
125 std::unordered_set<const void*> all_outputs_;
-
126};
+
117 void barrier();
+
118
+
119 private:
+
120 DeviceStream& stream_;
+
121 MTL::ComputeCommandEncoder* enc_;
+
122 bool needs_barrier_{false};
+
123 bool concurrent_{false};
+
124 std::unordered_set<MTL::Resource*> prev_outputs_;
+
125 std::unordered_set<MTL::Resource*> next_outputs_;
+
126 std::unordered_set<MTL::Resource*> concurrent_outputs_;
+
127 std::unordered_set<const void*> all_inputs_;
+
128 std::unordered_set<const void*> all_outputs_;
+
129};
-
127
-
-
128struct Fence {
-
129 Fence(MTL::Fence* fence) : fence(fence) {}
-
-
130 ~Fence() {
-
131 fence->release();
-
132 }
+
130
+
+
131struct Fence {
+
132 Fence(MTL::Fence* fence) : fence(fence) {}
+
+
133 ~Fence() {
+
134 fence->release();
+
135 }
-
133 MTL::Fence* fence;
-
134};
+
136 MTL::Fence* fence;
+
137};
-
135
-
-
136struct DeviceStream {
-
137 DeviceStream(MTL::CommandQueue* queue) : queue(queue) {};
-
-
138 ~DeviceStream() {
-
139 queue->release();
-
140 if (buffer != nullptr) {
-
141 buffer->release();
-
142 }
-
143 };
+
138
+
+
139struct DeviceStream {
+
140 DeviceStream(MTL::CommandQueue* queue) : queue(queue) {};
+
+
141 ~DeviceStream() {
+
142 queue->release();
+
143 if (buffer != nullptr) {
+
144 buffer->release();
+
145 }
+
146 };
-
144 MTL::CommandQueue* queue;
-
145 // A map of prior command encoder outputs to their corresponding fence
-
146 std::unordered_map<const void*, std::shared_ptr<Fence>> outputs;
-
147 // Used to allow thread-safe access to the outputs map
-
148 std::mutex fence_mtx;
-
149
-
150 // The buffer and buffer op count are updated
-
151 // between command buffers
-
152 MTL::CommandBuffer* buffer{nullptr};
-
153 int buffer_ops{0};
-
154
-
155 // The command encoder, fence, and temporaries are updated between command
-
156 // encoders
-
157 std::unique_ptr<CommandEncoder> encoder{nullptr};
-
158 std::shared_ptr<Fence> fence;
-
159 std::vector<array> temporaries;
-
160};
+
147 MTL::CommandQueue* queue;
+
148 // A map of prior command encoder outputs to their corresponding fence
+
149 std::unordered_map<const void*, std::shared_ptr<Fence>> outputs;
+
150 // Used to allow thread-safe access to the outputs map
+
151 std::mutex fence_mtx;
+
152
+
153 // Data updated between command buffers
+
154 MTL::CommandBuffer* buffer{nullptr};
+
155 int buffer_ops{0};
+
156 size_t buffer_sizes{0};
+
157
+
158 // The command encoder, fence, and temporaries are updated between command
+
159 // encoders
+
160 std::unique_ptr<CommandEncoder> encoder{nullptr};
+
161 std::shared_ptr<Fence> fence;
+
162 std::vector<array> temporaries;
+
163};
-
161
-
-
162class Device {
-
163 public:
-
164 Device();
-
165 Device(const Device&) = delete;
-
166 Device& operator=(const Device&) = delete;
-
167 ~Device();
-
168
-
-
169 MTL::Device* mtl_device() {
-
170 return device_;
-
171 };
+
164
+
+
165class Device {
+
166 public:
+
167 Device();
+
168 Device(const Device&) = delete;
+
169 Device& operator=(const Device&) = delete;
+
170 ~Device();
+
171
+
+
172 MTL::Device* mtl_device() {
+
173 return device_;
+
174 };
-
172
-
-
173 const std::string& get_architecture() {
-
174 return arch_;
-
175 }
+
175
+
+
176 const std::string& get_architecture() {
+
177 return arch_;
+
178 }
-
176
-
177 void new_queue(int index);
-
178 MTL::CommandBuffer* get_command_buffer(int index);
-
179 int get_command_buffer_ops(int index);
-
180 void increment_command_buffer_ops(int index);
-
181 void commit_command_buffer(int index);
-
182 CommandEncoder& get_command_encoder(int index);
-
183 void end_encoding(int index);
-
184
-
185 void register_library(
-
186 const std::string& lib_name,
-
187 const std::string& lib_path);
-
188
-
189 // Note, this should remain in the header so that it is not dynamically
-
190 // linked
-
-
191 void register_library(const std::string& lib_name) {
-
192 if (auto it = library_map_.find(lib_name); it == library_map_.end()) {
-
193 register_library(lib_name, get_colocated_mtllib_path(lib_name));
-
194 }
-
195 }
+
179
+
180 void new_queue(int index);
+
181 MTL::CommandBuffer* get_command_buffer(int index);
+
182 bool command_buffer_needs_commit(int index);
+
183 void commit_command_buffer(int index);
+
184 CommandEncoder& get_command_encoder(int index);
+
185 void end_encoding(int index);
+
186
+
187 void register_library(
+
188 const std::string& lib_name,
+
189 const std::string& lib_path);
+
190
+
191 // Note, this should remain in the header so that it is not dynamically
+
192 // linked
+
+
193 void register_library(const std::string& lib_name) {
+
194 if (auto it = library_map_.find(lib_name); it == library_map_.end()) {
+
195 register_library(lib_name, get_colocated_mtllib_path(lib_name));
+
196 }
+
197 }
-
196
-
197 MTL::Library* get_library(
-
198 const std::string& name,
-
199 const std::function<std::string(void)>& builder);
-
200
-
201 MTL::ComputePipelineState* get_kernel(
-
202 const std::string& base_name,
-
203 MTL::Library* mtl_lib,
-
204 const std::string& hash_name = "",
-
205 const MTLFCList& func_consts = {},
-
206 const std::vector<MTL::Function*>& linked_functions = {});
-
207
-
208 MTL::ComputePipelineState* get_kernel(
-
209 const std::string& base_name,
-
210 const std::string& lib_name = "mlx",
-
211 const std::string& hash_name = "",
-
212 const MTLFCList& func_consts = {},
-
213 const std::vector<MTL::Function*>& linked_functions = {});
-
214
-
215 MTL::ArgumentEncoder* argument_encoder(
-
216 const std::vector<MTL::ArgumentDescriptor*>& arg_descs) const;
-
217
-
218 // Record temporary arrays for the given stream index
-
219 void add_temporary(array arr, int index);
-
220 void add_temporaries(std::vector<array> arrays, int index);
-
221
-
222 void set_residency_set(const MTL::ResidencySet* residency_set);
+
198
+
199 MTL::Library* get_library(
+
200 const std::string& name,
+
201 const std::function<std::string(void)>& builder);
+
202
+
203 MTL::ComputePipelineState* get_kernel(
+
204 const std::string& base_name,
+
205 MTL::Library* mtl_lib,
+
206 const std::string& hash_name = "",
+
207 const MTLFCList& func_consts = {},
+
208 const std::vector<MTL::Function*>& linked_functions = {});
+
209
+
210 MTL::ComputePipelineState* get_kernel(
+
211 const std::string& base_name,
+
212 const std::string& lib_name = "mlx",
+
213 const std::string& hash_name = "",
+
214 const MTLFCList& func_consts = {},
+
215 const std::vector<MTL::Function*>& linked_functions = {});
+
216
+
217 MTL::ArgumentEncoder* argument_encoder(
+
218 const std::vector<MTL::ArgumentDescriptor*>& arg_descs) const;
+
219
+
220 // Record temporary arrays for the given stream index
+
221 void add_temporary(array arr, int index);
+
222 void add_temporaries(std::vector<array> arrays, int index);
223
-
224 private:
-
225 DeviceStream& get_stream_(int index) {
-
226 return stream_map_.find(index)->second;
-
227 }
-
228 MTL::Library* get_library_cache_(const std::string& name);
-
229
-
230 MTL::Library* get_library_(const std::string& name);
-
231 MTL::Library* build_library_(const std::string& source_string);
-
232
-
233 MTL::Function* get_function_(const std::string& name, MTL::Library* mtl_lib);
+
224 void set_residency_set(const MTL::ResidencySet* residency_set);
+
225
+
226 private:
+
227 DeviceStream& get_stream_(int index) {
+
228 return stream_map_.find(index)->second;
+
229 }
+
230 MTL::Library* get_library_cache_(const std::string& name);
+
231
+
232 MTL::Library* get_library_(const std::string& name);
+
233 MTL::Library* build_library_(const std::string& source_string);
234
-
235 MTL::Function* get_function_(
-
236 const std::string& name,
-
237 const std::string& specialized_name,
-
238 const MTLFCList& func_consts,
-
239 MTL::Library* mtl_lib);
-
240
-
241 MTL::LinkedFunctions* get_linked_functions_(
-
242 const std::vector<MTL::Function*>& funcs);
-
243
-
244 MTL::ComputePipelineState* get_kernel_(
-
245 const std::string& name,
-
246 const MTL::Function* mtl_function);
-
247
-
248 MTL::ComputePipelineState* get_kernel_(
-
249 const std::string& name,
-
250 const MTL::Function* mtl_function,
-
251 const MTL::LinkedFunctions* linked_functions);
-
252
-
253 MTL::ComputePipelineState* get_kernel_(
-
254 const std::string& base_name,
-
255 MTL::Library* mtl_lib,
-
256 const std::string& hash_name,
-
257 const MTLFCList& func_consts = {},
-
258 const std::vector<MTL::Function*>& linked_functions = {});
-
259
-
260 MTL::Device* device_;
-
261 std::unordered_map<int32_t, DeviceStream> stream_map_;
-
262
-
263 std::shared_mutex kernel_mtx_;
-
264 std::unordered_map<std::string, MTL::ComputePipelineState*> kernel_map_;
-
265
-
266 std::shared_mutex library_mtx_;
-
267 std::unordered_map<std::string, MTL::Library*> library_map_;
-
268 const MTL::ResidencySet* residency_set_{nullptr};
-
269 std::string arch_;
-
270};
+
235 MTL::Function* get_function_(const std::string& name, MTL::Library* mtl_lib);
+
236
+
237 MTL::Function* get_function_(
+
238 const std::string& name,
+
239 const std::string& specialized_name,
+
240 const MTLFCList& func_consts,
+
241 MTL::Library* mtl_lib);
+
242
+
243 MTL::LinkedFunctions* get_linked_functions_(
+
244 const std::vector<MTL::Function*>& funcs);
+
245
+
246 MTL::ComputePipelineState* get_kernel_(
+
247 const std::string& name,
+
248 const MTL::Function* mtl_function);
+
249
+
250 MTL::ComputePipelineState* get_kernel_(
+
251 const std::string& name,
+
252 const MTL::Function* mtl_function,
+
253 const MTL::LinkedFunctions* linked_functions);
+
254
+
255 MTL::ComputePipelineState* get_kernel_(
+
256 const std::string& base_name,
+
257 MTL::Library* mtl_lib,
+
258 const std::string& hash_name,
+
259 const MTLFCList& func_consts = {},
+
260 const std::vector<MTL::Function*>& linked_functions = {});
+
261
+
262 MTL::Device* device_;
+
263 std::unordered_map<int32_t, DeviceStream> stream_map_;
+
264
+
265 std::shared_mutex kernel_mtx_;
+
266 std::unordered_map<std::string, MTL::ComputePipelineState*> kernel_map_;
+
267
+
268 std::shared_mutex library_mtx_;
+
269 std::unordered_map<std::string, MTL::Library*> library_map_;
+
270 const MTL::ResidencySet* residency_set_{nullptr};
+
271 std::string arch_;
+
272 int max_ops_per_buffer_;
+
273 int max_mb_per_buffer_;
+
274};
-
271
-
272Device& device(mlx::core::Device);
-
273
-
274} // namespace mlx::core::metal
+
275
+
276Device& device(mlx::core::Device);
+
277
+
278} // namespace mlx::core::metal
mlx::core::array
Definition array.h:24
-
mlx::core::metal::Device
Definition device.h:162
+
mlx::core::metal::Device
Definition device.h:165
mlx::core::metal::Device::set_residency_set
void set_residency_set(const MTL::ResidencySet *residency_set)
-
mlx::core::metal::Device::get_command_buffer_ops
int get_command_buffer_ops(int index)
-
mlx::core::metal::Device::mtl_device
MTL::Device * mtl_device()
Definition device.h:169
+
mlx::core::metal::Device::command_buffer_needs_commit
bool command_buffer_needs_commit(int index)
+
mlx::core::metal::Device::mtl_device
MTL::Device * mtl_device()
Definition device.h:172
mlx::core::metal::Device::register_library
void register_library(const std::string &lib_name, const std::string &lib_path)
mlx::core::metal::Device::get_command_buffer
MTL::CommandBuffer * get_command_buffer(int index)
mlx::core::metal::Device::end_encoding
void end_encoding(int index)
-
mlx::core::metal::Device::get_architecture
const std::string & get_architecture()
Definition device.h:173
+
mlx::core::metal::Device::get_architecture
const std::string & get_architecture()
Definition device.h:176
mlx::core::metal::Device::get_kernel
MTL::ComputePipelineState * get_kernel(const std::string &base_name, MTL::Library *mtl_lib, const std::string &hash_name="", const MTLFCList &func_consts={}, const std::vector< MTL::Function * > &linked_functions={})
mlx::core::metal::Device::argument_encoder
MTL::ArgumentEncoder * argument_encoder(const std::vector< MTL::ArgumentDescriptor * > &arg_descs) const
mlx::core::metal::Device::add_temporaries
void add_temporaries(std::vector< array > arrays, int index)
mlx::core::metal::Device::get_library
MTL::Library * get_library(const std::string &name, const std::function< std::string(void)> &builder)
-
mlx::core::metal::Device::increment_command_buffer_ops
void increment_command_buffer_ops(int index)
mlx::core::metal::Device::new_queue
void new_queue(int index)
mlx::core::metal::Device::commit_command_buffer
void commit_command_buffer(int index)
-
mlx::core::metal::Device::register_library
void register_library(const std::string &lib_name)
Definition device.h:191
+
mlx::core::metal::Device::register_library
void register_library(const std::string &lib_name)
Definition device.h:193
mlx::core::metal::Device::Device
Device(const Device &)=delete
mlx::core::metal::Device::add_temporary
void add_temporary(array arr, int index)
mlx::core::metal::Device::operator=
Device & operator=(const Device &)=delete
@@ -455,49 +458,50 @@ $(function(){initNavTree('backend_2metal_2device_8h_source.html',''); initResiza
mlx::core::metal::get_colocated_mtllib_path
std::string get_colocated_mtllib_path(const std::string &lib_name)
Definition device.h:24
mlx::core::metal::MTLFCList
std::vector< std::tuple< const void *, MTL::DataType, NS::UInteger > > MTLFCList
Definition device.h:38
mlx::core::metal::device
Device & device(mlx::core::Device)
-
mlx::core::CommandEncoder::ConcurrentContext::ConcurrentContext
ConcurrentContext(CommandEncoder &enc)
Definition device.h:47
-
mlx::core::CommandEncoder::CommandEncoder
CommandEncoder(MTL::CommandBuffer *cbuf)
+
mlx::core::CommandEncoder::ConcurrentContext::ConcurrentContext
ConcurrentContext(CommandEncoder &enc)
Definition device.h:49
+
mlx::core::CommandEncoder::CommandEncoder
CommandEncoder(DeviceStream &stream)
mlx::core::Device
Definition device.h:7
- - -
mlx::core::metal::CommandEncoder::ConcurrentContext::ConcurrentContext
ConcurrentContext(CommandEncoder &enc)
Definition device.h:47
-
mlx::core::metal::CommandEncoder
Definition device.h:41
+ + +
mlx::core::metal::CommandEncoder::ConcurrentContext::ConcurrentContext
ConcurrentContext(CommandEncoder &enc)
Definition device.h:49
+
mlx::core::metal::CommandEncoder
Definition device.h:43
mlx::core::metal::CommandEncoder::dispatch_threads
void dispatch_threads(MTL::Size grid_dims, MTL::Size group_dims)
-
mlx::core::metal::CommandEncoder::CommandEncoder
CommandEncoder(MTL::CommandBuffer *cbuf)
-
mlx::core::metal::CommandEncoder::inputs
std::unordered_set< const void * > & inputs()
Definition device.h:106
+
mlx::core::metal::CommandEncoder::inputs
std::unordered_set< const void * > & inputs()
Definition device.h:108
mlx::core::metal::CommandEncoder::operator=
CommandEncoder & operator=(const CommandEncoder &)=delete
-
mlx::core::metal::CommandEncoder::start_concurrent
ConcurrentContext start_concurrent()
Definition device.h:100
-
mlx::core::metal::CommandEncoder::set_vector_bytes
void set_vector_bytes(const std::vector< T > &vec, size_t nelems, int idx)
Definition device.h:82
+
mlx::core::metal::CommandEncoder::start_concurrent
ConcurrentContext start_concurrent()
Definition device.h:102
+
mlx::core::metal::CommandEncoder::set_vector_bytes
void set_vector_bytes(const std::vector< T > &vec, size_t nelems, int idx)
Definition device.h:84
mlx::core::metal::CommandEncoder::set_output_array
void set_output_array(array &a, int idx, int64_t offset=0)
-
mlx::core::metal::CommandEncoder::set_compute_pipeline_state
void set_compute_pipeline_state(MTL::ComputePipelineState *kernel)
Definition device.h:69
-
mlx::core::metal::CommandEncoder::set_vector_bytes
void set_vector_bytes(const std::vector< T > &vec, int idx)
Definition device.h:86
+
mlx::core::metal::CommandEncoder::set_compute_pipeline_state
void set_compute_pipeline_state(MTL::ComputePipelineState *kernel)
Definition device.h:71
+
mlx::core::metal::CommandEncoder::CommandEncoder
CommandEncoder(DeviceStream &stream)
+
mlx::core::metal::CommandEncoder::set_vector_bytes
void set_vector_bytes(const std::vector< T > &vec, int idx)
Definition device.h:88
mlx::core::metal::CommandEncoder::dispatch_threadgroups
void dispatch_threadgroups(MTL::Size grid_dims, MTL::Size group_dims)
-
mlx::core::metal::CommandEncoder::set_bytes
void set_bytes(const T *v, int n, int idx)
Definition device.h:91
+
mlx::core::metal::CommandEncoder::set_bytes
void set_bytes(const T *v, int n, int idx)
Definition device.h:93
mlx::core::metal::CommandEncoder::set_input_array
void set_input_array(const array &a, int idx, int64_t offset=0)
-
mlx::core::metal::CommandEncoder::set_bytes
void set_bytes(const T &v, int idx)
Definition device.h:96
+
mlx::core::metal::CommandEncoder::set_bytes
void set_bytes(const T &v, int idx)
Definition device.h:98
mlx::core::metal::CommandEncoder::CommandEncoder
CommandEncoder(const CommandEncoder &)=delete
mlx::core::metal::CommandEncoder::set_buffer
void set_buffer(const MTL::Buffer *buf, int idx, int64_t offset=0)
-
mlx::core::metal::CommandEncoder::update_fence
void update_fence(MTL::Fence *fence)
Definition device.h:77
-
mlx::core::metal::CommandEncoder::outputs
std::unordered_set< const void * > outputs()
Definition device.h:111
-
mlx::core::metal::CommandEncoder::wait_for_fence
void wait_for_fence(MTL::Fence *fence)
Definition device.h:73
-
mlx::core::metal::DeviceStream
Definition device.h:136
-
mlx::core::metal::DeviceStream::~DeviceStream
~DeviceStream()
Definition device.h:138
-
mlx::core::metal::DeviceStream::outputs
std::unordered_map< const void *, std::shared_ptr< Fence > > outputs
Definition device.h:146
-
mlx::core::metal::DeviceStream::DeviceStream
DeviceStream(MTL::CommandQueue *queue)
Definition device.h:137
-
mlx::core::metal::DeviceStream::encoder
std::unique_ptr< CommandEncoder > encoder
Definition device.h:157
-
mlx::core::metal::DeviceStream::fence_mtx
std::mutex fence_mtx
Definition device.h:148
-
mlx::core::metal::DeviceStream::queue
MTL::CommandQueue * queue
Definition device.h:144
-
mlx::core::metal::DeviceStream::fence
std::shared_ptr< Fence > fence
Definition device.h:158
-
mlx::core::metal::DeviceStream::buffer
MTL::CommandBuffer * buffer
Definition device.h:152
-
mlx::core::metal::DeviceStream::buffer_ops
int buffer_ops
Definition device.h:153
-
mlx::core::metal::DeviceStream::temporaries
std::vector< array > temporaries
Definition device.h:159
-
mlx::core::metal::Fence::Fence
Fence(MTL::Fence *fence)
Definition device.h:129
-
mlx::core::metal::Fence::~Fence
~Fence()
Definition device.h:130
-
mlx::core::metal::Fence::fence
MTL::Fence * fence
Definition device.h:133
+
mlx::core::metal::CommandEncoder::update_fence
void update_fence(MTL::Fence *fence)
Definition device.h:79
+
mlx::core::metal::CommandEncoder::outputs
std::unordered_set< const void * > outputs()
Definition device.h:113
+
mlx::core::metal::CommandEncoder::wait_for_fence
void wait_for_fence(MTL::Fence *fence)
Definition device.h:75
+
mlx::core::metal::DeviceStream
Definition device.h:139
+
mlx::core::metal::DeviceStream::~DeviceStream
~DeviceStream()
Definition device.h:141
+
mlx::core::metal::DeviceStream::outputs
std::unordered_map< const void *, std::shared_ptr< Fence > > outputs
Definition device.h:149
+
mlx::core::metal::DeviceStream::DeviceStream
DeviceStream(MTL::CommandQueue *queue)
Definition device.h:140
+
mlx::core::metal::DeviceStream::encoder
std::unique_ptr< CommandEncoder > encoder
Definition device.h:160
+
mlx::core::metal::DeviceStream::fence_mtx
std::mutex fence_mtx
Definition device.h:151
+
mlx::core::metal::DeviceStream::queue
MTL::CommandQueue * queue
Definition device.h:147
+
mlx::core::metal::DeviceStream::fence
std::shared_ptr< Fence > fence
Definition device.h:161
+
mlx::core::metal::DeviceStream::buffer
MTL::CommandBuffer * buffer
Definition device.h:154
+
mlx::core::metal::DeviceStream::buffer_ops
int buffer_ops
Definition device.h:155
+
mlx::core::metal::DeviceStream::buffer_sizes
size_t buffer_sizes
Definition device.h:156
+
mlx::core::metal::DeviceStream::temporaries
std::vector< array > temporaries
Definition device.h:162
+
mlx::core::metal::Fence::Fence
Fence(MTL::Fence *fence)
Definition device.h:132
+
mlx::core::metal::Fence::~Fence
~Fence()
Definition device.h:133
+
mlx::core::metal::Fence::fence
MTL::Fence * fence
Definition device.h:136
diff --git a/docs/build/html/backend_2metal_2kernels_2fft_8h_source.html b/docs/build/html/backend_2metal_2kernels_2fft_8h_source.html index ce26c442a..ee4ea00c9 100644 --- a/docs/build/html/backend_2metal_2kernels_2fft_8h_source.html +++ b/docs/build/html/backend_2metal_2kernels_2fft_8h_source.html @@ -643,7 +643,7 @@ $(function(){initNavTree('backend_2metal_2kernels_2fft_8h_source.html',''); init
radix_func
METAL_FUNC void radix_func(thread float *x)
Definition hadamard.h:11
metal
Definition bf16_math.h:226
metal::min
METAL_FUNC bfloat16_t min(bfloat16_t x, bfloat16_t y)
Definition bf16_math.h:232
-
mlx::core::simd::real
auto real(Simd< T, 1 > in) -> Simd< decltype(std::real(in.value)), 1 >
Definition base_simd.h:98
+
mlx::core::simd::real
auto real(Simd< T, 1 > in) -> Simd< decltype(std::real(in.value)), 1 >
Definition base_simd.h:104
radix5
METAL_FUNC void radix5(thread float2 *x, thread float2 *y)
Definition radix.h:69
radix4
METAL_FUNC void radix4(thread float2 *x, thread float2 *y)
Definition radix.h:56
diff --git a/docs/build/html/backend_2metal_2utils_8h.html b/docs/build/html/backend_2metal_2utils_8h.html index 200f869bc..ac6674994 100644 --- a/docs/build/html/backend_2metal_2utils_8h.html +++ b/docs/build/html/backend_2metal_2utils_8h.html @@ -147,6 +147,9 @@ Functions template<typename T, typename... Args> void mlx::core::concatenate (std::string &acc, T first, Args... args)   +array mlx::core::unsafe_weak_copy (const array &x) + Get a new array that refers to the same data but has a non-owning pointer to them.
+ 
diff --git a/docs/build/html/backend_2metal_2utils_8h.js b/docs/build/html/backend_2metal_2utils_8h.js index b67a9d3f9..bc0d55b36 100644 --- a/docs/build/html/backend_2metal_2utils_8h.js +++ b/docs/build/html/backend_2metal_2utils_8h.js @@ -10,5 +10,6 @@ var backend_2metal_2utils_8h = [ "mlx::core::get_primitive_string", "namespacemlx_1_1core.html#ad4be35b310a252edd80d9cf04f094a60", null ], [ "mlx::core::make_string", "namespacemlx_1_1core.html#aed148d95e7b5221f1312473deded0d27", null ], [ "mlx::core::type_to_name", "namespacemlx_1_1core.html#af1fdfdaa5644394362e6baba30701bae", null ], - [ "mlx::core::type_to_name", "namespacemlx_1_1core.html#aef60e3a8d9c987c9c338b193673d2164", null ] + [ "mlx::core::type_to_name", "namespacemlx_1_1core.html#aef60e3a8d9c987c9c338b193673d2164", null ], + [ "mlx::core::unsafe_weak_copy", "namespacemlx_1_1core.html#a357f4172305d2021bde8cf07d99adb7d", null ] ]; \ No newline at end of file diff --git a/docs/build/html/backend_2metal_2utils_8h_source.html b/docs/build/html/backend_2metal_2utils_8h_source.html index 2567c0a28..8b09f8ba0 100644 --- a/docs/build/html/backend_2metal_2utils_8h_source.html +++ b/docs/build/html/backend_2metal_2utils_8h_source.html @@ -185,15 +185,35 @@ $(function(){initNavTree('backend_2metal_2utils_8h_source.html',''); initResizab
69 concatenate(acc, args...);
70}
-
71
-
72} // namespace mlx::core
+
71
+
+
76inline array unsafe_weak_copy(const array& x) {
+
77 return array(
+
78 x.buffer(),
+
79 x.shape(),
+
80 x.dtype(),
+
81 x.strides(),
+
82 x.data_size(),
+
83 x.flags(),
+
84 [](auto b) {});
+
85}
+
+
86
+
87} // namespace mlx::core
mlx::core::Primitive
Definition primitives.h:48
mlx::core::Primitive::print
virtual void print(std::ostream &os)=0
Print the primitive.
mlx::core::array
Definition array.h:24
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
+
mlx::core::array::shape
const Shape & shape() const
The shape of the array as a vector of integers.
Definition array.h:103
+
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
+
mlx::core::array::buffer
allocator::Buffer & buffer()
Definition array.h:336
+
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
mlx::core
Definition allocator.h:7
mlx::core::get_block_dims
MTL::Size get_block_dims(int dim0, int dim1, int dim2, int pow2=10)
+
mlx::core::unsafe_weak_copy
array unsafe_weak_copy(const array &x)
Get a new array that refers to the same data but has a non-owning pointer to them.
Definition utils.h:76
mlx::core::debug_set_primitive_buffer_label
void debug_set_primitive_buffer_label(MTL::CommandBuffer *command_buffer, Primitive &primitive)
Definition utils.h:46
mlx::core::Shape
std::vector< ShapeElem > Shape
Definition array.h:21
mlx::core::concatenate
void concatenate(std::string &acc, T first)
Definition utils.h:62
diff --git a/docs/build/html/base__simd_8h.html b/docs/build/html/base__simd_8h.html index db86e42bf..6728d3cc2 100644 --- a/docs/build/html/base__simd_8h.html +++ b/docs/build/html/base__simd_8h.html @@ -115,6 +115,7 @@ $(function(){initNavTree('base__simd_8h.html',''); initResizable(true); }); #include <algorithm>
#include <cmath>
#include <complex>
+#include <functional>

Go to the source code of this file.

@@ -226,6 +227,9 @@ Functions + + + diff --git a/docs/build/html/base__simd_8h.js b/docs/build/html/base__simd_8h.js index b68085333..bd59bdc38 100644 --- a/docs/build/html/base__simd_8h.js +++ b/docs/build/html/base__simd_8h.js @@ -86,6 +86,7 @@ var base__simd_8h = [ "mlx::core::simd::operator||", "namespacemlx_1_1core_1_1simd.html#a7a1c3be1c37d41e450469f2e98cd9dde", null ], [ "mlx::core::simd::operator||", "namespacemlx_1_1core_1_1simd.html#aad2d440fbb9e5478b5ed24400a859942", null ], [ "mlx::core::simd::operator||", "namespacemlx_1_1core_1_1simd.html#a0c8bd67982681ecd53cd8d739be3a5a9", null ], + [ "mlx::core::simd::operator~", "namespacemlx_1_1core_1_1simd.html#a4c6ed06d523db05f99df7ef21b374c41", null ], [ "mlx::core::simd::pow", "namespacemlx_1_1core_1_1simd.html#afe3d50bc4a11061898aa57377fa9536d", null ], [ "mlx::core::simd::prod", "namespacemlx_1_1core_1_1simd.html#ac27cdc630e86b25ad607ca409de2b274", null ], [ "mlx::core::simd::real", "namespacemlx_1_1core_1_1simd.html#acdf822b7626bbab6a495552aea3457b5", null ], diff --git a/docs/build/html/base__simd_8h_source.html b/docs/build/html/base__simd_8h_source.html index 450652fc7..33e3a3dea 100644 --- a/docs/build/html/base__simd_8h_source.html +++ b/docs/build/html/base__simd_8h_source.html @@ -111,356 +111,364 @@ $(function(){initNavTree('base__simd_8h_source.html',''); initResizable(true); }
4#include <algorithm>
5#include <cmath>
6#include <complex>
-
7
-
8namespace mlx::core::simd {
-
9template <typename T, int N>
-
10struct Simd;
-
11
-
12template <typename T>
-
13static constexpr int max_size = 1;
-
14
-
15template <typename T>
-
-
16struct Simd<T, 1> {
-
17 static constexpr int size = 1;
-
18 T value;
-
19 Simd() {}
-
20 template <typename U>
-
21 Simd(Simd<U, 1> v) : value(v.value) {}
-
22 template <typename U>
-
23 Simd(U v) : value(v) {}
-
24};
+
7#include <functional>
+
8
+
9namespace mlx::core::simd {
+
10template <typename T, int N>
+
11struct Simd;
+
12
+
13template <typename T>
+
14static constexpr int max_size = 1;
+
15
+
16template <typename T>
+
+
17struct Simd<T, 1> {
+
18 static constexpr int size = 1;
+
19 T value;
+
20 Simd() {}
+
21 template <typename U>
+
22 Simd(Simd<U, 1> v) : value(v.value) {}
+
23 template <typename U>
+
24 Simd(U v) : value(v) {}
+
25};
-
25
-
26template <typename T, int N>
-
-
27Simd<T, N> load(const T* x) {
-
28 return *(Simd<T, N>*)x;
-
29}
+
26
+
27template <typename T, int N>
+
+
28Simd<T, N> load(const T* x) {
+
29 return *(Simd<T, N>*)x;
+
30}
-
30
-
31template <typename T, int N>
-
-
32void store(T* dst, Simd<T, N> x) {
-
33 // Maintain invariant that bool is either 0 or 1 as
-
34 // simd comparison ops set all bits in the result to 1
-
35 if constexpr (std::is_same_v<T, bool> && N > 1) {
-
36 x = x & 1;
-
37 }
-
38 *(Simd<T, N>*)dst = x;
-
39}
+
31
+
32template <typename T, int N>
+
+
33void store(T* dst, Simd<T, N> x) {
+
34 // Maintain invariant that bool is either 0 or 1 as
+
35 // simd comparison ops set all bits in the result to 1
+
36 if constexpr (std::is_same_v<T, bool> && N > 1) {
+
37 x = x & 1;
+
38 }
+
39 *(Simd<T, N>*)dst = x;
+
40}
-
40
-
41template <typename, typename = void>
-
42constexpr bool is_complex = false;
-
43
-
44template <typename T>
-
45constexpr bool is_complex<T, std::void_t<decltype(std::declval<T>().real())>> =
-
46 true;
-
47
-
48template <typename T>
-
-
49Simd<T, 1> rint(Simd<T, 1> in) {
-
50 if constexpr (is_complex<T>) {
-
51 return Simd<T, 1>{
-
52 T{std::rint(in.value.real()), std::rint(in.value.imag())}};
-
53 } else {
-
54 return Simd<T, 1>{std::rint(in.value)};
-
55 }
-
56}
+
41
+
42template <typename, typename = void>
+
43constexpr bool is_complex = false;
+
44
+
45template <typename T>
+
46constexpr bool is_complex<T, std::void_t<decltype(std::declval<T>().real())>> =
+
47 true;
+
48
+
49template <typename T>
+
+
50Simd<T, 1> rint(Simd<T, 1> in) {
+
51 if constexpr (is_complex<T>) {
+
52 return Simd<T, 1>{
+
53 T{std::rint(in.value.real()), std::rint(in.value.imag())}};
+
54 } else {
+
55 return Simd<T, 1>{std::rint(in.value)};
+
56 }
+
57}
-
57
-
58template <typename T>
-
-
59Simd<T, 1> rsqrt(Simd<T, 1> in) {
-
60 return T(1.0) / sqrt(in);
-
61}
+
58
+
59template <typename T>
+
+
60Simd<T, 1> rsqrt(Simd<T, 1> in) {
+
61 return T(1.0) / sqrt(in);
+
62}
-
62
-
63template <typename T>
-
-
64Simd<T, 1> recip(Simd<T, 1> in) {
-
65 return T(1.0) / in;
-
66}
+
63
+
64template <typename T>
+
+
65Simd<T, 1> recip(Simd<T, 1> in) {
+
66 return T(1.0) / in;
+
67}
-
67
-
-
68#define DEFAULT_UNARY(name, op) \
-
69 template <typename T> \
-
70 Simd<T, 1> name(Simd<T, 1> in) { \
-
71 return op(in.value); \
-
72 }
+
68
+
+
69#define DEFAULT_UNARY(name, op) \
+
70 template <typename T> \
+
71 Simd<T, 1> name(Simd<T, 1> in) { \
+
72 return op(in.value); \
+
73 }
-
73
-
74DEFAULT_UNARY(operator-, std::negate{})
-
75DEFAULT_UNARY(operator!, std::logical_not{})
-
76DEFAULT_UNARY(abs, std::abs)
-
77DEFAULT_UNARY(acos, std::acos)
-
78DEFAULT_UNARY(acosh, std::acosh)
-
79DEFAULT_UNARY(asin, std::asin)
-
80DEFAULT_UNARY(asinh, std::asinh)
-
81DEFAULT_UNARY(atan, std::atan)
-
82DEFAULT_UNARY(atanh, std::atanh)
-
83DEFAULT_UNARY(ceil, std::ceil)
-
84DEFAULT_UNARY(conj, std::conj)
-
85DEFAULT_UNARY(cosh, std::cosh)
-
86DEFAULT_UNARY(expm1, std::expm1)
-
87DEFAULT_UNARY(floor, std::floor)
-
88DEFAULT_UNARY(log, std::log)
-
89DEFAULT_UNARY(log2, std::log2)
-
90DEFAULT_UNARY(log10, std::log10)
-
91DEFAULT_UNARY(log1p, std::log1p)
-
92DEFAULT_UNARY(sinh, std::sinh)
-
93DEFAULT_UNARY(sqrt, std::sqrt)
-
94DEFAULT_UNARY(tan, std::tan)
-
95DEFAULT_UNARY(tanh, std::tanh)
-
96
-
97template <typename T>
-
-
98auto real(Simd<T, 1> in) -> Simd<decltype(std::real(in.value)), 1> {
-
99 return std::real(in.value);
-
100}
+
74
+
75DEFAULT_UNARY(operator-, std::negate{})
+
76DEFAULT_UNARY(operator!, std::logical_not{})
+
77DEFAULT_UNARY(abs, std::abs)
+
78DEFAULT_UNARY(acos, std::acos)
+
79DEFAULT_UNARY(acosh, std::acosh)
+
80DEFAULT_UNARY(asin, std::asin)
+
81DEFAULT_UNARY(asinh, std::asinh)
+
82DEFAULT_UNARY(atan, std::atan)
+
83DEFAULT_UNARY(atanh, std::atanh)
+
84DEFAULT_UNARY(ceil, std::ceil)
+
85DEFAULT_UNARY(conj, std::conj)
+
86DEFAULT_UNARY(cosh, std::cosh)
+
87DEFAULT_UNARY(expm1, std::expm1)
+
88DEFAULT_UNARY(floor, std::floor)
+
89DEFAULT_UNARY(log, std::log)
+
90DEFAULT_UNARY(log2, std::log2)
+
91DEFAULT_UNARY(log10, std::log10)
+
92DEFAULT_UNARY(log1p, std::log1p)
+
93DEFAULT_UNARY(sinh, std::sinh)
+
94DEFAULT_UNARY(sqrt, std::sqrt)
+
95DEFAULT_UNARY(tan, std::tan)
+
96DEFAULT_UNARY(tanh, std::tanh)
+
97
+
98template <typename T>
+
+
99Simd<T, 1> operator~(Simd<T, 1> in) {
+
100 return ~in.value;
+
101}
-
101template <typename T>
-
-
102auto imag(Simd<T, 1> in) -> Simd<decltype(std::imag(in.value)), 1> {
-
103 return std::imag(in.value);
-
104}
+
102
+
103template <typename T>
+
+
104auto real(Simd<T, 1> in) -> Simd<decltype(std::real(in.value)), 1> {
+
105 return std::real(in.value);
+
106}
-
105template <typename T>
-
-
106Simd<bool, 1> isnan(Simd<T, 1> in) {
-
107 return std::isnan(in.value);
-
108}
+
107template <typename T>
+
+
108auto imag(Simd<T, 1> in) -> Simd<decltype(std::imag(in.value)), 1> {
+
109 return std::imag(in.value);
+
110}
-
109
-
-
110#define DEFAULT_BINARY(OP) \
-
111 template <typename T1, typename T2> \
-
112 auto operator OP(Simd<T1, 1> a, Simd<T2, 1> b) \
-
113 ->Simd<decltype(a.value OP b.value), 1> { \
-
114 return a.value OP b.value; \
-
115 } \
-
116 template <typename T1, typename T2> \
-
117 auto operator OP(T1 a, Simd<T2, 1> b)->Simd<decltype(a OP b.value), 1> { \
-
118 return a OP b.value; \
-
119 } \
-
120 template <typename T1, typename T2> \
-
121 auto operator OP(Simd<T1, 1> a, T2 b)->Simd<decltype(a.value OP b), 1> { \
-
122 return a.value OP b; \
-
123 }
+
111template <typename T>
+
+
112Simd<bool, 1> isnan(Simd<T, 1> in) {
+
113 return std::isnan(in.value);
+
114}
-
124
-
125DEFAULT_BINARY(+)
-
126DEFAULT_BINARY(-)
-
127DEFAULT_BINARY(*)
-
128DEFAULT_BINARY(/)
-
129DEFAULT_BINARY(<<)
-
130DEFAULT_BINARY(>>)
-
131DEFAULT_BINARY(|)
-
132DEFAULT_BINARY(^)
-
133DEFAULT_BINARY(&)
-
134DEFAULT_BINARY(&&)
-
135DEFAULT_BINARY(||)
-
136
-
137template <typename T>
-
-
138Simd<T, 1> remainder(Simd<T, 1> a_, Simd<T, 1> b_) {
-
139 T a = a_.value;
-
140 T b = b_.value;
-
141 T r;
-
142 if constexpr (std::is_integral_v<T>) {
-
143 r = a % b;
-
144 } else {
-
145 r = std::remainder(a, b);
-
146 }
-
147 if constexpr (std::is_signed_v<T>) {
-
148 if (r != 0 && (r < 0 != b < 0)) {
-
149 r += b;
-
150 }
-
151 }
-
152 return r;
-
153}
+
115
+
+
116#define DEFAULT_BINARY(OP) \
+
117 template <typename T1, typename T2> \
+
118 auto operator OP(Simd<T1, 1> a, Simd<T2, 1> b) \
+
119 ->Simd<decltype(a.value OP b.value), 1> { \
+
120 return a.value OP b.value; \
+
121 } \
+
122 template <typename T1, typename T2> \
+
123 auto operator OP(T1 a, Simd<T2, 1> b)->Simd<decltype(a OP b.value), 1> { \
+
124 return a OP b.value; \
+
125 } \
+
126 template <typename T1, typename T2> \
+
127 auto operator OP(Simd<T1, 1> a, T2 b)->Simd<decltype(a.value OP b), 1> { \
+
128 return a.value OP b; \
+
129 }
-
154
-
155template <typename T>
-
-
156Simd<T, 1> maximum(Simd<T, 1> a_, Simd<T, 1> b_) {
-
157 T a = a_.value;
-
158 T b = b_.value;
-
159 if constexpr (!std::is_integral_v<T>) {
-
160 if (std::isnan(a)) {
-
161 return a;
-
162 }
-
163 }
-
164 return (a > b) ? a : b;
-
165}
+
130
+
131DEFAULT_BINARY(+)
+
132DEFAULT_BINARY(-)
+
133DEFAULT_BINARY(*)
+
134DEFAULT_BINARY(/)
+
135DEFAULT_BINARY(<<)
+
136DEFAULT_BINARY(>>)
+
137DEFAULT_BINARY(|)
+
138DEFAULT_BINARY(^)
+
139DEFAULT_BINARY(&)
+
140DEFAULT_BINARY(&&)
+
141DEFAULT_BINARY(||)
+
142
+
143template <typename T>
+
+
144Simd<T, 1> remainder(Simd<T, 1> a_, Simd<T, 1> b_) {
+
145 T a = a_.value;
+
146 T b = b_.value;
+
147 T r;
+
148 if constexpr (std::is_integral_v<T>) {
+
149 r = a % b;
+
150 } else {
+
151 r = std::remainder(a, b);
+
152 }
+
153 if constexpr (std::is_signed_v<T>) {
+
154 if (r != 0 && (r < 0 != b < 0)) {
+
155 r += b;
+
156 }
+
157 }
+
158 return r;
+
159}
-
166
-
167template <typename T>
-
-
168Simd<T, 1> minimum(Simd<T, 1> a_, Simd<T, 1> b_) {
-
169 T a = a_.value;
-
170 T b = b_.value;
-
171 if constexpr (!std::is_integral_v<T>) {
-
172 if (std::isnan(a)) {
-
173 return a;
-
174 }
-
175 }
-
176 return (a < b) ? a : b;
-
177}
+
160
+
161template <typename T>
+
+
162Simd<T, 1> maximum(Simd<T, 1> a_, Simd<T, 1> b_) {
+
163 T a = a_.value;
+
164 T b = b_.value;
+
165 if constexpr (!std::is_integral_v<T>) {
+
166 if (std::isnan(a)) {
+
167 return a;
+
168 }
+
169 }
+
170 return (a > b) ? a : b;
+
171}
-
178
-
179template <typename T>
-
-
180Simd<T, 1> pow(Simd<T, 1> a, Simd<T, 1> b) {
-
181 T base = a.value;
-
182 T exp = b.value;
-
183 if constexpr (!std::is_integral_v<T>) {
-
184 return std::pow(base, exp);
-
185 } else {
-
186 T res = 1;
-
187 while (exp) {
-
188 if (exp & 1) {
-
189 res *= base;
-
190 }
-
191 exp >>= 1;
-
192 base *= base;
-
193 }
-
194 return res;
-
195 }
-
196}
+
172
+
173template <typename T>
+
+
174Simd<T, 1> minimum(Simd<T, 1> a_, Simd<T, 1> b_) {
+
175 T a = a_.value;
+
176 T b = b_.value;
+
177 if constexpr (!std::is_integral_v<T>) {
+
178 if (std::isnan(a)) {
+
179 return a;
+
180 }
+
181 }
+
182 return (a < b) ? a : b;
+
183}
-
197
-
198template <typename T>
-
-
199Simd<T, 1> atan2(Simd<T, 1> a, Simd<T, 1> b) {
-
200 return std::atan2(a.value, b.value);
-
201}
+
184
+
185template <typename T>
+
+
186Simd<T, 1> pow(Simd<T, 1> a, Simd<T, 1> b) {
+
187 T base = a.value;
+
188 T exp = b.value;
+
189 if constexpr (!std::is_integral_v<T>) {
+
190 return std::pow(base, exp);
+
191 } else {
+
192 T res = 1;
+
193 while (exp) {
+
194 if (exp & 1) {
+
195 res *= base;
+
196 }
+
197 exp >>= 1;
+
198 base *= base;
+
199 }
+
200 return res;
+
201 }
+
202}
-
202
-
-
203#define DEFAULT_COMPARISONS(OP) \
-
204 template <typename T1, typename T2> \
-
205 Simd<bool, 1> operator OP(Simd<T1, 1> a, Simd<T2, 1> b) { \
-
206 return a.value OP b.value; \
-
207 } \
-
208 template <typename T1, typename T2> \
-
209 Simd<bool, 1> operator OP(T1 a, Simd<T2, 1> b) { \
-
210 return a OP b.value; \
-
211 } \
-
212 template <typename T1, typename T2> \
-
213 Simd<bool, 1> operator OP(Simd<T1, 1> a, T2 b) { \
-
214 return a.value OP b; \
-
215 }
+
203
+
204template <typename T>
+
+
205Simd<T, 1> atan2(Simd<T, 1> a, Simd<T, 1> b) {
+
206 return std::atan2(a.value, b.value);
+
207}
-
216
-
-
217DEFAULT_COMPARISONS(>)
-
218DEFAULT_COMPARISONS(<)
+
208
+
+
209#define DEFAULT_COMPARISONS(OP) \
+
210 template <typename T1, typename T2> \
+
211 Simd<bool, 1> operator OP(Simd<T1, 1> a, Simd<T2, 1> b) { \
+
212 return a.value OP b.value; \
+
213 } \
+
214 template <typename T1, typename T2> \
+
215 Simd<bool, 1> operator OP(T1 a, Simd<T2, 1> b) { \
+
216 return a OP b.value; \
+
217 } \
+
218 template <typename T1, typename T2> \
+
219 Simd<bool, 1> operator OP(Simd<T1, 1> a, T2 b) { \
+
220 return a.value OP b; \
+
221 }
-
-
219DEFAULT_COMPARISONS(>=)
-
220DEFAULT_COMPARISONS(<=)
+
222
+ -
221DEFAULT_COMPARISONS(==)
-
222DEFAULT_COMPARISONS(!=)
-
223
-
224template <typename MaskT, typename T>
-
225Simd<T, 1> select(Simd<MaskT, 1> mask, Simd<T, 1> x, Simd<T, 1> y) {
-
226 return mask.value ? x.value : y.value;
-
227}
+
225DEFAULT_COMPARISONS(>=)
+
226DEFAULT_COMPARISONS(<=)
-
228
-
229template <typename T>
-
-
230Simd<T, 1> clamp(Simd<T, 1> v, Simd<T, 1> min, Simd<T, 1> max) {
-
231 return std::clamp(v.value, min.value, max.value);
-
232}
+
227DEFAULT_COMPARISONS(==)
+
228DEFAULT_COMPARISONS(!=)
+
229
+
230template <typename MaskT, typename T>
+
+
231Simd<T, 1> select(Simd<MaskT, 1> mask, Simd<T, 1> x, Simd<T, 1> y) {
+
232 return mask.value ? x.value : y.value;
+
233}
-
233
-
234template <typename T, typename U>
-
-
235Simd<T, 1> fma(Simd<T, 1> x, Simd<T, 1> y, U z) {
-
236 return std::fma(x.value, y.value, Simd<T, 1>(z).value);
-
237}
+
234
+
235template <typename T>
+
+
236Simd<T, 1> clamp(Simd<T, 1> v, Simd<T, 1> min, Simd<T, 1> max) {
+
237 return std::clamp(v.value, min.value, max.value);
+
238}
-
238
-
239// Reductions
-
-
240#define DEFAULT_REDUCTION(name, type) \
-
241 template <typename T> \
-
242 type name(Simd<T, 1> x) { \
-
243 return x.value; \
-
244 }
+
239
+
240template <typename T, typename U>
+
+
241Simd<T, 1> fma(Simd<T, 1> x, Simd<T, 1> y, U z) {
+
242 return std::fma(x.value, y.value, Simd<T, 1>(z).value);
+
243}
-
245
-
246DEFAULT_REDUCTION(max, T)
-
247DEFAULT_REDUCTION(min, T)
-
248DEFAULT_REDUCTION(sum, T)
-
249DEFAULT_REDUCTION(prod, T)
-
250DEFAULT_REDUCTION(any, bool)
-
251DEFAULT_REDUCTION(all, bool)
-
252
-
253} // namespace mlx::core::simd
-
DEFAULT_REDUCTION
#define DEFAULT_REDUCTION(name, type)
Definition base_simd.h:240
-
DEFAULT_UNARY
#define DEFAULT_UNARY(name, op)
Definition base_simd.h:68
-
DEFAULT_BINARY
#define DEFAULT_BINARY(OP)
Definition base_simd.h:110
-
DEFAULT_COMPARISONS
#define DEFAULT_COMPARISONS(OP)
Definition base_simd.h:203
+
244
+
245// Reductions
+
+
246#define DEFAULT_REDUCTION(name, type) \
+
247 template <typename T> \
+
248 type name(Simd<T, 1> x) { \
+
249 return x.value; \
+
250 }
+
+
251
+
252DEFAULT_REDUCTION(max, T)
+
253DEFAULT_REDUCTION(min, T)
+
254DEFAULT_REDUCTION(sum, T)
+
255DEFAULT_REDUCTION(prod, T)
+
256DEFAULT_REDUCTION(any, bool)
+
257DEFAULT_REDUCTION(all, bool)
+
258
+
259} // namespace mlx::core::simd
+
DEFAULT_REDUCTION
#define DEFAULT_REDUCTION(name, type)
Definition base_simd.h:246
+
DEFAULT_UNARY
#define DEFAULT_UNARY(name, op)
Definition base_simd.h:69
+
DEFAULT_BINARY
#define DEFAULT_BINARY(OP)
Definition base_simd.h:116
+
DEFAULT_COMPARISONS
#define DEFAULT_COMPARISONS(OP)
Definition base_simd.h:209
mlx::core::std
array std(const array &a, bool keepdims, int ddof=0, StreamOrDevice s={})
Computes the standard deviation of the elements of an array.
mlx::core::simd
Definition accelerate_fp16_simd.h:9
-
mlx::core::simd::isnan
Simd< bool, N > isnan(Simd< T, N > v)
Definition accelerate_simd.h:141
+
mlx::core::simd::isnan
Simd< bool, N > isnan(Simd< T, N > v)
Definition accelerate_simd.h:146
mlx::core::simd::sinh
Simd< float16_t, N > sinh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:41
mlx::core::simd::N
constexpr int N
Definition neon_fp16_simd.h:9
mlx::core::simd::atanh
Simd< float16_t, N > atanh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:34
-
mlx::core::simd::minimum
Simd< T, N > minimum(Simd< T, N > a, Simd< T, N > b)
Definition accelerate_simd.h:210
+
mlx::core::simd::minimum
Simd< T, N > minimum(Simd< T, N > a, Simd< T, N > b)
Definition accelerate_simd.h:215
mlx::core::simd::pow
Simd< float16_t, N > pow(Simd< float16_t, N > x, Simd< float16_t, N > y)
Definition accelerate_fp16_simd.h:54
mlx::core::simd::atan2
Simd< float16_t, N > atan2(Simd< float16_t, N > x, Simd< float16_t, N > y)
Definition accelerate_fp16_simd.h:52
-
mlx::core::simd::prod
T prod(Simd< T, N > x)
Definition accelerate_simd.h:292
+
mlx::core::simd::prod
T prod(Simd< T, N > x)
Definition accelerate_simd.h:297
mlx::core::simd::log10
Simd< float16_t, N > log10(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:39
mlx::core::simd::rint
Simd< T, N > rint(Simd< T, N > v)
Definition accelerate_simd.h:127
-
mlx::core::simd::load
Simd< T, N > load(const T *x)
Definition base_simd.h:27
+
mlx::core::simd::load
Simd< T, N > load(const T *x)
Definition base_simd.h:28
mlx::core::simd::tan
Simd< float16_t, N > tan(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:42
mlx::core::simd::abs
Simd< T, N > abs(Simd< T, N > v)
Definition accelerate_simd.h:112
mlx::core::simd::acosh
Simd< float16_t, N > acosh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:30
-
mlx::core::simd::all
bool all(Simd< T, N > x)
Definition accelerate_simd.h:271
-
mlx::core::simd::sum
T sum(Simd< T, N > x)
Definition accelerate_simd.h:279
-
mlx::core::simd::is_complex
constexpr bool is_complex
Definition base_simd.h:42
-
mlx::core::simd::conj
Simd< T, 1 > conj(Simd< T, 1 > in)
Definition base_simd.h:84
+
mlx::core::simd::all
bool all(Simd< T, N > x)
Definition accelerate_simd.h:276
+
mlx::core::simd::sum
T sum(Simd< T, N > x)
Definition accelerate_simd.h:284
+
mlx::core::simd::is_complex
constexpr bool is_complex
Definition base_simd.h:43
+
mlx::core::simd::conj
Simd< T, 1 > conj(Simd< T, 1 > in)
Definition base_simd.h:85
mlx::core::simd::log2
Simd< float16_t, N > log2(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:38
-
mlx::core::simd::max
T max(Simd< T, N > x)
Definition accelerate_simd.h:283
-
mlx::core::simd::maximum
Simd< T, N > maximum(Simd< T, N > a, Simd< T, N > b)
Definition accelerate_simd.h:204
+
mlx::core::simd::max
T max(Simd< T, N > x)
Definition accelerate_simd.h:288
+
mlx::core::simd::maximum
Simd< T, N > maximum(Simd< T, N > a, Simd< T, N > b)
Definition accelerate_simd.h:209
mlx::core::simd::exp
Simd< T, N > exp(Simd< T, N > in)
Compute exp(x) in an optimizer friendly way as follows:
Definition math.h:28
mlx::core::simd::log
Simd< float16_t, N > log(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:37
mlx::core::simd::floor
Simd< T, N > floor(Simd< T, N > v)
Definition accelerate_simd.h:113
mlx::core::simd::expm1
Simd< float16_t, N > expm1(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:36
-
mlx::core::simd::imag
auto imag(Simd< T, 1 > in) -> Simd< decltype(std::imag(in.value)), 1 >
Definition base_simd.h:102
+
mlx::core::simd::imag
auto imag(Simd< T, 1 > in) -> Simd< decltype(std::imag(in.value)), 1 >
Definition base_simd.h:108
mlx::core::simd::asin
Simd< float16_t, N > asin(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:31
-
mlx::core::simd::any
bool any(Simd< T, N > x)
Definition accelerate_simd.h:275
-
mlx::core::simd::fma
Simd< T, N > fma(Simd< T, N > x, Simd< T, N > y, U z)
Definition accelerate_simd.h:264
+
mlx::core::simd::any
bool any(Simd< T, N > x)
Definition accelerate_simd.h:280
+
mlx::core::simd::fma
Simd< T, N > fma(Simd< T, N > x, Simd< T, N > y, U z)
Definition accelerate_simd.h:269
mlx::core::simd::tanh
Simd< float16_t, N > tanh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:43
mlx::core::simd::atan
Simd< float16_t, N > atan(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:33
mlx::core::simd::asinh
Simd< float16_t, N > asinh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:32
mlx::core::simd::remainder
Simd< float16_t, N > remainder(Simd< float16_t, N > x, Simd< float16_t, N > y)
Definition accelerate_fp16_simd.h:53
-
mlx::core::simd::max_size
static constexpr int max_size
Definition base_simd.h:13
-
mlx::core::simd::min
T min(Simd< T, N > x)
Definition accelerate_simd.h:287
-
mlx::core::simd::real
auto real(Simd< T, 1 > in) -> Simd< decltype(std::real(in.value)), 1 >
Definition base_simd.h:98
+
mlx::core::simd::max_size
static constexpr int max_size
Definition base_simd.h:14
+
mlx::core::simd::min
T min(Simd< T, N > x)
Definition accelerate_simd.h:292
+
mlx::core::simd::real
auto real(Simd< T, 1 > in) -> Simd< decltype(std::real(in.value)), 1 >
Definition base_simd.h:104
mlx::core::simd::log1p
Simd< float16_t, N > log1p(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:40
mlx::core::simd::ceil
Simd< T, N > ceil(Simd< T, N > v)
Definition accelerate_simd.h:120
mlx::core::simd::recip
Simd< T, N > recip(Simd< T, N > v)
Definition accelerate_simd.h:131
mlx::core::simd::sqrt
Simd< T, N > sqrt(Simd< T, N > v)
Definition accelerate_simd.h:129
-
mlx::core::simd::clamp
Simd< T, N > clamp(Simd< T, N > v, Simd< T, N > min, Simd< T, N > max)
Definition accelerate_simd.h:259
+
mlx::core::simd::clamp
Simd< T, N > clamp(Simd< T, N > v, Simd< T, N > min, Simd< T, N > max)
Definition accelerate_simd.h:264
mlx::core::simd::acos
Simd< float16_t, N > acos(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:29
mlx::core::simd::rsqrt
Simd< T, N > rsqrt(Simd< T, N > v)
Definition accelerate_simd.h:130
mlx::core::simd::cosh
Simd< float16_t, N > cosh(Simd< float16_t, N > v)
Definition accelerate_fp16_simd.h:35
-
mlx::core::simd::store
void store(T *dst, Simd< T, N > x)
Definition base_simd.h:32
-
mlx::core::simd::select
Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
Definition accelerate_simd.h:231
-
mlx::core::simd::Simd< T, 1 >::size
static constexpr int size
Definition base_simd.h:17
-
mlx::core::simd::Simd< T, 1 >::Simd
Simd()
Definition base_simd.h:19
-
mlx::core::simd::Simd< T, 1 >::Simd
Simd(Simd< U, 1 > v)
Definition base_simd.h:21
-
mlx::core::simd::Simd< T, 1 >::value
T value
Definition base_simd.h:18
-
mlx::core::simd::Simd< T, 1 >::Simd
Simd(U v)
Definition base_simd.h:23
+
mlx::core::simd::store
void store(T *dst, Simd< T, N > x)
Definition base_simd.h:33
+
mlx::core::simd::select
Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
Definition accelerate_simd.h:236
+
mlx::core::simd::Simd< T, 1 >::size
static constexpr int size
Definition base_simd.h:18
+
mlx::core::simd::Simd< T, 1 >::Simd
Simd()
Definition base_simd.h:20
+
mlx::core::simd::Simd< T, 1 >::Simd
Simd(Simd< U, 1 > v)
Definition base_simd.h:22
+
mlx::core::simd::Simd< T, 1 >::value
T value
Definition base_simd.h:19
+
mlx::core::simd::Simd< T, 1 >::Simd
Simd(U v)
Definition base_simd.h:24
mlx::core::simd::Simd
Definition accelerate_simd.h:55
mlx::core::simd::Simd::value
asd::Vector< scalar_t, N >::packed_t value
Definition accelerate_simd.h:80
diff --git a/docs/build/html/classes.html b/docs/build/html/classes.html index 2d41d3bfa..9ed2c8f37 100644 --- a/docs/build/html/classes.html +++ b/docs/build/html/classes.html @@ -112,7 +112,7 @@ $(function(){initNavTree('classes.html',''); initResizable(true); });
Abs
Abs (mlx::core)
Abs (mlx::core::detail)
AccumHelper (mlx::steel)
Add
Add (mlx::core)
Add (mlx::core::detail)
add_vec (pocketfft::detail)
add_vec< cmplx< T > > (pocketfft::detail)
AddMM (mlx::core)
AffineQuantize (mlx::core::fast)
aligned_allocator (pocketfft::detail::threading)
AllGather (mlx::core::distributed)
Allocator (mlx::core::allocator)
AllReduce (mlx::core::distributed)
And
Arange (mlx::core)
ArcCos
ArcCos (mlx::core)
ArcCos (mlx::core::detail)
ArcCosh
ArcCosh (mlx::core)
ArcCosh (mlx::core::detail)
ArcSin
ArcSin (mlx::core)
ArcSin (mlx::core::detail)
ArcSinh
ArcSinh (mlx::core)
ArcSinh (mlx::core::detail)
ArcTan
ArcTan (mlx::core)
ArcTan (mlx::core::detail)
ArcTan2
ArcTan2 (mlx::core)
ArcTan2 (mlx::core::detail)
ArcTanh
ArcTanh (mlx::core)
ArcTanh (mlx::core::detail)
ArgPartition (mlx::core)
ArgReduce (mlx::core)
ArgSort (mlx::core)
arr (pocketfft::detail)
arr_info (pocketfft::detail)
array (mlx::core)
array::ArrayIterator (mlx::core)
AsStrided (mlx::core)
AsType (mlx::core)
AttnParams (mlx::steel)
B
-
BaseMMAFrag (mlx::steel)
BaseMMAFrag< T, 8, 8 > (mlx::steel)
_MLX_BFloat16::bits_to_bfloat_struct
BitwiseAnd
BitwiseAnd (mlx::core::detail)
BitwiseBinary (mlx::core)
BitwiseOr
BitwiseOr (mlx::core::detail)
BitwiseXor
BitwiseXor (mlx::core::detail)
BlockLoader (mlx::steel)
BlockLoaderT (mlx::steel)
BlockMaskedMM (mlx::core)
BlockMergeSort
BlockMMA (mlx::steel)
BlockSwizzle (mlx::steel)
bool4_or_uint
Broadcast (mlx::core)
BroadcastAxes (mlx::core)
Buffer (mlx::core::allocator)
Buffer (mlx::core::metal)
+
BaseMMAFrag (mlx::steel)
BaseMMAFrag< T, 8, 8 > (mlx::steel)
_MLX_BFloat16::bits_to_bfloat_struct
BitwiseAnd
BitwiseAnd (mlx::core::detail)
BitwiseBinary (mlx::core)
BitwiseInvert
BitwiseInvert (mlx::core)
BitwiseInvert (mlx::core::detail)
BitwiseOr
BitwiseOr (mlx::core::detail)
BitwiseXor
BitwiseXor (mlx::core::detail)
BlockLoader (mlx::steel)
BlockLoaderT (mlx::steel)
BlockMaskedMM (mlx::core)
BlockMergeSort
BlockMMA (mlx::steel)
BlockSwizzle (mlx::steel)
bool4_or_uint
Broadcast (mlx::core)
BroadcastAxes (mlx::core)
Buffer (mlx::core::allocator)
Buffer (mlx::core::metal)
C
Ceil
Ceil (mlx::core)
Ceil (mlx::core::detail)
cfftp (pocketfft::detail)
ChannelHelper (mlx::steel)
ChannelHelper< 1 > (mlx::steel)
ChannelHelper< 2 > (mlx::steel)
ChannelHelper< 3 > (mlx::steel)
ChannelHelper< 4 > (mlx::steel)
Cholesky (mlx::core)
cmplx (pocketfft::detail)
cndarr (pocketfft::detail)
CommandEncoder (mlx::core)
CommandEncoder (mlx::core::metal)
CommonAllocator (mlx::core::allocator)
Compiled (mlx::core)
complex128_t (mlx::core)
complex64_t
complex64_t (mlx::core)
Concatenate (mlx::core)
concurrent_queue (pocketfft::detail::threading)
CommandEncoder::ConcurrentContext (mlx::core)
CommandEncoder::ConcurrentContext (mlx::core::metal)
ConditionalType
ConditionalType< true, T, U >
Conjugate
Conjugate (mlx::core)
Conjugate (mlx::core::detail)
Contiguous (mlx::core)
ContiguousIterator (mlx::core)
Conv2DGeneralBaseInfo (mlx::steel)
Conv2DGeneralJumpParams (mlx::steel)
Conv2DInputBlockLoaderGeneral (mlx::steel)
Conv2DInputBlockLoaderLargeFilter (mlx::steel)
Conv2DInputBlockLoaderSmallChannels (mlx::steel)
Conv2DInputBlockLoaderSmallFilter (mlx::steel)
Conv2DWeightBlockLoader (mlx::steel)
Conv2DWeightBlockLoaderGeneral (mlx::steel)
Conv2DWeightBlockLoaderSmallChannels (mlx::steel)
Convolution (mlx::core)
Copy (mlx::core)
Cos
Cos (mlx::core)
Cos (mlx::core::detail)
Cosh
Cosh (mlx::core)
Cosh (mlx::core::detail)
CShape (mlx::steel)
CumMax
CumMin
CumProd
CumProd< bool >
CumSum
Custom (mlx::core::fast)
CustomKernel (mlx::core::fast)
CustomKernelShapeInfo (mlx::core::fast)
CustomTransforms (mlx::core)
@@ -142,13 +142,13 @@ $(function(){initNavTree('classes.html',''); initResizable(true); });
KernelMergeSort
KernelMultiBlockMergeSort
KeySequence (mlx::core::random)
L
-
latch (pocketfft::detail::threading)
LayerNorm (mlx::core::fast)
LayerNormVJP (mlx::core::fast)
Layout2D (mlx::steel)
LeftShift
LeftShift (mlx::core::detail)
Less
Less (mlx::core::detail)
Less (mlx::core)
LessEqual
LessEqual (mlx::core::detail)
LessEqual (mlx::core)
LessThan
Limits
Limits< bfloat16_t >
Limits< bool >
Limits< complex64_t >
Limits< float >
Limits< half >
Limits< int16_t >
Limits< int32_t >
Limits< int64_t >
Limits< int8_t >
Limits< uint16_t >
Limits< uint32_t >
Limits< uint64_t >
Limits< uint8_t >
Load (mlx::core)
Log
Log (mlx::core::detail)
Log (mlx::core)
Log10
Log10 (mlx::core::detail)
Log1p
Log1p (mlx::core::detail)
Log1p (mlx::core)
Log2
Log2 (mlx::core::detail)
LogAddExp
LogAddExp (mlx::core::detail)
LogAddExp (mlx::core)
LogicalAnd
LogicalAnd (mlx::core::detail)
LogicalAnd (mlx::core)
LogicalNot
LogicalNot (mlx::core::detail)
LogicalNot (mlx::core)
LogicalOr
LogicalOr (mlx::core::detail)
LogicalOr (mlx::core)
LoopAlignment (mlx::steel)
LoopedElemToLoc
LoopedElemToLoc< 1, OffsetT, false >
LoopedElemToLoc< 1, OffsetT, true >
+
latch (pocketfft::detail::threading)
LayerNorm (mlx::core::fast)
LayerNormVJP (mlx::core::fast)
Layout2D (mlx::steel)
LeftShift
LeftShift (mlx::core::detail)
Less
Less (mlx::core::detail)
Less (mlx::core)
LessEqual
LessEqual (mlx::core::detail)
LessEqual (mlx::core)
LessThan
Limits
Limits< bfloat16_t >
Limits< bool >
Limits< complex64_t >
Limits< float >
Limits< half >
Limits< int16_t >
Limits< int32_t >
Limits< int64_t >
Limits< int8_t >
Limits< uint16_t >
Limits< uint32_t >
Limits< uint64_t >
Limits< uint8_t >
Load (mlx::core)
Log
Log (mlx::core::detail)
Log (mlx::core)
Log10
Log10 (mlx::core::detail)
Log1p
Log1p (mlx::core::detail)
Log1p (mlx::core)
Log2
Log2 (mlx::core::detail)
LogAddExp
LogAddExp (mlx::core::detail)
LogAddExp (mlx::core)
LogicalAnd
LogicalAnd (mlx::core::detail)
LogicalAnd (mlx::core)
LogicalNot
LogicalNot (mlx::core::detail)
LogicalNot (mlx::core)
LogicalOr
LogicalOr (mlx::core::detail)
LogicalOr (mlx::core)
LoopAlignment (mlx::steel)
LoopedElemToLoc
LoopedElemToLoc< 1, OffsetT, false >
LoopedElemToLoc< 1, OffsetT, true >
LUF (mlx::core)
M
make_void (metal)
Matmul (mlx::core)
Max
Maximum
Maximum (mlx::core::detail)
Maximum (mlx::core)
MaxOp
MetalAllocator (mlx::core::metal)
Min
Minimum
Minimum (mlx::core::detail)
Minimum (mlx::core)
mlx_atomic
mlx_atomic< T, enable_if_t< is_metal_atomic< T > > >
MLXConvParams
MMATile (mlx::steel)
MulOp
multi_iter (pocketfft::detail)
Multiply (mlx::core::detail)
Multiply (mlx::core)
Multiply
N
-
NaNEqual (mlx::core::detail)
NaNEqual
ndarr (pocketfft::detail)
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None
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NotEqual (mlx::core)
NotEqual
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numeric_limits (mlx::core)
numeric_limits< bfloat16_t > (mlx::core)
numeric_limits< float > (mlx::core)
numeric_limits< float16_t > (mlx::core)
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NaNEqual (mlx::core::detail)
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numeric_limits (mlx::core)
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numeric_limits< double > (mlx::core)
numeric_limits< float > (mlx::core)
numeric_limits< float16_t > (mlx::core)
O
Or
diff --git a/docs/build/html/classmlx_1_1core_1_1_bitwise_invert-members.html b/docs/build/html/classmlx_1_1core_1_1_bitwise_invert-members.html new file mode 100644 index 000000000..b40fe8d2d --- /dev/null +++ b/docs/build/html/classmlx_1_1core_1_1_bitwise_invert-members.html @@ -0,0 +1,145 @@ + + + + + + + +MLX: Member List + + + + + + + + + + + + + + + + +
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template<typename T>
Simd< T, 1 > mlx::core::simd::tanh (Simd< T, 1 > in)
 
template<typename T>
Simd< T, 1 > mlx::core::simd::operator~ (Simd< T, 1 > in)
 
template<typename T>
auto mlx::core::simd::real (Simd< T, 1 > in) -> Simd< decltype(std::real(in.value)), 1 >
 
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mlx::core::BitwiseInvert Member List
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This is the complete list of members for mlx::core::BitwiseInvert, including all inherited members.

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BitwiseInvert(Stream stream)mlx::core::BitwiseInvertinlineexplicit
device()mlx::core::Primitiveinline
eval_cpu(const std::vector< array > &inputs, array &out) overridemlx::core::BitwiseInvertvirtual
mlx::core::UnaryPrimitive::eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) overridemlx::core::UnaryPrimitiveinlinevirtual
eval_gpu(const std::vector< array > &inputs, array &out) overridemlx::core::BitwiseInvertvirtual
mlx::core::UnaryPrimitive::eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) overridemlx::core::UnaryPrimitiveinlinevirtual
is_equivalent(const Primitive &other) const overridemlx::core::BitwiseInvertinlinevirtual
jvp(const std::vector< array > &primals, const std::vector< array > &tangents, const std::vector< int > &argnums)mlx::core::Primitivevirtual
operator=(const UnaryPrimitive &other)=deletemlx::core::UnaryPrimitive
operator=(UnaryPrimitive &&other)=deletemlx::core::UnaryPrimitive
mlx::core::Primitive::operator=(const Primitive &other)=deletemlx::core::Primitive
mlx::core::Primitive::operator=(Primitive &&other)=deletemlx::core::Primitive
output_shapes(const std::vector< array > &inputs) overridemlx::core::BitwiseInvertinlinevirtual
Primitive(Stream stream)mlx::core::Primitiveinlineexplicit
Primitive(const Primitive &other)=deletemlx::core::Primitive
Primitive(Primitive &&other)=deletemlx::core::Primitive
print(std::ostream &os) overridemlx::core::BitwiseInvertinlinevirtual
stream()mlx::core::Primitiveinline
UnaryPrimitive(Stream stream)mlx::core::UnaryPrimitiveinlineexplicit
UnaryPrimitive(const UnaryPrimitive &other)=deletemlx::core::UnaryPrimitive
UnaryPrimitive(UnaryPrimitive &&other)=deletemlx::core::UnaryPrimitive
vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs)mlx::core::Primitivevirtual
vmap(const std::vector< array > &inputs, const std::vector< int > &axes) overridemlx::core::BitwiseInvertvirtual
~Primitive()=defaultmlx::core::Primitivevirtual
~UnaryPrimitive()=defaultmlx::core::UnaryPrimitivevirtual
+
+ + + + diff --git a/docs/build/html/classmlx_1_1core_1_1_bitwise_invert.html b/docs/build/html/classmlx_1_1core_1_1_bitwise_invert.html new file mode 100644 index 000000000..2200e0910 --- /dev/null +++ b/docs/build/html/classmlx_1_1core_1_1_bitwise_invert.html @@ -0,0 +1,413 @@ + + + + + + + +MLX: mlx::core::BitwiseInvert Class Reference + + + + + + + + + + + + + + + + +
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+Public Member Functions | +List of all members
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mlx::core::BitwiseInvert Class Reference
+
+
+ +

#include <primitives.h>

+
+Inheritance diagram for mlx::core::BitwiseInvert:
+
+
+ + +mlx::core::UnaryPrimitive +mlx::core::Primitive + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 BitwiseInvert (Stream stream)
 
void eval_cpu (const std::vector< array > &inputs, array &out) override
 
void eval_gpu (const std::vector< array > &inputs, array &out) override
 
virtual std::pair< std::vector< array >, std::vector< int > > vmap (const std::vector< array > &inputs, const std::vector< int > &axes) override
 The primitive must know how to vectorize itself across the given axes.
 
void print (std::ostream &os) override
 Print the primitive.
 
bool is_equivalent (const Primitive &other) const override
 Equivalence check defaults to false unless overridden by the primitive.
 
std::vector< Shape > output_shapes (const std::vector< array > &inputs) override
 Get the output shapes of the primitive.
 
- Public Member Functions inherited from mlx::core::UnaryPrimitive
 UnaryPrimitive (Stream stream)
 An abstract base class for a primitive with a single output.
 
void eval_cpu (const std::vector< array > &inputs, std::vector< array > &outputs) override
 A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the output arrays.
 
void eval_gpu (const std::vector< array > &inputs, std::vector< array > &outputs) override
 
virtual ~UnaryPrimitive ()=default
 
 UnaryPrimitive (const UnaryPrimitive &other)=delete
 
 UnaryPrimitive (UnaryPrimitive &&other)=delete
 
UnaryPrimitive & operator= (const UnaryPrimitive &other)=delete
 
UnaryPrimitive & operator= (UnaryPrimitive &&other)=delete
 
- Public Member Functions inherited from mlx::core::Primitive
 Primitive (Stream stream)
 
const Device & device ()
 The device the primitive will run on.
 
const Stream & stream ()
 The stream the primitive will run on.
 
virtual std::vector< array > jvp (const std::vector< array > &primals, const std::vector< array > &tangents, const std::vector< int > &argnums)
 The Jacobian-vector product.
 
virtual std::vector< array > vjp (const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs)
 The vector-Jacobian product.
 
virtual ~Primitive ()=default
 
 Primitive (const Primitive &other)=delete
 
 Primitive (Primitive &&other)=delete
 
Primitive & operator= (const Primitive &other)=delete
 
Primitive & operator= (Primitive &&other)=delete
 
+

Constructor & Destructor Documentation

+ +

◆ BitwiseInvert()

+ +
+
+ + + + + +
+ + + + + + + +
mlx::core::BitwiseInvert::BitwiseInvert (Stream stream)
+ 		+inlineexplicit
+
+ +
+
+

Member Function Documentation

+ +

◆ eval_cpu()

+ +
+
+ + + + + +
+ + + + + + + + + + + +
void mlx::core::BitwiseInvert::eval_cpu (const std::vector< array > & inputs,
array & out )
+ 		+overridevirtual
+
+ +

Implements mlx::core::UnaryPrimitive.

+ +
+
+ +

◆ eval_gpu()

+ +
+
+ + + + + +
+ + + + + + + + + + + +
void mlx::core::BitwiseInvert::eval_gpu (const std::vector< array > & inputs,
array & out )
+ 		+overridevirtual
+
+ +

Implements mlx::core::UnaryPrimitive.

+ +
+
+ +

◆ is_equivalent()

+ +
+
+ + + + + +
+ + + + + + + +
bool mlx::core::BitwiseInvert::is_equivalent (const Primitive & other) const
+ 		+inlineoverridevirtual
+
+ +

Equivalence check defaults to false unless overridden by the primitive.

+ +

Reimplemented from mlx::core::Primitive.

+ +
+
+ +

◆ output_shapes()

+ +
+
+ + + + + +
+ + + + + + + +
std::vector< Shape > mlx::core::BitwiseInvert::output_shapes (const std::vector< array > & inputs)
+ 		+inlineoverridevirtual
+
+ +

Get the output shapes of the primitive.

+

This is not required to be implemented by derived classes, in which case it will throw.

+ +

Reimplemented from mlx::core::Primitive.

+ +
+
+ +

◆ print()

+ +
+
+ + + + + +
+ + + + + + + +
void mlx::core::BitwiseInvert::print (std::ostream & os)
+ 		+inlineoverridevirtual
+
+ +

Print the primitive.

+ +

Implements mlx::core::Primitive.

+ +
+
+ +

◆ vmap()

+ +
+
+ + + + + +
+ + + + + + + + + + + +
virtual std::pair< std::vector< array >, std::vector< int > > mlx::core::BitwiseInvert::vmap (const std::vector< array > & inputs,
const std::vector< int > & axes )
+ 		+overridevirtual
+
+ +

The primitive must know how to vectorize itself across the given axes.

+

The output is a pair containing the output arrays representing the vectorized computation and the axes which corresponds to the vectorized dimensions of each output.

+ +

Reimplemented from mlx::core::Primitive.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+ + + + diff --git a/docs/build/html/classmlx_1_1core_1_1_bitwise_invert.js b/docs/build/html/classmlx_1_1core_1_1_bitwise_invert.js new file mode 100644 index 000000000..01879ac95 --- /dev/null +++ b/docs/build/html/classmlx_1_1core_1_1_bitwise_invert.js @@ -0,0 +1,10 @@ +var classmlx_1_1core_1_1_bitwise_invert = +[ + [ "BitwiseInvert", "classmlx_1_1core_1_1_bitwise_invert.html#aaa0180570a82e93988b982b93cd91623", null ], + [ "eval_cpu", "classmlx_1_1core_1_1_bitwise_invert.html#af7de39edef13cf483a6140f2dad4187e", null ], + [ "eval_gpu", "classmlx_1_1core_1_1_bitwise_invert.html#a09162c49334380f5a04433e00427abfa", null ], + [ "is_equivalent", "classmlx_1_1core_1_1_bitwise_invert.html#a22457fe46135c2df426b89cc15b1f940", null ], + [ "output_shapes", "classmlx_1_1core_1_1_bitwise_invert.html#a36558873262f1353f1575590e68ef8bf", null ], + [ "print", "classmlx_1_1core_1_1_bitwise_invert.html#a7a122900d844f1e57a0faa7ad8b47a5c", null ], + [ "vmap", "classmlx_1_1core_1_1_bitwise_invert.html#a2213ba033d215cca411edca552ac634e", null ] +]; \ No newline at end of file diff --git a/docs/build/html/classmlx_1_1core_1_1_bitwise_invert.png b/docs/build/html/classmlx_1_1core_1_1_bitwise_invert.png new file mode 100644 index 0000000000000000000000000000000000000000..fa6939e93b39b574e07887d3adf6e89ed8655e0d GIT binary patch literal 922 zcmeAS@N?(olHy`uVBq!ia0vp^(}1{xgBeH~F+Z{fQqloFA+G=b{|7Q(y!l$%e`vXd zfo6fk^fNCWJa_;UH$5A+1SrQ@666=m0OW&#In(Sb3=GVwo-U3d6^w7^zRr7W#lz-4 zzoFs%|0BmsYZm6*Ox<*I9p5RZ<{f4ydo)-5^yXI+hYUBFP&#eSfoXXV!lo|mS}uBDhRy1pQ)Qi$=<5;2DSnFaDA1_w(1w(E01;dryk0b9$}zNUQL& z*6N=%4~3?M$J#&J@b~TZ2QLpAzKhJ&-+t%weG}IF{Xcf?z816HUgp^@{cvhue!!B?QRX%4Z(sfN{PCjb zxi_=kZgZ@0Ty6d7c9z?|&!y$Ff6SX^FLpmOSNhhx4R5RJ>ux;Ud%NBE?!~NG7c4s` zeJPClBmKkqf6cvZzg9=RkN#W#FVy>zy*e;5Pwj}>dd*6PVg4gV1G(fZTRG>d-j$}2 zy)R5xgw1nlu)quq>>(AuAk<6qv7@1}bng`-D*pXTZI|+O%g(nCv(jF# zDC5feH|Gs&zTcvmHwBhVn;AI;?)qa_wU$nK_=DeK#w^~T#W~HuT*Tn%>gTe~DWM4f D$2Q8m literal 0 HcmV?d00001 diff --git a/docs/build/html/classmlx_1_1core_1_1_l_u_f-members.html b/docs/build/html/classmlx_1_1core_1_1_l_u_f-members.html new file mode 100644 index 000000000..6d4a2eff6 --- /dev/null +++ b/docs/build/html/classmlx_1_1core_1_1_l_u_f-members.html @@ -0,0 +1,137 @@ + + + + + + + +MLX: Member List + + + + + + + + + + + + + + + + +
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mlx::core::LUF Member List
+
+
+ +

This is the complete list of members for mlx::core::LUF, including all inherited members.

+ + + + + + + + + + + + + + + + + + +
device()mlx::core::Primitiveinline
eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) overridemlx::core::LUFvirtual
eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) overridemlx::core::LUFvirtual
is_equivalent(const Primitive &other) constmlx::core::Primitiveinlinevirtual
jvp(const std::vector< array > &primals, const std::vector< array > &tangents, const std::vector< int > &argnums)mlx::core::Primitivevirtual
LUF(Stream stream)mlx::core::LUFinlineexplicit
operator=(const Primitive &other)=deletemlx::core::Primitive
operator=(Primitive &&other)=deletemlx::core::Primitive
output_shapes(const std::vector< array > &inputs)mlx::core::Primitivevirtual
Primitive(Stream stream)mlx::core::Primitiveinlineexplicit
Primitive(const Primitive &other)=deletemlx::core::Primitive
Primitive(Primitive &&other)=deletemlx::core::Primitive
print(std::ostream &os) overridemlx::core::LUFinlinevirtual
stream()mlx::core::Primitiveinline
vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs)mlx::core::Primitivevirtual
vmap(const std::vector< array > &inputs, const std::vector< int > &axes)mlx::core::Primitivevirtual
~Primitive()=defaultmlx::core::Primitivevirtual
+
+ + + + diff --git a/docs/build/html/classmlx_1_1core_1_1_l_u_f.html b/docs/build/html/classmlx_1_1core_1_1_l_u_f.html new file mode 100644 index 000000000..e475455c3 --- /dev/null +++ b/docs/build/html/classmlx_1_1core_1_1_l_u_f.html @@ -0,0 +1,304 @@ + + + + + + + +MLX: mlx::core::LUF Class Reference + + + + + + + + + + + + + + + + +
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+ + + + + + + +
+
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mlx::core::LUF Class Reference
+
+
+ +

#include <primitives.h>

+
+Inheritance diagram for mlx::core::LUF:
+
+
+ + +mlx::core::Primitive + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

 LUF (Stream stream)
 
void eval_cpu (const std::vector< array > &inputs, std::vector< array > &outputs) override
 A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the output arrays.
 
void eval_gpu (const std::vector< array > &inputs, std::vector< array > &outputs) override
 
void print (std::ostream &os) override
 Print the primitive.
 
- Public Member Functions inherited from mlx::core::Primitive
 Primitive (Stream stream)
 
const Device & device ()
 The device the primitive will run on.
 
const Stream & stream ()
 The stream the primitive will run on.
 
virtual std::vector< array > jvp (const std::vector< array > &primals, const std::vector< array > &tangents, const std::vector< int > &argnums)
 The Jacobian-vector product.
 
virtual std::vector< array > vjp (const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs)
 The vector-Jacobian product.
 
virtual std::pair< std::vector< array >, std::vector< int > > vmap (const std::vector< array > &inputs, const std::vector< int > &axes)
 The primitive must know how to vectorize itself across the given axes.
 
virtual bool is_equivalent (const Primitive &other) const
 Equivalence check defaults to false unless overridden by the primitive.
 
virtual std::vector< Shape > output_shapes (const std::vector< array > &inputs)
 Get the output shapes of the primitive.
 
virtual ~Primitive ()=default
 
 Primitive (const Primitive &other)=delete
 
 Primitive (Primitive &&other)=delete
 
Primitive & operator= (const Primitive &other)=delete
 
Primitive & operator= (Primitive &&other)=delete
 
+

Constructor & Destructor Documentation

+ +

◆ LUF()

+ +
+
+ + + + + +
+ + + + + + + +
mlx::core::LUF::LUF (Stream stream)
+ 		+inlineexplicit
+
+ +
+
+

Member Function Documentation

+ +

◆ eval_cpu()

+ +
+
+ + + + + +
+ + + + + + + + + + + +
void mlx::core::LUF::eval_cpu (const std::vector< array > & inputs,
std::vector< array > & outputs )
+ 		+overridevirtual
+
+ +

A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the output arrays.

+

To avoid unnecessary allocations, the evaluation function is responsible for allocating space for the array.

+ +

Implements mlx::core::Primitive.

+ +
+
+ +

◆ eval_gpu()

+ +
+
+ + + + + +
+ + + + + + + + + + + +
void mlx::core::LUF::eval_gpu (const std::vector< array > & inputs,
std::vector< array > & outputs )
+ 		+overridevirtual
+
+ +

Implements mlx::core::Primitive.

+ +
+
+ +

◆ print()

+ +
+
+ + + + + +
+ + + + + + + +
void mlx::core::LUF::print (std::ostream & os)
+ 		+inlineoverridevirtual
+
+ +

Print the primitive.

+ +

Implements mlx::core::Primitive.

+ +
+
+
The documentation for this class was generated from the following file: +
+
+ + + + diff --git a/docs/build/html/classmlx_1_1core_1_1_l_u_f.js b/docs/build/html/classmlx_1_1core_1_1_l_u_f.js new file mode 100644 index 000000000..1c9cf18be --- /dev/null +++ b/docs/build/html/classmlx_1_1core_1_1_l_u_f.js @@ -0,0 +1,7 @@ +var classmlx_1_1core_1_1_l_u_f = +[ + [ "LUF", "classmlx_1_1core_1_1_l_u_f.html#a0d8687ad3af3ff5b74881f1a4b312051", null ], + [ "eval_cpu", "classmlx_1_1core_1_1_l_u_f.html#a6cb497d6b011210a8090bdc8fdf14913", null ], + [ "eval_gpu", "classmlx_1_1core_1_1_l_u_f.html#aa2e955a6ca2ffbfab463a3e9c69beabf", null ], + [ "print", "classmlx_1_1core_1_1_l_u_f.html#a7e71d966d49e473f4bf0524c18425a07", null ] +]; \ No newline at end of file diff --git a/docs/build/html/classmlx_1_1core_1_1_l_u_f.png b/docs/build/html/classmlx_1_1core_1_1_l_u_f.png new file mode 100644 index 0000000000000000000000000000000000000000..fe727c03c3ef642223630870e6a7efb394e4b8d7 GIT binary patch literal 506 zcmVvTJr#LVva2S`&=-}Ys|Ns9r%~qrU000SeQchC<|NsC0|NsC0Hv*f~0004n zNkltAdqBVhLj|m z@g-6t$=9*@ua-NlpMxZGK9~NIbF@{G+WKD0!X?B))@cdbYTJV6Z-o8Fs{8mI@=AS7Q3+|>liz9iDpyOZy>lpy7v{36Qr~q4mF}D6R9bDM zG_po2?{s&(=ThHnXVP@kdH1GuL@wmZyhjeoGx85TCN8LN50ML#h1%PG@DF8HMNCBW3Lka-R7*YUe#*hL)GlmoZ zPB1g;4NQ{yGNh8!j4zb_@r7deGEE=PPL-sBrcz0&QI*=7vMgM7eDQUP58FRRoiA5?l(Bc+iwQhBFm$16!SUX-Sz&bv3Q wV|YC4b&{kS<7ZHknlYr3)Qo>6H8bnX5A*zD24V;uVE_OC07*qoM6N<$f*6_X*#H0l literal 0 HcmV?d00001 diff --git a/docs/build/html/classmlx_1_1core_1_1_primitive.html b/docs/build/html/classmlx_1_1core_1_1_primitive.html index 7eaf3dc5e..c5c9717f2 100644 --- a/docs/build/html/classmlx_1_1core_1_1_primitive.html +++ b/docs/build/html/classmlx_1_1core_1_1_primitive.html @@ -121,13 +121,14 @@ Inheritance diagram for mlx::core::Primitive:
mlx::core::Depends mlx::core::DivMod mlx::core::Eigh -mlx::core::QRF -mlx::core::SVD -mlx::core::Split -mlx::core::UnaryPrimitive -mlx::core::distributed::DistPrimitive -mlx::core::fast::Custom -mlx::core::fast::CustomKernel +mlx::core::LUF +mlx::core::QRF +mlx::core::SVD +mlx::core::Split +mlx::core::UnaryPrimitive +mlx::core::distributed::DistPrimitive +mlx::core::fast::Custom +mlx::core::fast::CustomKernel
@@ -334,7 +335,7 @@ Public Member Functions

A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the output arrays.

To avoid unnecessary allocations, the evaluation function is responsible for allocating space for the array.

-

Implemented in mlx::core::Compiled, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Recv, mlx::core::distributed::Send, mlx::core::DivMod, mlx::core::Eigh, mlx::core::fast::AffineQuantize, mlx::core::fast::CustomKernel, mlx::core::fast::LayerNorm, mlx::core::fast::LayerNormVJP, mlx::core::fast::RMSNorm, mlx::core::fast::RMSNormVJP, mlx::core::fast::RoPE, mlx::core::fast::ScaledDotProductAttention, mlx::core::QRF, mlx::core::Split, mlx::core::SVD, and mlx::core::UnaryPrimitive.

+

Implemented in mlx::core::Compiled, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Recv, mlx::core::distributed::Send, mlx::core::DivMod, mlx::core::Eigh, mlx::core::fast::AffineQuantize, mlx::core::fast::CustomKernel, mlx::core::fast::LayerNorm, mlx::core::fast::LayerNormVJP, mlx::core::fast::RMSNorm, mlx::core::fast::RMSNormVJP, mlx::core::fast::RoPE, mlx::core::fast::ScaledDotProductAttention, mlx::core::LUF, mlx::core::QRF, mlx::core::Split, mlx::core::SVD, and mlx::core::UnaryPrimitive.

@@ -365,7 +366,7 @@ Public Member Functions
-

Implemented in mlx::core::Compiled, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Recv, mlx::core::distributed::Send, mlx::core::DivMod, mlx::core::Eigh, mlx::core::fast::AffineQuantize, mlx::core::fast::CustomKernel, mlx::core::fast::LayerNorm, mlx::core::fast::LayerNormVJP, mlx::core::fast::RMSNorm, mlx::core::fast::RMSNormVJP, mlx::core::fast::RoPE, mlx::core::fast::ScaledDotProductAttention, mlx::core::QRF, mlx::core::Split, mlx::core::SVD, and mlx::core::UnaryPrimitive.

+

Implemented in mlx::core::Compiled, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Recv, mlx::core::distributed::Send, mlx::core::DivMod, mlx::core::Eigh, mlx::core::fast::AffineQuantize, mlx::core::fast::CustomKernel, mlx::core::fast::LayerNorm, mlx::core::fast::LayerNormVJP, mlx::core::fast::RMSNorm, mlx::core::fast::RMSNormVJP, mlx::core::fast::RoPE, mlx::core::fast::ScaledDotProductAttention, mlx::core::LUF, mlx::core::QRF, mlx::core::Split, mlx::core::SVD, and mlx::core::UnaryPrimitive.

@@ -394,7 +395,7 @@ Public Member Functions

Equivalence check defaults to false unless overridden by the primitive.

-

Reimplemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::fast::AffineQuantize, mlx::core::fast::ScaledDotProductAttention, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

+

Reimplemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::fast::AffineQuantize, mlx::core::fast::ScaledDotProductAttention, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

@@ -512,7 +513,7 @@ Public Member Functions

Get the output shapes of the primitive.

This is not required to be implemented by derived classes, in which case it will throw.

-

Reimplemented in mlx::core::Abs, mlx::core::Add, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::Flatten, mlx::core::Floor, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, and mlx::core::Unflatten.

+

Reimplemented in mlx::core::Abs, mlx::core::Add, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::Flatten, mlx::core::Floor, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, and mlx::core::Unflatten.

@@ -541,7 +542,7 @@ Public Member Functions

Print the primitive.

-

Implemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

+

Implemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::LUF, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

@@ -645,7 +646,7 @@ Public Member Functions

The primitive must know how to vectorize itself across the given axes.

The output is a pair containing the output arrays representing the vectorized computation and the axes which corresponds to the vectorized dimensions of each output.

-

Reimplemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

+

Reimplemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

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mlx::core::AsStrided mlx::core::AsType mlx::core::BitwiseBinary -mlx::core::BlockMaskedMM -mlx::core::Broadcast -mlx::core::BroadcastAxes -mlx::core::Ceil -mlx::core::Cholesky -mlx::core::Concatenate -mlx::core::Conjugate -mlx::core::Contiguous -mlx::core::Convolution -mlx::core::Copy -mlx::core::Cos -mlx::core::Cosh -mlx::core::Divide -mlx::core::DynamicSlice -mlx::core::DynamicSliceUpdate -mlx::core::Equal -mlx::core::Erf -mlx::core::ErfInv -mlx::core::Exp -mlx::core::ExpandDims -mlx::core::Expm1 -mlx::core::FFT -mlx::core::Flatten -mlx::core::Floor -mlx::core::Full -mlx::core::Gather -mlx::core::GatherAxis -mlx::core::GatherMM -mlx::core::GatherQMM -mlx::core::Greater -mlx::core::GreaterEqual -mlx::core::Hadamard -mlx::core::Imag -mlx::core::Inverse -mlx::core::Less -mlx::core::LessEqual -mlx::core::Load -mlx::core::Log -mlx::core::Log1p -mlx::core::LogAddExp -mlx::core::LogicalAnd -mlx::core::LogicalNot -mlx::core::LogicalOr -mlx::core::Matmul -mlx::core::Maximum -mlx::core::Minimum -mlx::core::Multiply -mlx::core::Negative -mlx::core::NotEqual -mlx::core::NumberOfElements -mlx::core::Pad -mlx::core::Partition -mlx::core::Power -mlx::core::QuantizedMatmul -mlx::core::RandomBits -mlx::core::Real -mlx::core::Reduce -mlx::core::Remainder -mlx::core::Reshape -mlx::core::Round -mlx::core::Scan -mlx::core::Scatter -mlx::core::ScatterAxis -mlx::core::Select -mlx::core::Sigmoid -mlx::core::Sign -mlx::core::Sin -mlx::core::Sinh -mlx::core::Slice -mlx::core::SliceUpdate -mlx::core::Softmax -mlx::core::Sort -mlx::core::Sqrt -mlx::core::Square -mlx::core::Squeeze -mlx::core::StopGradient -mlx::core::Subtract -mlx::core::Tan -mlx::core::Tanh -mlx::core::Transpose -mlx::core::Unflatten -mlx::core::View +mlx::core::BitwiseInvert +mlx::core::BlockMaskedMM +mlx::core::Broadcast +mlx::core::BroadcastAxes +mlx::core::Ceil +mlx::core::Cholesky +mlx::core::Concatenate +mlx::core::Conjugate +mlx::core::Contiguous +mlx::core::Convolution +mlx::core::Copy +mlx::core::Cos +mlx::core::Cosh +mlx::core::Divide +mlx::core::DynamicSlice +mlx::core::DynamicSliceUpdate +mlx::core::Equal +mlx::core::Erf +mlx::core::ErfInv +mlx::core::Exp +mlx::core::ExpandDims +mlx::core::Expm1 +mlx::core::FFT +mlx::core::Flatten +mlx::core::Floor +mlx::core::Full +mlx::core::Gather +mlx::core::GatherAxis +mlx::core::GatherMM +mlx::core::GatherQMM +mlx::core::Greater +mlx::core::GreaterEqual +mlx::core::Hadamard +mlx::core::Imag +mlx::core::Inverse +mlx::core::Less +mlx::core::LessEqual +mlx::core::Load +mlx::core::Log +mlx::core::Log1p +mlx::core::LogAddExp +mlx::core::LogicalAnd +mlx::core::LogicalNot +mlx::core::LogicalOr +mlx::core::Matmul +mlx::core::Maximum +mlx::core::Minimum +mlx::core::Multiply +mlx::core::Negative +mlx::core::NotEqual +mlx::core::NumberOfElements +mlx::core::Pad +mlx::core::Partition +mlx::core::Power +mlx::core::QuantizedMatmul +mlx::core::RandomBits +mlx::core::Real +mlx::core::Reduce +mlx::core::Remainder +mlx::core::Reshape +mlx::core::Round +mlx::core::Scan +mlx::core::Scatter +mlx::core::ScatterAxis +mlx::core::Select +mlx::core::Sigmoid +mlx::core::Sign +mlx::core::Sin +mlx::core::Sinh +mlx::core::Slice +mlx::core::SliceUpdate +mlx::core::Softmax +mlx::core::Sort +mlx::core::Sqrt +mlx::core::Square +mlx::core::Squeeze +mlx::core::StopGradient +mlx::core::Subtract +mlx::core::Tan +mlx::core::Tanh +mlx::core::Transpose +mlx::core::Unflatten +mlx::core::View
@@ -412,7 +413,7 @@ Public Member Functions
-

Implemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

+

Implemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

@@ -477,7 +478,7 @@ Public Member Functions
-

Implemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

+

Implemented in mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, and mlx::core::View.

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zk!}BFH6%T}Ko(;Ur1qnZxCbFKb>O*IbP)*e>@hy~3OqE8OzHb25@_Kcq}xpHF2xA& zCVw9F9A(A1&|C^&KaL9+x_8Ki&K#4J;IfAPQb6)kXzo!P{V1#2$%jqrHocLemrzUG z3oU#6g-q|FKPnO*>xbDG;V(@6mcEqIZJFu0^dQ zDF8gX(EY;X@*JxyDBC2!n0h>5A3HH}UGwqV#uS)ri&H*Ic&%wPoTiP=WZc3G{-wzc zGk%SqvJtFs?0}lHmwf&&HU9x7h}QVhv3aKqZ%IwIv9i2wOa_Slj{qpPsV<>FNn?x|_cq_S zVpJIbY_QhX8aW9fyQGIU^$wh<$!-Bn2+uQ#c{valQ}b%@dY#Oi=NXI%8AMPI9L8tB zwyFas7JCPa=1a?vsb2llnbfIomB|0%k1H1DUSI;CyJ|-tcJYIgD-u72%2(dhy8$0G zyx=*t9vxn$-+l(d#YAqcBRtP>$|86PgrnfKrf@l5@-C{M`{N_A+vmuo<(GHeJIN?* p9mcHKZ*Thmh>)wSX2@nfT!qJn!a(qkGrVarray(const array &other)=defaultmlx::core::array array(array &&other)=defaultmlx::core::array array(Shape shape, Dtype dtype, std::shared_ptr< Primitive > primitive, std::vector< array > inputs)mlx::core::array - attach_event(Event e) constmlx::core::arrayinline - available enum valuemlx::core::array - begin() constmlx::core::arrayinline - buffer()mlx::core::arrayinline - buffer() constmlx::core::arrayinline - buffer_size() constmlx::core::arrayinline - copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)mlx::core::array - copy_shared_buffer(const array &other)mlx::core::array - data()mlx::core::arrayinline - data() constmlx::core::arrayinline - data_shared_ptr() constmlx::core::arrayinline - data_size() constmlx::core::arrayinline - detach()mlx::core::array - dtype() constmlx::core::arrayinline - end() constmlx::core::arrayinline - eval()mlx::core::array - evaluated enum valuemlx::core::array - event() constmlx::core::arrayinline - flags() constmlx::core::arrayinline - has_primitive() constmlx::core::arrayinline - id() constmlx::core::arrayinline - inputs() constmlx::core::arrayinline - inputs()mlx::core::arrayinline - is_available() constmlx::core::array - is_donatable() constmlx::core::arrayinline - is_tracer() constmlx::core::array - item()mlx::core::array - item() constmlx::core::array - itemsize() constmlx::core::arrayinline - make_arrays(std::vector< Shape > shapes, const std::vector< Dtype > &dtypes, const std::shared_ptr< Primitive > &primitive, const std::vector< array > &inputs)mlx::core::arraystatic - move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)mlx::core::array - move_shared_buffer(array other)mlx::core::array - nbytes() constmlx::core::arrayinline - ndim() constmlx::core::arrayinline - operator=(const array &other) &&=deletemlx::core::array - operator=(array &&other) &&=deletemlx::core::array - operator=(array &&other) &=defaultmlx::core::array - operator=(const array &other) &mlx::core::arrayinline - outputs() constmlx::core::arrayinline - overwrite_descriptor(const array &other)mlx::core::arrayinline - primitive() constmlx::core::arrayinline - primitive_id() constmlx::core::arrayinline - primitive_ptr() constmlx::core::arrayinline - scheduled enum valuemlx::core::array - set_data(allocator::Buffer buffer, Deleter d=allocator::free)mlx::core::array - set_data(allocator::Buffer buffer, size_t data_size, Strides strides, Flags flags, Deleter d=allocator::free)mlx::core::array - set_siblings(std::vector< array > siblings, uint16_t position)mlx::core::arrayinline - set_status(Status s) constmlx::core::arrayinline - set_tracer(bool is_tracer)mlx::core::arrayinline - shape() constmlx::core::arrayinline - shape(int dim) constmlx::core::arrayinline - siblings() constmlx::core::arrayinline - siblings()mlx::core::arrayinline - size() constmlx::core::arrayinline - Status enum namemlx::core::array - status() constmlx::core::arrayinline - strides() constmlx::core::arrayinline - strides(int dim) constmlx::core::arrayinline - unscheduled enum valuemlx::core::array - wait()mlx::core::array - ~array()mlx::core::array + array(allocator::Buffer data, Shape shape, Dtype dtype, Strides strides, size_t data_size, Flags flags, Deleter deleter=allocator::free)mlx::core::arrayexplicit + attach_event(Event e) constmlx::core::arrayinline + available enum valuemlx::core::array + begin() constmlx::core::arrayinline + buffer()mlx::core::arrayinline + buffer() constmlx::core::arrayinline + buffer_size() constmlx::core::arrayinline + copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)mlx::core::array + copy_shared_buffer(const array &other)mlx::core::array + data()mlx::core::arrayinline + data() constmlx::core::arrayinline + data_shared_ptr() constmlx::core::arrayinline + data_size() constmlx::core::arrayinline + detach()mlx::core::array + dtype() constmlx::core::arrayinline + end() constmlx::core::arrayinline + eval()mlx::core::array + evaluated enum valuemlx::core::array + event() constmlx::core::arrayinline + flags() constmlx::core::arrayinline + has_primitive() constmlx::core::arrayinline + id() constmlx::core::arrayinline + inputs() constmlx::core::arrayinline + inputs()mlx::core::arrayinline + is_available() constmlx::core::array + is_donatable() constmlx::core::arrayinline + is_tracer() constmlx::core::array + item()mlx::core::array + item() constmlx::core::array + itemsize() constmlx::core::arrayinline + make_arrays(std::vector< Shape > shapes, const std::vector< Dtype > &dtypes, const std::shared_ptr< Primitive > &primitive, const std::vector< array > &inputs)mlx::core::arraystatic + move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)mlx::core::array + move_shared_buffer(array other)mlx::core::array + nbytes() constmlx::core::arrayinline + ndim() constmlx::core::arrayinline + operator=(const array &other) &&=deletemlx::core::array + operator=(array &&other) &&=deletemlx::core::array + operator=(array &&other) &=defaultmlx::core::array + operator=(const array &other) &mlx::core::arrayinline + outputs() constmlx::core::arrayinline + overwrite_descriptor(const array &other)mlx::core::arrayinline + primitive() constmlx::core::arrayinline + primitive_id() constmlx::core::arrayinline + primitive_ptr() constmlx::core::arrayinline + scheduled enum valuemlx::core::array + set_data(allocator::Buffer buffer, Deleter d=allocator::free)mlx::core::array + set_data(allocator::Buffer buffer, size_t data_size, Strides strides, Flags flags, Deleter d=allocator::free)mlx::core::array + set_siblings(std::vector< array > siblings, uint16_t position)mlx::core::arrayinline + set_status(Status s) constmlx::core::arrayinline + set_tracer(bool is_tracer)mlx::core::arrayinline + shape() constmlx::core::arrayinline + shape(int dim) constmlx::core::arrayinline + siblings() constmlx::core::arrayinline + siblings()mlx::core::arrayinline + size() constmlx::core::arrayinline + Status enum namemlx::core::array + status() constmlx::core::arrayinline + strides() constmlx::core::arrayinline + strides(int dim) constmlx::core::arrayinline + unscheduled enum valuemlx::core::array + wait()mlx::core::array + ~array()mlx::core::array
diff --git a/docs/build/html/classmlx_1_1core_1_1array.html b/docs/build/html/classmlx_1_1core_1_1array.html index 30d31e329..b020815bb 100644 --- a/docs/build/html/classmlx_1_1core_1_1array.html +++ b/docs/build/html/classmlx_1_1core_1_1array.html @@ -219,6 +219,9 @@ Public Member Functions std::uintptr_t primitive_id () const  A unique identifier for an arrays primitive.
  + array (allocator::Buffer data, Shape shape, Dtype dtype, Strides strides, size_t data_size, Flags flags, Deleter deleter=allocator::free) + Build an array from all the info held by the array description.
+  Primitive & primitive () const  The array's primitive.
  @@ -331,7 +334,7 @@ Static Public Member Functions

Constructor & Destructor Documentation

-

◆ array() [1/11]

+

◆ array() [1/12]

@@ -364,7 +367,7 @@ template<typename T>
-

◆ array() [2/11]

+

◆ array() [2/12]

@@ -393,7 +396,7 @@ template<typename T>
-

◆ array() [3/11]

+

◆ array() [3/12]

@@ -429,7 +432,7 @@ template<typename It>
-

◆ array() [4/11]

+

◆ array() [4/12]

@@ -460,7 +463,7 @@ template<typename T>
-

◆ array() [5/11]

+

◆ array() [5/12]

@@ -485,7 +488,7 @@ template<typename T>
-

◆ array() [6/11]

+

◆ array() [6/12]

@@ -514,7 +517,7 @@ template<typename T>
-

◆ array() [7/11]

+

◆ array() [7/12]

@@ -550,7 +553,7 @@ template<typename T>
-

◆ array() [8/11]

+

◆ array() [8/12]

@@ -589,7 +592,7 @@ template<typename T>
-

◆ array() [9/11]

+

◆ array() [9/12]

@@ -614,7 +617,7 @@ template<typename T>
-

◆ array() [10/11]

+

◆ array() [10/12]

@@ -639,7 +642,7 @@ template<typename T>
-

◆ array() [11/11]

+

◆ array() [11/12]

@@ -670,6 +673,63 @@ template<typename T>

The following methods should be used with caution.

They are intended for use by the backend implementation and the API may change.

+
+
+ +

◆ array() [12/12]

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
mlx::core::array::array (allocator::Buffer data,
Shape shape,
Dtype dtype,
Strides strides,
size_t data_size,
Flags flags,
Deleter deleter = allocator::free )
+ 		+explicit
+
+ +

Build an array from all the info held by the array description.

+

Including the buffer, strides, flags.

+
diff --git a/docs/build/html/classmlx_1_1core_1_1array.js b/docs/build/html/classmlx_1_1core_1_1array.js index 3f3d71b56..dc9be6583 100644 --- a/docs/build/html/classmlx_1_1core_1_1array.js +++ b/docs/build/html/classmlx_1_1core_1_1array.js @@ -20,6 +20,7 @@ var classmlx_1_1core_1_1array = [ "array", "classmlx_1_1core_1_1array.html#a297df274e2da5cb884257bbeffd6b187", null ], [ "array", "classmlx_1_1core_1_1array.html#ab6cbccbba66cc54acda4390b19f0397c", null ], [ "array", "classmlx_1_1core_1_1array.html#abc26528271076510822e374d1668a94b", null ], + [ "array", "classmlx_1_1core_1_1array.html#a2476f987ec7a5afb7665d3b3974db0b2", null ], [ "~array", "classmlx_1_1core_1_1array.html#a2f16c1ef8ee248d2fba95520c86dfad2", null ], [ "attach_event", "classmlx_1_1core_1_1array.html#a000c3cfe13cb378bf0523b62816190da", null ], [ "begin", "classmlx_1_1core_1_1array.html#a76b258b169d7d73419ebbf85340fb914", null ], diff --git a/docs/build/html/classmlx_1_1core_1_1metal_1_1_device-members.html b/docs/build/html/classmlx_1_1core_1_1metal_1_1_device-members.html index d5f4b9bac..e67963e7e 100644 --- a/docs/build/html/classmlx_1_1core_1_1metal_1_1_device-members.html +++ b/docs/build/html/classmlx_1_1core_1_1metal_1_1_device-members.html @@ -111,25 +111,24 @@ $(function(){initNavTree('classmlx_1_1core_1_1metal_1_1_device.html',''); initRe add_temporaries(std::vector< array > arrays, int index)mlx::core::metal::Device add_temporary(array arr, int index)mlx::core::metal::Device argument_encoder(const std::vector< MTL::ArgumentDescriptor * > &arg_descs) constmlx::core::metal::Device - commit_command_buffer(int index)mlx::core::metal::Device - Device()mlx::core::metal::Device - Device(const Device &)=deletemlx::core::metal::Device - end_encoding(int index)mlx::core::metal::Device - get_architecture()mlx::core::metal::Deviceinline - get_command_buffer(int index)mlx::core::metal::Device - get_command_buffer_ops(int index)mlx::core::metal::Device + command_buffer_needs_commit(int index)mlx::core::metal::Device + commit_command_buffer(int index)mlx::core::metal::Device + Device()mlx::core::metal::Device + Device(const Device &)=deletemlx::core::metal::Device + end_encoding(int index)mlx::core::metal::Device + get_architecture()mlx::core::metal::Deviceinline + get_command_buffer(int index)mlx::core::metal::Device get_command_encoder(int index)mlx::core::metal::Device get_kernel(const std::string &base_name, MTL::Library *mtl_lib, const std::string &hash_name="", const MTLFCList &func_consts={}, const std::vector< MTL::Function * > &linked_functions={})mlx::core::metal::Device get_kernel(const std::string &base_name, const std::string &lib_name="mlx", const std::string &hash_name="", const MTLFCList &func_consts={}, const std::vector< MTL::Function * > &linked_functions={})mlx::core::metal::Device get_library(const std::string &name, const std::function< std::string(void)> &builder)mlx::core::metal::Device - increment_command_buffer_ops(int index)mlx::core::metal::Device - mtl_device()mlx::core::metal::Deviceinline - new_queue(int index)mlx::core::metal::Device - operator=(const Device &)=deletemlx::core::metal::Device - register_library(const std::string &lib_name, const std::string &lib_path)mlx::core::metal::Device - register_library(const std::string &lib_name)mlx::core::metal::Deviceinline - set_residency_set(const MTL::ResidencySet *residency_set)mlx::core::metal::Device - ~Device()mlx::core::metal::Device + mtl_device()mlx::core::metal::Deviceinline + new_queue(int index)mlx::core::metal::Device + operator=(const Device &)=deletemlx::core::metal::Device + register_library(const std::string &lib_name, const std::string &lib_path)mlx::core::metal::Device + register_library(const std::string &lib_name)mlx::core::metal::Deviceinline + set_residency_set(const MTL::ResidencySet *residency_set)mlx::core::metal::Device + ~Device()mlx::core::metal::Device
diff --git a/docs/build/html/classmlx_1_1core_1_1metal_1_1_device.html b/docs/build/html/classmlx_1_1core_1_1metal_1_1_device.html index 35a3b1ff2..989e76cca 100644 --- a/docs/build/html/classmlx_1_1core_1_1metal_1_1_device.html +++ b/docs/build/html/classmlx_1_1core_1_1metal_1_1_device.html @@ -129,10 +129,8 @@ Public Member Functions   MTL::CommandBuffer * get_command_buffer (int index)   -int get_command_buffer_ops (int index) -  -void increment_command_buffer_ops (int index) -  +bool command_buffer_needs_commit (int index) +  void commit_command_buffer (int index)   CommandEncoder & get_command_encoder (int index) @@ -276,6 +274,23 @@ Public Member Functions
+
+
+ +

◆ command_buffer_needs_commit()

+ +
+
+ + + + + + + +
bool mlx::core::metal::Device::command_buffer_needs_commit (int index)
+
+
@@ -352,23 +367,6 @@ Public Member Functions
-
-
- -

◆ get_command_buffer_ops()

- -
-
- - - - - - - -
int mlx::core::metal::Device::get_command_buffer_ops (int index)
-
-
@@ -479,23 +477,6 @@ Public Member Functions
-
-
- -

◆ increment_command_buffer_ops()

- -
-
- - - - - - - -
void mlx::core::metal::Device::increment_command_buffer_ops (int index)
-
-
diff --git a/docs/build/html/classmlx_1_1core_1_1metal_1_1_device.js b/docs/build/html/classmlx_1_1core_1_1metal_1_1_device.js index 11e5d93df..c4248d1b9 100644 --- a/docs/build/html/classmlx_1_1core_1_1metal_1_1_device.js +++ b/docs/build/html/classmlx_1_1core_1_1metal_1_1_device.js @@ -6,16 +6,15 @@ var classmlx_1_1core_1_1metal_1_1_device = [ "add_temporaries", "classmlx_1_1core_1_1metal_1_1_device.html#a72ad17c96fc6ce825bc77f0bed657901", null ], [ "add_temporary", "classmlx_1_1core_1_1metal_1_1_device.html#acb90010af0cffe27fd8cc6c253d3a576", null ], [ "argument_encoder", "classmlx_1_1core_1_1metal_1_1_device.html#a6e33e2b1287324fb4a6575e0da5e5881", null ], + [ "command_buffer_needs_commit", "classmlx_1_1core_1_1metal_1_1_device.html#a2580a395419fa6735e8ca5a67495700e", null ], [ "commit_command_buffer", "classmlx_1_1core_1_1metal_1_1_device.html#a95248f1387824067fd4fed23ace5ac0c", null ], [ "end_encoding", "classmlx_1_1core_1_1metal_1_1_device.html#a60689f97347811b27e8c5ca23e0372bf", null ], [ "get_architecture", "classmlx_1_1core_1_1metal_1_1_device.html#a65f64dd8bafdc704d871fc5be5e7bc0b", null ], [ "get_command_buffer", "classmlx_1_1core_1_1metal_1_1_device.html#a5fe3970fbe92ccc55fce4241ffbe5210", null ], - [ "get_command_buffer_ops", "classmlx_1_1core_1_1metal_1_1_device.html#a064e1cb6a16de7a0619f6447622350f8", null ], [ "get_command_encoder", "classmlx_1_1core_1_1metal_1_1_device.html#affa682ef612def4890f5152f81ffb7e6", null ], [ "get_kernel", "classmlx_1_1core_1_1metal_1_1_device.html#afa0cac9d800c21a8a7f6cb224256abaf", null ], [ "get_kernel", "classmlx_1_1core_1_1metal_1_1_device.html#a6810c4dcbcfbf93fc51d42aa5ff0fc3a", null ], [ "get_library", "classmlx_1_1core_1_1metal_1_1_device.html#a75ed55e73baf48013028796518723ff0", null ], - [ "increment_command_buffer_ops", "classmlx_1_1core_1_1metal_1_1_device.html#a7a33d4d601423a3d3c23d5ad7072abb6", null ], [ "mtl_device", "classmlx_1_1core_1_1metal_1_1_device.html#a31dba377f2be44a746db10d1b9367653", null ], [ "new_queue", "classmlx_1_1core_1_1metal_1_1_device.html#a8135ae2a8c1e6f3861e84d4e60c28b67", null ], [ "operator=", "classmlx_1_1core_1_1metal_1_1_device.html#ad1d6382fd18a46b1906e1b43e0bd2e73", null ], diff --git a/docs/build/html/common_2binary_8h_source.html b/docs/build/html/common_2binary_8h_source.html index 0abe8b8b9..50a81be57 100644 --- a/docs/build/html/common_2binary_8h_source.html +++ b/docs/build/html/common_2binary_8h_source.html @@ -237,7 +237,7 @@ $(function(){initNavTree('common_2binary_8h_source.html',''); initResizable(true
mlx::core::array
Definition array.h:24
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:306
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
mlx::core::array::size
size_t size() const
The number of elements in the array.
Definition array.h:88
@@ -245,7 +245,7 @@ $(function(){initNavTree('common_2binary_8h_source.html',''); initResizable(true
mlx::core::array::move_shared_buffer
void move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:320
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
mlx::core::allocator::malloc_or_wait
Buffer malloc_or_wait(size_t size)
mlx::core
Definition allocator.h:7
mlx::core::get_binary_op_type
BinaryOpType get_binary_op_type(const array &a, const array &b)
Definition binary.h:19
diff --git a/docs/build/html/common_2hadamard_8h_source.html b/docs/build/html/common_2hadamard_8h_source.html index 8ed8b7365..5c70f5ba9 100644 --- a/docs/build/html/common_2hadamard_8h_source.html +++ b/docs/build/html/common_2hadamard_8h_source.html @@ -220,7 +220,7 @@ $(function(){initNavTree('common_2hadamard_8h_source.html',''); initResizable(tr
mlx::core::hadamard_matrices
const std::map< int, std::string_view > hadamard_matrices()
Definition hadamard.h:81
mlx::core::h20
constexpr std::string_view h20
Definition hadamard.h:27
mlx::core::h28
constexpr std::string_view h28
Definition hadamard.h:50
-
mlx::core::is_power_of_2
bool is_power_of_2(int n)
Definition utils.h:104
+
mlx::core::is_power_of_2
bool is_power_of_2(int n)
Definition utils.h:105
diff --git a/docs/build/html/common_2ternary_8h_source.html b/docs/build/html/common_2ternary_8h_source.html index e45fb9785..eabc69f86 100644 --- a/docs/build/html/common_2ternary_8h_source.html +++ b/docs/build/html/common_2ternary_8h_source.html @@ -193,14 +193,14 @@ $(function(){initNavTree('common_2ternary_8h_source.html',''); initResizable(tru
mlx::core::array
Definition array.h:24
-
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:306
+
mlx::core::array::flags
const Flags & flags() const
Get the Flags bit-field.
Definition array.h:318
mlx::core::array::strides
const Strides & strides() const
The strides of the array.
Definition array.h:117
mlx::core::array::nbytes
size_t nbytes() const
The number of bytes in the array.
Definition array.h:93
mlx::core::array::copy_shared_buffer
void copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::move_shared_buffer
void move_shared_buffer(array other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
mlx::core::array::itemsize
size_t itemsize() const
The size of the array's datatype in bytes.
Definition array.h:83
mlx::core::array::set_data
void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
-
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:320
+
mlx::core::array::data_size
size_t data_size() const
The size (in elements) of the underlying buffer the array points to.
Definition array.h:332
mlx::core::allocator::malloc_or_wait
Buffer malloc_or_wait(size_t size)
mlx::core
Definition allocator.h:7
mlx::core::BinaryOpType::General
@ General
Definition binary.h:16
diff --git a/docs/build/html/compile_8h.html b/docs/build/html/compile_8h.html index 11fcad64b..76a30a9dc 100644 --- a/docs/build/html/compile_8h.html +++ b/docs/build/html/compile_8h.html @@ -134,8 +134,8 @@ Functions std::function< std::vector< array >(const std::vector< array > &)> mlx::core::compile (std::function< std::vector< array >(const std::vector< array > &)> fun, bool shapeless=false)  Compile takes a function and returns a compiled function.
  -std::function< std::vector< array >(const std::vector< array > &)> mlx::core::compile (std::vector< array >(fun)(const std::vector< array > &), bool shapeless=false) -  +std::function< std::vector< array >(const std::vector< array > &)> mlx::core::compile (std::vector< array >(*fun)(const std::vector< array > &), bool shapeless=false) +  template<typename F> std::function< std::vector< array >(const std::vector< array > &)> mlx::core::compile (F &&f, bool shapeless=false)   diff --git a/docs/build/html/compile_8h.js b/docs/build/html/compile_8h.js index a61e7f82b..60f17ecef 100644 --- a/docs/build/html/compile_8h.js +++ b/docs/build/html/compile_8h.js @@ -8,7 +8,7 @@ var compile_8h = ] ], [ "mlx::core::compile", "namespacemlx_1_1core.html#ace67713d269595f5f2265e46728a6f9c", null ], [ "mlx::core::compile", "namespacemlx_1_1core.html#a55933c6665de9f81059120d6b0de1c87", null ], - [ "mlx::core::compile", "namespacemlx_1_1core.html#a56de948c2dffbf35c88035bc1561db53", null ], + [ "mlx::core::compile", "namespacemlx_1_1core.html#abf57076f6d2351ba9f1e0cbe478f8afa", null ], [ "mlx::core::disable_compile", "namespacemlx_1_1core.html#a5f5fea955057bb3842b271b037909e66", null ], [ "mlx::core::enable_compile", "namespacemlx_1_1core.html#a1983a2466bff3bae4d23cf34bd0946c9", null ], [ "mlx::core::set_compile_mode", "namespacemlx_1_1core.html#a49445a55f976c4397f25ea18e1e92bef", null ] diff --git a/docs/build/html/compile_8h_source.html b/docs/build/html/compile_8h_source.html index e5fed8202..e0ef69c80 100644 --- a/docs/build/html/compile_8h_source.html +++ b/docs/build/html/compile_8h_source.html @@ -119,8 +119,8 @@ $(function(){initNavTree('compile_8h_source.html',''); initResizable(true); });
13 std::function<std::vector<array>(const std::vector<array>&)> fun,
14 bool shapeless = false);
15
-
16std::function<std::vector<array>(const std::vector<array>&)> compile(
-
17 std::vector<array>(fun)(const std::vector<array>&),
+
16std::function<std::vector<array>(const std::vector<array>&)> compile(
+
17 std::vector<array> (*fun)(const std::vector<array>&),
18 bool shapeless = false);
19
20// Convert capture-less lambdas to function pointers.
diff --git a/docs/build/html/compiled_8h_source.html b/docs/build/html/compiled_8h_source.html index 857e5edfb..e279c1183 100644 --- a/docs/build/html/compiled_8h_source.html +++ b/docs/build/html/compiled_8h_source.html @@ -185,11 +185,11 @@ $(function(){initNavTree('compiled_8h_source.html',''); initResizable(true); });
68} // namespace mlx::core
mlx::core::AsType
Definition primitives.h:392
-
mlx::core::Broadcast
Definition primitives.h:528
+
mlx::core::Broadcast
Definition primitives.h:541
mlx::core::Primitive
Definition primitives.h:48
mlx::core::array
Definition array.h:24
mlx::core::array::ndim
size_t ndim() const
The number of dimensions of the array.
Definition array.h:98
-
mlx::core::array::item
T item()
Get the value from a scalar array.
Definition array.h:539
+
mlx::core::array::item
T item()
Get the value from a scalar array.
Definition array.h:551
mlx::core::array::dtype
Dtype dtype() const
Get the arrays data type.
Definition array.h:131
mlx::core::contiguous
array contiguous(const array &a, bool allow_col_major=false, StreamOrDevice s={})
mlx::core
Definition allocator.h:7
diff --git a/docs/build/html/cpp/ops.html b/docs/build/html/cpp/ops.html index 20841b0cb..2cb1c169b 100644 --- a/docs/build/html/cpp/ops.html +++ b/docs/build/html/cpp/ops.html @@ -8,7 +8,7 @@ - Operations — MLX 0.22.1 documentation + Operations — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
@@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
    • -
    73
    -
    74} // namespace mlx::core
    +
    76
    +
    77} // namespace mlx::core
    mlx::core::array
    Definition array.h:24
    @@ -190,20 +193,21 @@ $(function(){initNavTree('cpu_2arange_8h_source.html',''); initResizable(true);
    mlx::core::array::set_data
    void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
    mlx::core::allocator::malloc_or_wait
    Buffer malloc_or_wait(size_t size)
    mlx::core
    Definition allocator.h:7
    -
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:67
    -
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:72
    -
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:70
    +
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:68
    +
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:73
    +
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:71
    mlx::core::arange
    void arange(const std::vector< array > &inputs, array &out, double start, double step)
    Definition arange.h:24
    -
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:81
    -
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:76
    -
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:80
    -
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:75
    -
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:74
    -
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:77
    -
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:69
    -
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:79
    -
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:71
    -
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:82
    +
    mlx::core::float64
    constexpr Dtype float64
    Definition dtype.h:82
    +
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:83
    +
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:77
    +
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:81
    +
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:76
    +
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:75
    +
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:78
    +
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:70
    +
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:80
    +
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:72
    +
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:84
    diff --git a/docs/build/html/cpu_2binary_8h_source.html b/docs/build/html/cpu_2binary_8h_source.html index f348da1cd..762cbc7e3 100644 --- a/docs/build/html/cpu_2binary_8h_source.html +++ b/docs/build/html/cpu_2binary_8h_source.html @@ -486,58 +486,62 @@ $(function(){initNavTree('cpu_2binary_8h_source.html',''); initResizable(true);
    358 case float32:
    359 binary_op<float>(a, b, out, op);
    360 break;
    -
    361 case bfloat16:
    -
    362 binary_op<bfloat16_t>(a, b, out, op);
    +
    361 case float64:
    +
    362 binary_op<double>(a, b, out, op);
    363 break;
    -
    364 case complex64:
    -
    365 binary_op<complex64_t>(a, b, out, op);
    +
    364 case bfloat16:
    +
    365 binary_op<bfloat16_t>(a, b, out, op);
    366 break;
    -
    367 }
    -
    368}
    +
    367 case complex64:
    +
    368 binary_op<complex64_t>(a, b, out, op);
    +
    369 break;
    +
    370 }
    +
    371}
    -
    369
    -
    370} // namespace mlx::core
    +
    372
    +
    373} // namespace mlx::core
    mlx::core::array
    Definition array.h:24
    mlx::core::array::shape
    const Shape & shape() const
    The shape of the array as a vector of integers.
    Definition array.h:103
    mlx::core::array::size
    size_t size() const
    The number of elements in the array.
    Definition array.h:88
    -
    mlx::core::array::data
    T * data()
    Definition array.h:342
    +
    mlx::core::array::data
    T * data()
    Definition array.h:354
    mlx::core::array::dtype
    Dtype dtype() const
    Get the arrays data type.
    Definition array.h:131
    -
    mlx::core::array::data_size
    size_t data_size() const
    The size (in elements) of the underlying buffer the array points to.
    Definition array.h:320
    +
    mlx::core::array::data_size
    size_t data_size() const
    The size (in elements) of the underlying buffer the array points to.
    Definition array.h:332
    -
    mlx::core::simd::load
    Simd< T, N > load(const T *x)
    Definition base_simd.h:27
    -
    mlx::core::simd::max_size
    static constexpr int max_size
    Definition base_simd.h:13
    -
    mlx::core::simd::store
    void store(T *dst, Simd< T, N > x)
    Definition base_simd.h:32
    +
    mlx::core::simd::load
    Simd< T, N > load(const T *x)
    Definition base_simd.h:28
    +
    mlx::core::simd::max_size
    static constexpr int max_size
    Definition base_simd.h:14
    +
    mlx::core::simd::store
    void store(T *dst, Simd< T, N > x)
    Definition base_simd.h:33
    mlx::core
    Definition allocator.h:7
    -
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:67
    -
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:72
    +
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:68
    +
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:73
    mlx::core::get_binary_op_type
    BinaryOpType get_binary_op_type(const array &a, const array &b)
    Definition binary.h:19
    -
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:70
    +
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:71
    +
    mlx::core::float64
    constexpr Dtype float64
    Definition dtype.h:82
    mlx::core::collapse_contiguous_dims
    std::tuple< Shape, std::vector< Strides > > collapse_contiguous_dims(const Shape &shape, const std::vector< Strides > &strides, int64_t size_cap=std::numeric_limits< int32_t >::max())
    -
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:81
    +
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:83
    mlx::core::BinaryOpType::General
    @ General
    Definition binary.h:16
    mlx::core::BinaryOpType::VectorVector
    @ VectorVector
    Definition binary.h:15
    mlx::core::BinaryOpType::ScalarScalar
    @ ScalarScalar
    Definition binary.h:12
    mlx::core::BinaryOpType::VectorScalar
    @ VectorScalar
    Definition binary.h:14
    mlx::core::BinaryOpType::ScalarVector
    @ ScalarVector
    Definition binary.h:13
    -
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:76
    +
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:77
    mlx::core::binary_op_dispatch_dims
    void binary_op_dispatch_dims(const array &a, const array &b, array &out, Op op, int dim, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides)
    Definition binary.h:122
    -
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:80
    +
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:81
    mlx::core::Shape
    std::vector< ShapeElem > Shape
    Definition array.h:21
    mlx::core::set_binary_op_output_data
    void set_binary_op_output_data(const array &a, const array &b, array &out, BinaryOpType bopt, bool donate_with_move=false)
    Definition binary.h:37
    -
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:75
    +
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:76
    mlx::core::Strides
    std::vector< int64_t > Strides
    Definition array.h:22
    mlx::core::binary_op_dims
    void binary_op_dims(const T *a, const T *b, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis)
    Definition binary.h:89
    -
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:74
    -
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:77
    -
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:69
    +
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:75
    +
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:78
    +
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:70
    mlx::core::binary_op
    void binary_op(const array &a, const array &b, array &out, Op op)
    Definition binary.h:194
    -
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:79
    -
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:71
    +
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:80
    +
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:72
    mlx::core::binary
    void binary(const array &a, const array &b, array &out, Op op)
    Definition binary.h:326
    -
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:82
    +
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:84
    mlx::core::ContiguousIterator
    Definition utils.h:73
    mlx::core::ContiguousIterator::loc
    int64_t loc
    Definition utils.h:126
    diff --git a/docs/build/html/cpu_2binary__ops_8h_source.html b/docs/build/html/cpu_2binary__ops_8h_source.html index 0273cb1ba..b04054470 100644 --- a/docs/build/html/cpu_2binary__ops_8h_source.html +++ b/docs/build/html/cpu_2binary__ops_8h_source.html @@ -232,16 +232,16 @@ $(function(){initNavTree('cpu_2binary__ops_8h_source.html',''); initResizable(tr
    BINARY_SINGLE
    #define BINARY_SINGLE()
    Definition binary_ops.h:11
    mlx::core::detail
    Definition binary_ops.h:7
    mlx::core::simd
    Definition accelerate_fp16_simd.h:9
    -
    mlx::core::simd::isnan
    Simd< bool, N > isnan(Simd< T, N > v)
    Definition accelerate_simd.h:141
    -
    mlx::core::simd::minimum
    Simd< T, N > minimum(Simd< T, N > a, Simd< T, N > b)
    Definition accelerate_simd.h:210
    +
    mlx::core::simd::isnan
    Simd< bool, N > isnan(Simd< T, N > v)
    Definition accelerate_simd.h:146
    +
    mlx::core::simd::minimum
    Simd< T, N > minimum(Simd< T, N > a, Simd< T, N > b)
    Definition accelerate_simd.h:215
    mlx::core::simd::pow
    Simd< float16_t, N > pow(Simd< float16_t, N > x, Simd< float16_t, N > y)
    Definition accelerate_fp16_simd.h:54
    mlx::core::simd::atan2
    Simd< float16_t, N > atan2(Simd< float16_t, N > x, Simd< float16_t, N > y)
    Definition accelerate_fp16_simd.h:52
    mlx::core::simd::inf
    constexpr float inf
    Definition math.h:9
    -
    mlx::core::simd::maximum
    Simd< T, N > maximum(Simd< T, N > a, Simd< T, N > b)
    Definition accelerate_simd.h:204
    +
    mlx::core::simd::maximum
    Simd< T, N > maximum(Simd< T, N > a, Simd< T, N > b)
    Definition accelerate_simd.h:209
    mlx::core::simd::exp
    Simd< T, N > exp(Simd< T, N > in)
    Compute exp(x) in an optimizer friendly way as follows:
    Definition math.h:28
    mlx::core::simd::remainder
    Simd< float16_t, N > remainder(Simd< float16_t, N > x, Simd< float16_t, N > y)
    Definition accelerate_fp16_simd.h:53
    mlx::core::simd::log1p
    Simd< float16_t, N > log1p(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:40
    -
    mlx::core::simd::select
    Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
    Definition accelerate_simd.h:231
    +
    mlx::core::simd::select
    Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
    Definition accelerate_simd.h:236
    mlx::core::detail::Add
    Definition binary_ops.h:26
    mlx::core::detail::ArcTan2
    Definition binary_ops.h:27
    diff --git a/docs/build/html/cpu_2binary__two_8h_source.html b/docs/build/html/cpu_2binary__two_8h_source.html index f10f73e7b..f3ddd5360 100644 --- a/docs/build/html/cpu_2binary__two_8h_source.html +++ b/docs/build/html/cpu_2binary__two_8h_source.html @@ -312,49 +312,53 @@ $(function(){initNavTree('cpu_2binary__two_8h_source.html',''); initResizable(tr
    205 case float32:
    206 binary_op<float>(a, b, outputs, op);
    207 break;
    -
    208 case bfloat16:
    -
    209 binary_op<bfloat16_t>(a, b, outputs, op);
    +
    208 case float64:
    +
    209 binary_op<double>(a, b, outputs, op);
    210 break;
    -
    211 case complex64:
    -
    212 binary_op<complex64_t>(a, b, outputs, op);
    +
    211 case bfloat16:
    +
    212 binary_op<bfloat16_t>(a, b, outputs, op);
    213 break;
    -
    214 }
    -
    215}
    -
    216
    -
    217} // namespace
    -
    218
    -
    219} // namespace mlx::core
    +
    214 case complex64:
    +
    215 binary_op<complex64_t>(a, b, outputs, op);
    +
    216 break;
    +
    217 }
    +
    218}
    +
    219
    +
    220} // namespace
    +
    221
    +
    222} // namespace mlx::core
    mlx::core::array
    Definition array.h:24
    mlx::core::simd::N
    constexpr int N
    Definition neon_fp16_simd.h:9
    mlx::core
    Definition allocator.h:7
    -
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:67
    -
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:72
    +
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:68
    +
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:73
    mlx::core::get_binary_op_type
    BinaryOpType get_binary_op_type(const array &a, const array &b)
    Definition binary.h:19
    -
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:70
    +
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:71
    +
    mlx::core::float64
    constexpr Dtype float64
    Definition dtype.h:82
    mlx::core::collapse_contiguous_dims
    std::tuple< Shape, std::vector< Strides > > collapse_contiguous_dims(const Shape &shape, const std::vector< Strides > &strides, int64_t size_cap=std::numeric_limits< int32_t >::max())
    -
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:81
    +
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:83
    mlx::core::BinaryOpType::General
    @ General
    Definition binary.h:16
    mlx::core::BinaryOpType::ScalarScalar
    @ ScalarScalar
    Definition binary.h:12
    mlx::core::BinaryOpType::VectorScalar
    @ VectorScalar
    Definition binary.h:14
    mlx::core::BinaryOpType::ScalarVector
    @ ScalarVector
    Definition binary.h:13
    -
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:76
    +
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:77
    mlx::core::binary_op_dispatch_dims
    void binary_op_dispatch_dims(const array &a, const array &b, array &out, Op op, int dim, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides)
    Definition binary.h:122
    -
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:80
    +
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:81
    mlx::core::Shape
    std::vector< ShapeElem > Shape
    Definition array.h:21
    mlx::core::set_binary_op_output_data
    void set_binary_op_output_data(const array &a, const array &b, array &out, BinaryOpType bopt, bool donate_with_move=false)
    Definition binary.h:37
    -
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:75
    +
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:76
    mlx::core::Strides
    std::vector< int64_t > Strides
    Definition array.h:22
    mlx::core::binary_op_dims
    void binary_op_dims(const T *a, const T *b, U *out, Op op, const Shape &shape, const Strides &a_strides, const Strides &b_strides, const Strides &out_strides, int axis)
    Definition binary.h:89
    -
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:74
    -
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:77
    -
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:69
    +
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:75
    +
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:78
    +
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:70
    mlx::core::binary_op
    void binary_op(const array &a, const array &b, array &out, Op op)
    Definition binary.h:194
    -
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:79
    -
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:71
    +
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:80
    +
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:72
    mlx::core::binary
    void binary(const array &a, const array &b, array &out, Op op)
    Definition binary.h:326
    -
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:82
    +
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:84
    mlx::core::ContiguousIterator
    Definition utils.h:73
    diff --git a/docs/build/html/cpu_2ternary_8h_source.html b/docs/build/html/cpu_2ternary_8h_source.html index 4f1832834..40361d521 100644 --- a/docs/build/html/cpu_2ternary_8h_source.html +++ b/docs/build/html/cpu_2ternary_8h_source.html @@ -274,7 +274,7 @@ $(function(){initNavTree('cpu_2ternary_8h_source.html',''); initResizable(true);
    mlx::core::array
    Definition array.h:24
    mlx::core::array::shape
    const Shape & shape() const
    The shape of the array as a vector of integers.
    Definition array.h:103
    mlx::core::array::size
    size_t size() const
    The number of elements in the array.
    Definition array.h:88
    -
    mlx::core::array::data
    T * data()
    Definition array.h:342
    +
    mlx::core::array::data
    T * data()
    Definition array.h:354
    mlx::core
    Definition allocator.h:7
    mlx::core::collapse_contiguous_dims
    std::tuple< Shape, std::vector< Strides > > collapse_contiguous_dims(const Shape &shape, const std::vector< Strides > &strides, int64_t size_cap=std::numeric_limits< int32_t >::max())
    diff --git a/docs/build/html/cpu_2unary_8h.html b/docs/build/html/cpu_2unary_8h.html index 8d5653fae..d797ec193 100644 --- a/docs/build/html/cpu_2unary_8h.html +++ b/docs/build/html/cpu_2unary_8h.html @@ -139,6 +139,9 @@ Functions template<typename Op> void mlx::core::unary_fp (const array &a, array &out, Op op)   +template<typename Op> +void mlx::core::unary_int (const array &a, array &out, Op op) +  diff --git a/docs/build/html/cpu_2unary_8h.js b/docs/build/html/cpu_2unary_8h.js index a2741a1fd..fdc54690d 100644 --- a/docs/build/html/cpu_2unary_8h.js +++ b/docs/build/html/cpu_2unary_8h.js @@ -3,6 +3,7 @@ var cpu_2unary_8h = [ "mlx::core::set_unary_output_data", "namespacemlx_1_1core.html#a4c6a4241bfcdd7bbf30d0e521b79e5a3", null ], [ "mlx::core::unary", "namespacemlx_1_1core.html#a6c8fdd03ef891d7f47804bf02e9a8507", null ], [ "mlx::core::unary_fp", "namespacemlx_1_1core.html#a76a2cb4634f5fd6970a8c3b3753d7a4a", null ], + [ "mlx::core::unary_int", "namespacemlx_1_1core.html#a078859db0d66ff77f97af6dc9764e8eb", null ], [ "mlx::core::unary_op", "namespacemlx_1_1core.html#ae20f207ad1ed3badc17cecf08f118b5e", null ], [ "mlx::core::unary_op", "namespacemlx_1_1core.html#a27f00519f9756896734fd4d47fec0625", null ] ]; \ No newline at end of file diff --git a/docs/build/html/cpu_2unary_8h_source.html b/docs/build/html/cpu_2unary_8h_source.html index 3437a7e9b..c7dcf23fb 100644 --- a/docs/build/html/cpu_2unary_8h_source.html +++ b/docs/build/html/cpu_2unary_8h_source.html @@ -218,80 +218,124 @@ $(function(){initNavTree('cpu_2unary_8h_source.html',''); initResizable(true); }
    104 case float32:
    105 unary_op<float>(a, out, op);
    106 break;
    -
    107 case bfloat16:
    -
    108 unary_op<bfloat16_t>(a, out, op);
    +
    107 case float64:
    +
    108 unary_op<double>(a, out, op);
    109 break;
    -
    110 case complex64:
    -
    111 unary_op<complex64_t>(a, out, op);
    +
    110 case bfloat16:
    +
    111 unary_op<bfloat16_t>(a, out, op);
    112 break;
    -
    113 }
    -
    114}
    +
    113 case complex64:
    +
    114 unary_op<complex64_t>(a, out, op);
    +
    115 break;
    +
    116 }
    +
    117}
    -
    115
    -
    116template <typename Op>
    -
    -
    117void unary_fp(const array& a, array& out, Op op) {
    -
    118 switch (out.dtype()) {
    -
    119 case bfloat16:
    -
    120 unary_op<bfloat16_t>(a, out, op);
    -
    121 break;
    -
    122 case float16:
    -
    123 unary_op<float16_t>(a, out, op);
    +
    118
    +
    119template <typename Op>
    +
    +
    120void unary_fp(const array& a, array& out, Op op) {
    +
    121 switch (out.dtype()) {
    +
    122 case bfloat16:
    +
    123 unary_op<bfloat16_t>(a, out, op);
    124 break;
    -
    125 case float32:
    -
    126 unary_op<float>(a, out, op);
    +
    125 case float16:
    +
    126 unary_op<float16_t>(a, out, op);
    127 break;
    -
    128 case complex64:
    -
    129 unary_op<complex64_t>(a, out, op);
    +
    128 case float32:
    +
    129 unary_op<float>(a, out, op);
    130 break;
    -
    131 default:
    -
    132 std::ostringstream err;
    -
    133 err << "[unary_fp] Does not support " << out.dtype();
    -
    134 throw std::runtime_error(err.str());
    -
    135 }
    -
    136}
    +
    131 case float64:
    +
    132 unary_op<double>(a, out, op);
    +
    133 break;
    +
    134 case complex64:
    +
    135 unary_op<complex64_t>(a, out, op);
    +
    136 break;
    +
    137 default:
    +
    138 std::ostringstream err;
    +
    139 err << "[unary_fp] Does not support " << out.dtype();
    +
    140 throw std::runtime_error(err.str());
    +
    141 }
    +
    142}
    -
    137
    -
    138} // namespace mlx::core
    +
    143
    +
    144template <typename Op>
    +
    +
    145void unary_int(const array& a, array& out, Op op) {
    +
    146 switch (out.dtype()) {
    +
    147 case uint8:
    +
    148 unary_op<uint8_t>(a, out, op);
    +
    149 break;
    +
    150 case uint16:
    +
    151 unary_op<uint16_t>(a, out, op);
    +
    152 break;
    +
    153 case uint32:
    +
    154 unary_op<uint32_t>(a, out, op);
    +
    155 break;
    +
    156 case uint64:
    +
    157 unary_op<uint64_t>(a, out, op);
    +
    158 break;
    +
    159 case int8:
    +
    160 unary_op<int8_t>(a, out, op);
    +
    161 break;
    +
    162 case int16:
    +
    163 unary_op<int16_t>(a, out, op);
    +
    164 break;
    +
    165 case int32:
    +
    166 unary_op<int32_t>(a, out, op);
    +
    167 break;
    +
    168 case int64:
    +
    169 unary_op<int64_t>(a, out, op);
    +
    170 break;
    +
    171 default:
    +
    172 std::ostringstream err;
    +
    173 err << "[unary_int] Does not support " << out.dtype();
    +
    174 throw std::runtime_error(err.str());
    +
    175 }
    +
    176}
    +
    +
    177
    +
    178} // namespace mlx::core
    mlx::core::array
    Definition array.h:24
    -
    mlx::core::array::flags
    const Flags & flags() const
    Get the Flags bit-field.
    Definition array.h:306
    +
    mlx::core::array::flags
    const Flags & flags() const
    Get the Flags bit-field.
    Definition array.h:318
    mlx::core::array::shape
    const Shape & shape() const
    The shape of the array as a vector of integers.
    Definition array.h:103
    mlx::core::array::strides
    const Strides & strides() const
    The strides of the array.
    Definition array.h:117
    mlx::core::array::nbytes
    size_t nbytes() const
    The number of bytes in the array.
    Definition array.h:93
    mlx::core::array::ndim
    size_t ndim() const
    The number of dimensions of the array.
    Definition array.h:98
    mlx::core::array::size
    size_t size() const
    The number of elements in the array.
    Definition array.h:88
    -
    mlx::core::array::data
    T * data()
    Definition array.h:342
    +
    mlx::core::array::data
    T * data()
    Definition array.h:354
    mlx::core::array::copy_shared_buffer
    void copy_shared_buffer(const array &other, const Strides &strides, Flags flags, size_t data_size, size_t offset=0)
    mlx::core::array::dtype
    Dtype dtype() const
    Get the arrays data type.
    Definition array.h:131
    mlx::core::array::itemsize
    size_t itemsize() const
    The size of the array's datatype in bytes.
    Definition array.h:83
    mlx::core::array::set_data
    void set_data(allocator::Buffer buffer, Deleter d=allocator::free)
    -
    mlx::core::array::data_size
    size_t data_size() const
    The size (in elements) of the underlying buffer the array points to.
    Definition array.h:320
    +
    mlx::core::array::data_size
    size_t data_size() const
    The size (in elements) of the underlying buffer the array points to.
    Definition array.h:332
    mlx::core::allocator::malloc_or_wait
    Buffer malloc_or_wait(size_t size)
    -
    mlx::core::simd::load
    Simd< T, N > load(const T *x)
    Definition base_simd.h:27
    -
    mlx::core::simd::max_size
    static constexpr int max_size
    Definition base_simd.h:13
    -
    mlx::core::simd::store
    void store(T *dst, Simd< T, N > x)
    Definition base_simd.h:32
    +
    mlx::core::simd::load
    Simd< T, N > load(const T *x)
    Definition base_simd.h:28
    +
    mlx::core::simd::max_size
    static constexpr int max_size
    Definition base_simd.h:14
    +
    mlx::core::simd::store
    void store(T *dst, Simd< T, N > x)
    Definition base_simd.h:33
    mlx::core
    Definition allocator.h:7
    -
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:67
    -
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:72
    +
    mlx::core::unary_int
    void unary_int(const array &a, array &out, Op op)
    Definition unary.h:145
    +
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:68
    +
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:73
    mlx::core::unary_op
    void unary_op(const T *a, U *out, Op op, size_t shape, size_t stride)
    Definition unary.h:27
    -
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:70
    +
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:71
    +
    mlx::core::float64
    constexpr Dtype float64
    Definition dtype.h:82
    mlx::core::set_unary_output_data
    void set_unary_output_data(const array &in, array &out)
    Definition unary.h:13
    -
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:81
    -
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:76
    -
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:80
    +
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:83
    +
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:77
    +
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:81
    mlx::core::unary
    void unary(const array &a, array &out, Op op)
    Definition unary.h:72
    -
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:75
    -
    mlx::core::unary_fp
    void unary_fp(const array &a, array &out, Op op)
    Definition unary.h:117
    -
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:74
    -
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:77
    -
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:69
    -
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:79
    -
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:71
    +
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:76
    +
    mlx::core::unary_fp
    void unary_fp(const array &a, array &out, Op op)
    Definition unary.h:120
    +
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:75
    +
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:78
    +
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:70
    +
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:80
    +
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:72
    mlx::core::is_donatable
    bool is_donatable(const array &in, const array &out)
    Definition utils.h:155
    -
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:82
    +
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:84
    mlx::core::ContiguousIterator
    Definition utils.h:73
    mlx::core::ContiguousIterator::loc
    int64_t loc
    Definition utils.h:126
    diff --git a/docs/build/html/cpu_2unary__ops_8h.html b/docs/build/html/cpu_2unary__ops_8h.html index 6abe68814..f35b2d695 100644 --- a/docs/build/html/cpu_2unary__ops_8h.html +++ b/docs/build/html/cpu_2unary__ops_8h.html @@ -132,6 +132,8 @@ Classes   struct  mlx::core::detail::ArcTanh   +struct  mlx::core::detail::BitwiseInvert +  struct  mlx::core::detail::Ceil   struct  mlx::core::detail::Conjugate diff --git a/docs/build/html/cpu_2unary__ops_8h.js b/docs/build/html/cpu_2unary__ops_8h.js index 517b07cd4..610928492 100644 --- a/docs/build/html/cpu_2unary__ops_8h.js +++ b/docs/build/html/cpu_2unary__ops_8h.js @@ -7,6 +7,7 @@ var cpu_2unary__ops_8h = [ "mlx::core::detail::ArcSinh", "structmlx_1_1core_1_1detail_1_1_arc_sinh.html", "structmlx_1_1core_1_1detail_1_1_arc_sinh" ], [ "mlx::core::detail::ArcTan", "structmlx_1_1core_1_1detail_1_1_arc_tan.html", "structmlx_1_1core_1_1detail_1_1_arc_tan" ], [ "mlx::core::detail::ArcTanh", "structmlx_1_1core_1_1detail_1_1_arc_tanh.html", "structmlx_1_1core_1_1detail_1_1_arc_tanh" ], + [ "mlx::core::detail::BitwiseInvert", "structmlx_1_1core_1_1detail_1_1_bitwise_invert.html", "structmlx_1_1core_1_1detail_1_1_bitwise_invert" ], [ "mlx::core::detail::Ceil", "structmlx_1_1core_1_1detail_1_1_ceil.html", "structmlx_1_1core_1_1detail_1_1_ceil" ], [ "mlx::core::detail::Conjugate", "structmlx_1_1core_1_1detail_1_1_conjugate.html", "structmlx_1_1core_1_1detail_1_1_conjugate" ], [ "mlx::core::detail::Cos", "structmlx_1_1core_1_1detail_1_1_cos.html", "structmlx_1_1core_1_1detail_1_1_cos" ], diff --git a/docs/build/html/cpu_2unary__ops_8h_source.html b/docs/build/html/cpu_2unary__ops_8h_source.html index 0a2168a9a..b27ad75c2 100644 --- a/docs/build/html/cpu_2unary__ops_8h_source.html +++ b/docs/build/html/cpu_2unary__ops_8h_source.html @@ -145,98 +145,99 @@ $(function(){initNavTree('cpu_2unary__ops_8h_source.html',''); initResizable(tru
    34DEFAULT_OP(ArcSinh, asinh)
    35DEFAULT_OP(ArcTan, atan)
    36DEFAULT_OP(ArcTanh, atanh)
    -
    37DEFAULT_OP(Ceil, ceil)
    -
    38DEFAULT_OP(Conjugate, conj)
    -
    39DEFAULT_OP(Cos, cos)
    -
    40DEFAULT_OP(Cosh, cosh)
    -
    41DEFAULT_OP(Erf, erf)
    -
    42DEFAULT_OP(ErfInv, erfinv)
    -
    43DEFAULT_OP(Exp, exp)
    -
    44DEFAULT_OP(Expm1, expm1)
    -
    45DEFAULT_OP(Floor, floor);
    -
    46DEFAULT_OP(Log, log);
    -
    47DEFAULT_OP(Log2, log2);
    -
    48DEFAULT_OP(Log10, log10);
    -
    49DEFAULT_OP(Log1p, log1p);
    -
    50DEFAULT_OP(LogicalNot, operator!)
    -
    51DEFAULT_OP(Negative, operator-)
    -
    52DEFAULT_OP(Round, rint);
    -
    53DEFAULT_OP(Sin, sin)
    -
    54DEFAULT_OP(Sinh, sinh)
    -
    55DEFAULT_OP(Sqrt, sqrt)
    -
    56DEFAULT_OP(Rsqrt, rsqrt)
    -
    57DEFAULT_OP(Tan, tan)
    -
    58DEFAULT_OP(Tanh, tanh)
    -
    59
    -
    -
    60struct Imag {
    -
    61 template <int N>
    -
    -
    62 Simd<float, N> operator()(Simd<complex64_t, N> x) {
    -
    63 return simd::imag(x);
    -
    64 }
    +
    37DEFAULT_OP(BitwiseInvert, operator~)
    +
    38DEFAULT_OP(Ceil, ceil)
    +
    39DEFAULT_OP(Conjugate, conj)
    +
    40DEFAULT_OP(Cos, cos)
    +
    41DEFAULT_OP(Cosh, cosh)
    +
    42DEFAULT_OP(Erf, erf)
    +
    43DEFAULT_OP(ErfInv, erfinv)
    +
    44DEFAULT_OP(Exp, exp)
    +
    45DEFAULT_OP(Expm1, expm1)
    +
    46DEFAULT_OP(Floor, floor);
    +
    47DEFAULT_OP(Log, log);
    +
    48DEFAULT_OP(Log2, log2);
    +
    49DEFAULT_OP(Log10, log10);
    +
    50DEFAULT_OP(Log1p, log1p);
    +
    51DEFAULT_OP(LogicalNot, operator!)
    +
    52DEFAULT_OP(Negative, operator-)
    +
    53DEFAULT_OP(Round, rint);
    +
    54DEFAULT_OP(Sin, sin)
    +
    55DEFAULT_OP(Sinh, sinh)
    +
    56DEFAULT_OP(Sqrt, sqrt)
    +
    57DEFAULT_OP(Rsqrt, rsqrt)
    +
    58DEFAULT_OP(Tan, tan)
    +
    59DEFAULT_OP(Tanh, tanh)
    +
    60
    +
    +
    61struct Imag {
    +
    62 template <int N>
    + -
    65 SINGLE()
    -
    66};
    +
    66 SINGLE()
    +
    67};
    -
    67
    -
    -
    68struct Real {
    -
    69 template <int N>
    -
    -
    70 Simd<float, N> operator()(Simd<complex64_t, N> x) {
    -
    71 return simd::real(x);
    -
    72 }
    +
    68
    +
    +
    69struct Real {
    +
    70 template <int N>
    + -
    73 SINGLE()
    -
    74};
    +
    74 SINGLE()
    +
    75};
    -
    75
    -
    -
    76struct Sigmoid {
    -
    77 template <int N, typename T>
    -
    -
    78 Simd<T, N> operator()(Simd<T, N> x) {
    -
    79 return 1.0f / (1.0f + simd::exp(-x));
    -
    80 }
    +
    76
    +
    +
    77struct Sigmoid {
    +
    78 template <int N, typename T>
    +
    +
    79 Simd<T, N> operator()(Simd<T, N> x) {
    +
    80 return 1.0f / (1.0f + simd::exp(-x));
    +
    81 }
    -
    81 SINGLE()
    -
    82};
    +
    82 SINGLE()
    +
    83};
    -
    83
    -
    -
    84struct Sign {
    -
    85 template <int N, typename T>
    -
    -
    86 Simd<T, N> operator()(Simd<T, N> x) {
    -
    87 auto z = Simd<T, N>{0};
    -
    88 if constexpr (std::is_unsigned_v<T>) {
    -
    89 return x != z;
    -
    90 } else if constexpr (std::is_same_v<T, complex64_t>) {
    -
    91 return simd::select(x == z, x, Simd<T, N>(x / simd::abs(x)));
    -
    92 } else {
    -
    93 return simd::select(
    -
    94 x < z, Simd<T, N>{-1}, simd::select(x > z, Simd<T, N>{1}, z));
    -
    95 }
    -
    96 }
    +
    84
    +
    +
    85struct Sign {
    +
    86 template <int N, typename T>
    +
    +
    87 Simd<T, N> operator()(Simd<T, N> x) {
    +
    88 auto z = Simd<T, N>{0};
    +
    89 if constexpr (std::is_unsigned_v<T>) {
    +
    90 return x != z;
    +
    91 } else if constexpr (std::is_same_v<T, complex64_t>) {
    +
    92 return simd::select(x == z, x, Simd<T, N>(x / simd::abs(x)));
    +
    93 } else {
    +
    94 return simd::select(
    +
    95 x < z, Simd<T, N>{-1}, simd::select(x > z, Simd<T, N>{1}, z));
    +
    96 }
    +
    97 }
    -
    97 SINGLE()
    -
    98};
    +
    98 SINGLE()
    +
    99};
    -
    99
    -
    -
    100struct Square {
    -
    101 template <int N, typename T>
    -
    -
    102 Simd<T, N> operator()(Simd<T, N> x) {
    -
    103 return x * x;
    -
    104 }
    +
    100
    +
    +
    101struct Square {
    +
    102 template <int N, typename T>
    +
    +
    103 Simd<T, N> operator()(Simd<T, N> x) {
    +
    104 return x * x;
    +
    105 }
    -
    105 SINGLE()
    -
    106};
    +
    106 SINGLE()
    +
    107};
    -
    107
    -
    108} // namespace mlx::core::detail
    +
    108
    +
    109} // namespace mlx::core::detail
    SINGLE
    #define SINGLE()
    Definition unary_ops.h:15
    DEFAULT_OP
    #define DEFAULT_OP(Op, op)
    Definition unary_ops.h:21
    mlx::core::detail
    Definition binary_ops.h:7
    @@ -248,28 +249,28 @@ $(function(){initNavTree('cpu_2unary__ops_8h_source.html',''); initResizable(tru
    mlx::core::simd::abs
    Simd< T, N > abs(Simd< T, N > v)
    Definition accelerate_simd.h:112
    mlx::core::simd::acosh
    Simd< float16_t, N > acosh(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:30
    mlx::core::simd::erf
    Simd< T, N > erf(Simd< T, N > x)
    Definition math.h:137
    -
    mlx::core::simd::conj
    Simd< T, 1 > conj(Simd< T, 1 > in)
    Definition base_simd.h:84
    +
    mlx::core::simd::conj
    Simd< T, 1 > conj(Simd< T, 1 > in)
    Definition base_simd.h:85
    mlx::core::simd::log2
    Simd< float16_t, N > log2(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:38
    mlx::core::simd::erfinv
    Simd< T, N > erfinv(Simd< T, N > a_)
    Definition math.h:151
    mlx::core::simd::exp
    Simd< T, N > exp(Simd< T, N > in)
    Compute exp(x) in an optimizer friendly way as follows:
    Definition math.h:28
    mlx::core::simd::log
    Simd< float16_t, N > log(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:37
    mlx::core::simd::floor
    Simd< T, N > floor(Simd< T, N > v)
    Definition accelerate_simd.h:113
    mlx::core::simd::expm1
    Simd< float16_t, N > expm1(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:36
    -
    mlx::core::simd::imag
    auto imag(Simd< T, 1 > in) -> Simd< decltype(std::imag(in.value)), 1 >
    Definition base_simd.h:102
    +
    mlx::core::simd::imag
    auto imag(Simd< T, 1 > in) -> Simd< decltype(std::imag(in.value)), 1 >
    Definition base_simd.h:108
    mlx::core::simd::asin
    Simd< float16_t, N > asin(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:31
    mlx::core::simd::tanh
    Simd< float16_t, N > tanh(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:43
    mlx::core::simd::atan
    Simd< float16_t, N > atan(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:33
    mlx::core::simd::asinh
    Simd< float16_t, N > asinh(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:32
    mlx::core::simd::cos
    Simd< T, N > cos(Simd< T, N > x)
    Definition math.h:128
    mlx::core::simd::sin
    Simd< T, N > sin(Simd< T, N > x)
    Definition math.h:119
    -
    mlx::core::simd::real
    auto real(Simd< T, 1 > in) -> Simd< decltype(std::real(in.value)), 1 >
    Definition base_simd.h:98
    +
    mlx::core::simd::real
    auto real(Simd< T, 1 > in) -> Simd< decltype(std::real(in.value)), 1 >
    Definition base_simd.h:104
    mlx::core::simd::log1p
    Simd< float16_t, N > log1p(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:40
    mlx::core::simd::ceil
    Simd< T, N > ceil(Simd< T, N > v)
    Definition accelerate_simd.h:120
    mlx::core::simd::sqrt
    Simd< T, N > sqrt(Simd< T, N > v)
    Definition accelerate_simd.h:129
    mlx::core::simd::acos
    Simd< float16_t, N > acos(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:29
    mlx::core::simd::rsqrt
    Simd< T, N > rsqrt(Simd< T, N > v)
    Definition accelerate_simd.h:130
    mlx::core::simd::cosh
    Simd< float16_t, N > cosh(Simd< float16_t, N > v)
    Definition accelerate_fp16_simd.h:35
    -
    mlx::core::simd::select
    Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
    Definition accelerate_simd.h:231
    +
    mlx::core::simd::select
    Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
    Definition accelerate_simd.h:236
    mlx::core::detail::Abs
    Definition unary_ops.h:30
    mlx::core::detail::ArcCos
    Definition unary_ops.h:31
    @@ -278,38 +279,39 @@ $(function(){initNavTree('cpu_2unary__ops_8h_source.html',''); initResizable(tru
    mlx::core::detail::ArcSinh
    Definition unary_ops.h:34
    mlx::core::detail::ArcTan
    Definition unary_ops.h:35
    mlx::core::detail::ArcTanh
    Definition unary_ops.h:36
    -
    mlx::core::detail::Ceil
    Definition unary_ops.h:37
    -
    mlx::core::detail::Conjugate
    Definition unary_ops.h:38
    -
    mlx::core::detail::Cos
    Definition unary_ops.h:39
    -
    mlx::core::detail::Cosh
    Definition unary_ops.h:40
    -
    mlx::core::detail::Erf
    Definition unary_ops.h:41
    -
    mlx::core::detail::ErfInv
    Definition unary_ops.h:42
    -
    mlx::core::detail::Exp
    Definition unary_ops.h:43
    -
    mlx::core::detail::Expm1
    Definition unary_ops.h:44
    -
    mlx::core::detail::Floor
    Definition unary_ops.h:45
    -
    mlx::core::detail::Imag
    Definition unary_ops.h:60
    -
    mlx::core::detail::Imag::operator()
    Simd< float, N > operator()(Simd< complex64_t, N > x)
    Definition unary_ops.h:62
    -
    mlx::core::detail::Log10
    Definition unary_ops.h:48
    -
    mlx::core::detail::Log1p
    Definition unary_ops.h:49
    -
    mlx::core::detail::Log2
    Definition unary_ops.h:47
    -
    mlx::core::detail::Log
    Definition unary_ops.h:46
    -
    mlx::core::detail::LogicalNot
    Definition unary_ops.h:50
    -
    mlx::core::detail::Negative
    Definition unary_ops.h:51
    -
    mlx::core::detail::Real
    Definition unary_ops.h:68
    -
    mlx::core::detail::Real::operator()
    Simd< float, N > operator()(Simd< complex64_t, N > x)
    Definition unary_ops.h:70
    -
    mlx::core::detail::Round
    Definition unary_ops.h:52
    -
    mlx::core::detail::Rsqrt
    Definition unary_ops.h:56
    -
    mlx::core::detail::Sigmoid
    Definition unary_ops.h:76
    -
    mlx::core::detail::Sigmoid::operator()
    Simd< T, N > operator()(Simd< T, N > x)
    Definition unary_ops.h:78
    -
    mlx::core::detail::Sign
    Definition unary_ops.h:84
    -
    mlx::core::detail::Sign::operator()
    Simd< T, N > operator()(Simd< T, N > x)
    Definition unary_ops.h:86
    -
    mlx::core::detail::Sin
    Definition unary_ops.h:53
    -
    mlx::core::detail::Sinh
    Definition unary_ops.h:54
    -
    mlx::core::detail::Sqrt
    Definition unary_ops.h:55
    -
    mlx::core::detail::Square
    Definition unary_ops.h:100
    -
    mlx::core::detail::Square::operator()
    Simd< T, N > operator()(Simd< T, N > x)
    Definition unary_ops.h:102
    -
    mlx::core::detail::Tan
    Definition unary_ops.h:57
    -
    mlx::core::detail::Tanh
    Definition unary_ops.h:58
    +
    mlx::core::detail::BitwiseInvert
    Definition unary_ops.h:37
    +
    mlx::core::detail::Ceil
    Definition unary_ops.h:38
    +
    mlx::core::detail::Conjugate
    Definition unary_ops.h:39
    +
    mlx::core::detail::Cos
    Definition unary_ops.h:40
    +
    mlx::core::detail::Cosh
    Definition unary_ops.h:41
    +
    mlx::core::detail::Erf
    Definition unary_ops.h:42
    +
    mlx::core::detail::ErfInv
    Definition unary_ops.h:43
    +
    mlx::core::detail::Exp
    Definition unary_ops.h:44
    +
    mlx::core::detail::Expm1
    Definition unary_ops.h:45
    +
    mlx::core::detail::Floor
    Definition unary_ops.h:46
    +
    mlx::core::detail::Imag
    Definition unary_ops.h:61
    +
    mlx::core::detail::Imag::operator()
    Simd< float, N > operator()(Simd< complex64_t, N > x)
    Definition unary_ops.h:63
    +
    mlx::core::detail::Log10
    Definition unary_ops.h:49
    +
    mlx::core::detail::Log1p
    Definition unary_ops.h:50
    +
    mlx::core::detail::Log2
    Definition unary_ops.h:48
    +
    mlx::core::detail::Log
    Definition unary_ops.h:47
    +
    mlx::core::detail::LogicalNot
    Definition unary_ops.h:51
    +
    mlx::core::detail::Negative
    Definition unary_ops.h:52
    +
    mlx::core::detail::Real
    Definition unary_ops.h:69
    +
    mlx::core::detail::Real::operator()
    Simd< float, N > operator()(Simd< complex64_t, N > x)
    Definition unary_ops.h:71
    +
    mlx::core::detail::Round
    Definition unary_ops.h:53
    +
    mlx::core::detail::Rsqrt
    Definition unary_ops.h:57
    +
    mlx::core::detail::Sigmoid
    Definition unary_ops.h:77
    +
    mlx::core::detail::Sigmoid::operator()
    Simd< T, N > operator()(Simd< T, N > x)
    Definition unary_ops.h:79
    +
    mlx::core::detail::Sign
    Definition unary_ops.h:85
    +
    mlx::core::detail::Sign::operator()
    Simd< T, N > operator()(Simd< T, N > x)
    Definition unary_ops.h:87
    +
    mlx::core::detail::Sin
    Definition unary_ops.h:54
    +
    mlx::core::detail::Sinh
    Definition unary_ops.h:55
    +
    mlx::core::detail::Sqrt
    Definition unary_ops.h:56
    +
    mlx::core::detail::Square
    Definition unary_ops.h:101
    +
    mlx::core::detail::Square::operator()
    Simd< T, N > operator()(Simd< T, N > x)
    Definition unary_ops.h:103
    +
    mlx::core::detail::Tan
    Definition unary_ops.h:58
    +
    mlx::core::detail::Tanh
    Definition unary_ops.h:59
    mlx::core::simd::Simd
    Definition accelerate_simd.h:55
    diff --git a/docs/build/html/dev/custom_metal_kernels.html b/docs/build/html/dev/custom_metal_kernels.html index d44b8aaae..42511a4c1 100644 --- a/docs/build/html/dev/custom_metal_kernels.html +++ b/docs/build/html/dev/custom_metal_kernels.html @@ -8,7 +8,7 @@ - Custom Metal Kernels — MLX 0.22.1 documentation + Custom Metal Kernels — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/dev/extensions.html b/docs/build/html/dev/extensions.html index f9270149d..2729ea725 100644 --- a/docs/build/html/dev/extensions.html +++ b/docs/build/html/dev/extensions.html @@ -8,7 +8,7 @@ - Custom Extensions in MLX — MLX 0.22.1 documentation + Custom Extensions in MLX — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/dev/metal_debugger.html b/docs/build/html/dev/metal_debugger.html index 8eee1ab87..cbe886361 100644 --- a/docs/build/html/dev/metal_debugger.html +++ b/docs/build/html/dev/metal_debugger.html @@ -8,7 +8,7 @@ - Metal Debugger — MLX 0.22.1 documentation + Metal Debugger — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/dev/mlx_in_cpp.html b/docs/build/html/dev/mlx_in_cpp.html index 4f56324fe..7d640df93 100644 --- a/docs/build/html/dev/mlx_in_cpp.html +++ b/docs/build/html/dev/mlx_in_cpp.html @@ -8,7 +8,7 @@ - Using MLX in C++ — MLX 0.22.1 documentation + Using MLX in C++ — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -50,7 +50,7 @@ - + @@ -129,8 +129,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -275,6 +275,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -485,6 +486,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
    • -
    29
    -
    -
    30 enum class Kind {
    -
    31 b, /* bool */
    -
    32 u, /* unsigned int */
    -
    33 i, /* signed int */
    -
    34 f, /* float */
    -
    35 c, /* complex */
    -
    36 V, /* void - used for brain float */
    -
    37 };
    +
    30
    +
    +
    31 enum class Kind {
    +
    32 b, /* bool */
    +
    33 u, /* unsigned int */
    +
    34 i, /* signed int */
    +
    35 f, /* float */
    +
    36 c, /* complex */
    +
    37 V, /* void - used for brain float */
    +
    38 };
    -
    38
    -
    -
    39 enum class Category {
    -
    40 complexfloating,
    -
    41 floating,
    -
    42 inexact,
    -
    43 signedinteger,
    -
    44 unsignedinteger,
    -
    45 integer,
    -
    46 number,
    -
    47 generic
    -
    48 };
    +
    39
    + -
    49
    -
    50 constexpr explicit Dtype(Val val, uint8_t size) : val_(val), size_(size) {}
    -
    51
    -
    -
    52 constexpr operator Val() const {
    -
    53 return val_;
    -
    54 }
    +
    50
    +
    51 constexpr explicit Dtype(Val val, uint8_t size) : val_(val), size_(size) {}
    +
    52
    +
    +
    53 constexpr operator Val() const {
    +
    54 return val_;
    +
    55 }
    -
    -
    55 constexpr Val val() const {
    -
    56 return val_;
    -
    57 }
    +
    +
    56 constexpr Val val() const {
    +
    57 return val_;
    +
    58 }
    -
    -
    58 constexpr uint8_t size() const {
    -
    59 return size_;
    -
    60 }
    +
    +
    59 constexpr uint8_t size() const {
    +
    60 return size_;
    +
    61 }
    -
    61
    -
    62 private:
    -
    63 Val val_;
    -
    64 uint8_t size_;
    -
    65};
    +
    62
    +
    63 private:
    +
    64 Val val_;
    +
    65 uint8_t size_;
    +
    66};
    -
    66
    -
    67inline constexpr Dtype bool_{Dtype::Val::bool_, sizeof(bool)};
    -
    68
    -
    69inline constexpr Dtype uint8{Dtype::Val::uint8, sizeof(uint8_t)};
    -
    70inline constexpr Dtype uint16{Dtype::Val::uint16, sizeof(uint16_t)};
    -
    71inline constexpr Dtype uint32{Dtype::Val::uint32, sizeof(uint32_t)};
    -
    72inline constexpr Dtype uint64{Dtype::Val::uint64, sizeof(uint64_t)};
    -
    73
    -
    74inline constexpr Dtype int8{Dtype::Val::int8, sizeof(int8_t)};
    -
    75inline constexpr Dtype int16{Dtype::Val::int16, sizeof(int16_t)};
    -
    76inline constexpr Dtype int32{Dtype::Val::int32, sizeof(int32_t)};
    -
    77inline constexpr Dtype int64{Dtype::Val::int64, sizeof(int64_t)};
    -
    78
    -
    79inline constexpr Dtype float16{Dtype::Val::float16, sizeof(uint16_t)};
    -
    80inline constexpr Dtype float32{Dtype::Val::float32, sizeof(float)};
    -
    81inline constexpr Dtype bfloat16{Dtype::Val::bfloat16, sizeof(uint16_t)};
    -
    82inline constexpr Dtype complex64{Dtype::Val::complex64, sizeof(complex64_t)};
    -
    83
    -
    84inline constexpr Dtype::Category complexfloating =
    -
    85 Dtype::Category::complexfloating;
    -
    86inline constexpr Dtype::Category floating = Dtype::Category::floating;
    -
    87inline constexpr Dtype::Category inexact = Dtype::Category::inexact;
    -
    88inline constexpr Dtype::Category signedinteger = Dtype::Category::signedinteger;
    -
    89inline constexpr Dtype::Category unsignedinteger =
    -
    90 Dtype::Category::unsignedinteger;
    -
    91inline constexpr Dtype::Category integer = Dtype::Category::integer;
    -
    92inline constexpr Dtype::Category number = Dtype::Category::number;
    -
    93inline constexpr Dtype::Category generic = Dtype::Category::generic;
    -
    94
    -
    95bool issubdtype(const Dtype& a, const Dtype& b);
    -
    96bool issubdtype(const Dtype::Category& a, const Dtype& b);
    -
    97bool issubdtype(const Dtype& a, const Dtype::Category& b);
    -
    98bool issubdtype(const Dtype::Category& a, const Dtype::Category& b);
    -
    99
    -
    100Dtype promote_types(const Dtype& t1, const Dtype& t2);
    +
    67
    +
    68inline constexpr Dtype bool_{Dtype::Val::bool_, sizeof(bool)};
    +
    69
    +
    70inline constexpr Dtype uint8{Dtype::Val::uint8, sizeof(uint8_t)};
    +
    71inline constexpr Dtype uint16{Dtype::Val::uint16, sizeof(uint16_t)};
    +
    72inline constexpr Dtype uint32{Dtype::Val::uint32, sizeof(uint32_t)};
    +
    73inline constexpr Dtype uint64{Dtype::Val::uint64, sizeof(uint64_t)};
    +
    74
    +
    75inline constexpr Dtype int8{Dtype::Val::int8, sizeof(int8_t)};
    +
    76inline constexpr Dtype int16{Dtype::Val::int16, sizeof(int16_t)};
    +
    77inline constexpr Dtype int32{Dtype::Val::int32, sizeof(int32_t)};
    +
    78inline constexpr Dtype int64{Dtype::Val::int64, sizeof(int64_t)};
    +
    79
    +
    80inline constexpr Dtype float16{Dtype::Val::float16, sizeof(uint16_t)};
    +
    81inline constexpr Dtype float32{Dtype::Val::float32, sizeof(float)};
    +
    82inline constexpr Dtype float64{Dtype::Val::float64, sizeof(double)};
    +
    83inline constexpr Dtype bfloat16{Dtype::Val::bfloat16, sizeof(uint16_t)};
    +
    84inline constexpr Dtype complex64{Dtype::Val::complex64, sizeof(complex64_t)};
    +
    85
    +
    86inline constexpr Dtype::Category complexfloating =
    +
    87 Dtype::Category::complexfloating;
    +
    88inline constexpr Dtype::Category floating = Dtype::Category::floating;
    +
    89inline constexpr Dtype::Category inexact = Dtype::Category::inexact;
    +
    90inline constexpr Dtype::Category signedinteger = Dtype::Category::signedinteger;
    +
    91inline constexpr Dtype::Category unsignedinteger =
    +
    92 Dtype::Category::unsignedinteger;
    +
    93inline constexpr Dtype::Category integer = Dtype::Category::integer;
    +
    94inline constexpr Dtype::Category number = Dtype::Category::number;
    +
    95inline constexpr Dtype::Category generic = Dtype::Category::generic;
    +
    96
    +
    97bool issubdtype(const Dtype& a, const Dtype& b);
    +
    98bool issubdtype(const Dtype::Category& a, const Dtype& b);
    +
    99bool issubdtype(const Dtype& a, const Dtype::Category& b);
    +
    100bool issubdtype(const Dtype::Category& a, const Dtype::Category& b);
    101
    -
    -
    102inline uint8_t size_of(const Dtype& t) {
    -
    103 return t.size();
    -
    104}
    +
    102Dtype promote_types(const Dtype& t1, const Dtype& t2);
    +
    103
    +
    +
    104inline uint8_t size_of(const Dtype& t) {
    +
    105 return t.size();
    +
    106}
    -
    105
    -
    106Dtype::Kind kindof(const Dtype& t);
    107
    -
    108template <typename T>
    -
    -
    109struct TypeToDtype {
    -
    110 operator Dtype();
    -
    111};
    +
    108Dtype::Kind kindof(const Dtype& t);
    +
    109
    +
    110template <typename T>
    +
    +
    111struct TypeToDtype {
    +
    112 operator Dtype();
    +
    113};
    -
    112
    -
    113} // namespace mlx::core
    +
    114
    +
    115} // namespace mlx::core
    half_types.h
    mlx::core
    Definition allocator.h:7
    -
    mlx::core::number
    constexpr Dtype::Category number
    Definition dtype.h:92
    -
    mlx::core::integer
    constexpr Dtype::Category integer
    Definition dtype.h:91
    -
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:67
    -
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:72
    -
    mlx::core::signedinteger
    constexpr Dtype::Category signedinteger
    Definition dtype.h:88
    -
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:70
    -
    mlx::core::unsignedinteger
    constexpr Dtype::Category unsignedinteger
    Definition dtype.h:89
    +
    mlx::core::number
    constexpr Dtype::Category number
    Definition dtype.h:94
    +
    mlx::core::integer
    constexpr Dtype::Category integer
    Definition dtype.h:93
    +
    mlx::core::bool_
    constexpr Dtype bool_
    Definition dtype.h:68
    +
    mlx::core::uint64
    constexpr Dtype uint64
    Definition dtype.h:73
    +
    mlx::core::signedinteger
    constexpr Dtype::Category signedinteger
    Definition dtype.h:90
    +
    mlx::core::uint16
    constexpr Dtype uint16
    Definition dtype.h:71
    +
    mlx::core::unsignedinteger
    constexpr Dtype::Category unsignedinteger
    Definition dtype.h:91
    +
    mlx::core::float64
    constexpr Dtype float64
    Definition dtype.h:82
    mlx::core::promote_types
    Dtype promote_types(const Dtype &t1, const Dtype &t2)
    -
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:81
    -
    mlx::core::inexact
    constexpr Dtype::Category inexact
    Definition dtype.h:87
    -
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:76
    -
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:80
    -
    mlx::core::complexfloating
    constexpr Dtype::Category complexfloating
    Definition dtype.h:84
    -
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:75
    -
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:74
    -
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:77
    -
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:69
    -
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:79
    -
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:71
    -
    mlx::core::floating
    constexpr Dtype::Category floating
    Definition dtype.h:86
    +
    mlx::core::bfloat16
    constexpr Dtype bfloat16
    Definition dtype.h:83
    +
    mlx::core::inexact
    constexpr Dtype::Category inexact
    Definition dtype.h:89
    +
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:77
    +
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:81
    +
    mlx::core::complexfloating
    constexpr Dtype::Category complexfloating
    Definition dtype.h:86
    +
    mlx::core::int16
    constexpr Dtype int16
    Definition dtype.h:76
    +
    mlx::core::int8
    constexpr Dtype int8
    Definition dtype.h:75
    +
    mlx::core::int64
    constexpr Dtype int64
    Definition dtype.h:78
    +
    mlx::core::uint8
    constexpr Dtype uint8
    Definition dtype.h:70
    +
    mlx::core::float16
    constexpr Dtype float16
    Definition dtype.h:80
    +
    mlx::core::uint32
    constexpr Dtype uint32
    Definition dtype.h:72
    +
    mlx::core::floating
    constexpr Dtype::Category floating
    Definition dtype.h:88
    mlx::core::issubdtype
    bool issubdtype(const Dtype &a, const Dtype &b)
    mlx::core::kindof
    Dtype::Kind kindof(const Dtype &t)
    -
    mlx::core::size_of
    uint8_t size_of(const Dtype &t)
    Definition dtype.h:102
    -
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:82
    +
    mlx::core::size_of
    uint8_t size_of(const Dtype &t)
    Definition dtype.h:104
    +
    mlx::core::complex64
    constexpr Dtype complex64
    Definition dtype.h:84
    mlx::core::Dtype
    Definition dtype.h:13
    -
    mlx::core::Dtype::val
    constexpr Val val() const
    Definition dtype.h:55
    -
    mlx::core::Dtype::size
    constexpr uint8_t size() const
    Definition dtype.h:58
    -
    mlx::core::Dtype::Category
    Category
    Definition dtype.h:39
    -
    mlx::core::Dtype::Category::integer
    @ integer
    Definition dtype.h:45
    -
    mlx::core::Dtype::Category::floating
    @ floating
    Definition dtype.h:41
    -
    mlx::core::Dtype::Category::generic
    @ generic
    Definition dtype.h:47
    -
    mlx::core::Dtype::Category::unsignedinteger
    @ unsignedinteger
    Definition dtype.h:44
    -
    mlx::core::Dtype::Category::number
    @ number
    Definition dtype.h:46
    -
    mlx::core::Dtype::Category::inexact
    @ inexact
    Definition dtype.h:42
    -
    mlx::core::Dtype::Category::signedinteger
    @ signedinteger
    Definition dtype.h:43
    -
    mlx::core::Dtype::Category::complexfloating
    @ complexfloating
    Definition dtype.h:40
    -
    mlx::core::Dtype::Kind
    Kind
    Definition dtype.h:30
    -
    mlx::core::Dtype::Kind::c
    @ c
    Definition dtype.h:35
    -
    mlx::core::Dtype::Kind::V
    @ V
    Definition dtype.h:36
    -
    mlx::core::Dtype::Kind::u
    @ u
    Definition dtype.h:32
    -
    mlx::core::Dtype::Kind::i
    @ i
    Definition dtype.h:33
    -
    mlx::core::Dtype::Kind::f
    @ f
    Definition dtype.h:34
    -
    mlx::core::Dtype::Kind::b
    @ b
    Definition dtype.h:31
    +
    mlx::core::Dtype::val
    constexpr Val val() const
    Definition dtype.h:56
    +
    mlx::core::Dtype::size
    constexpr uint8_t size() const
    Definition dtype.h:59
    +
    mlx::core::Dtype::Category
    Category
    Definition dtype.h:40
    +
    mlx::core::Dtype::Category::integer
    @ integer
    Definition dtype.h:46
    +
    mlx::core::Dtype::Category::floating
    @ floating
    Definition dtype.h:42
    +
    mlx::core::Dtype::Category::generic
    @ generic
    Definition dtype.h:48
    +
    mlx::core::Dtype::Category::unsignedinteger
    @ unsignedinteger
    Definition dtype.h:45
    +
    mlx::core::Dtype::Category::number
    @ number
    Definition dtype.h:47
    +
    mlx::core::Dtype::Category::inexact
    @ inexact
    Definition dtype.h:43
    +
    mlx::core::Dtype::Category::signedinteger
    @ signedinteger
    Definition dtype.h:44
    +
    mlx::core::Dtype::Category::complexfloating
    @ complexfloating
    Definition dtype.h:41
    +
    mlx::core::Dtype::Kind
    Kind
    Definition dtype.h:31
    +
    mlx::core::Dtype::Kind::c
    @ c
    Definition dtype.h:36
    +
    mlx::core::Dtype::Kind::V
    @ V
    Definition dtype.h:37
    +
    mlx::core::Dtype::Kind::u
    @ u
    Definition dtype.h:33
    +
    mlx::core::Dtype::Kind::i
    @ i
    Definition dtype.h:34
    +
    mlx::core::Dtype::Kind::f
    @ f
    Definition dtype.h:35
    +
    mlx::core::Dtype::Kind::b
    @ b
    Definition dtype.h:32
    mlx::core::Dtype::Val
    Val
    Definition dtype.h:14
    mlx::core::Dtype::Val::int32
    @ int32
    Definition dtype.h:22
    mlx::core::Dtype::Val::float16
    @ float16
    Definition dtype.h:24
    mlx::core::Dtype::Val::int8
    @ int8
    Definition dtype.h:20
    mlx::core::Dtype::Val::uint64
    @ uint64
    Definition dtype.h:19
    mlx::core::Dtype::Val::uint32
    @ uint32
    Definition dtype.h:18
    -
    mlx::core::Dtype::Val::bfloat16
    @ bfloat16
    Definition dtype.h:26
    +
    mlx::core::Dtype::Val::bfloat16
    @ bfloat16
    Definition dtype.h:27
    mlx::core::Dtype::Val::bool_
    @ bool_
    Definition dtype.h:15
    mlx::core::Dtype::Val::uint8
    @ uint8
    Definition dtype.h:16
    -
    mlx::core::Dtype::Val::complex64
    @ complex64
    Definition dtype.h:27
    +
    mlx::core::Dtype::Val::complex64
    @ complex64
    Definition dtype.h:28
    mlx::core::Dtype::Val::uint16
    @ uint16
    Definition dtype.h:17
    mlx::core::Dtype::Val::int16
    @ int16
    Definition dtype.h:21
    mlx::core::Dtype::Val::float32
    @ float32
    Definition dtype.h:25
    +
    mlx::core::Dtype::Val::float64
    @ float64
    Definition dtype.h:26
    mlx::core::Dtype::Val::int64
    @ int64
    Definition dtype.h:23
    -
    mlx::core::Dtype::Dtype
    constexpr Dtype(Val val, uint8_t size)
    Definition dtype.h:50
    -
    mlx::core::TypeToDtype
    Definition dtype.h:109
    +
    mlx::core::Dtype::Dtype
    constexpr Dtype(Val val, uint8_t size)
    Definition dtype.h:51
    +
    mlx::core::TypeToDtype
    Definition dtype.h:111
    mlx::core::complex64_t
    Definition complex.h:35
    diff --git a/docs/build/html/examples/linear_regression.html b/docs/build/html/examples/linear_regression.html index 4dc92d925..c2205d192 100644 --- a/docs/build/html/examples/linear_regression.html +++ b/docs/build/html/examples/linear_regression.html @@ -8,7 +8,7 @@ - Linear Regression — MLX 0.22.1 documentation + Linear Regression — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/examples/llama-inference.html b/docs/build/html/examples/llama-inference.html index 4facb9856..30817cc0c 100644 --- a/docs/build/html/examples/llama-inference.html +++ b/docs/build/html/examples/llama-inference.html @@ -8,7 +8,7 @@ - LLM inference — MLX 0.22.1 documentation + LLM inference — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/examples/mlp.html b/docs/build/html/examples/mlp.html index 12c573fcd..f8266bc9b 100644 --- a/docs/build/html/examples/mlp.html +++ b/docs/build/html/examples/mlp.html @@ -8,7 +8,7 @@ - Multi-Layer Perceptron — MLX 0.22.1 documentation + Multi-Layer Perceptron — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
    • diff --git a/docs/build/html/functions_func_o.html b/docs/build/html/functions_func_o.html index 924e6e010..b9c97832f 100644 --- a/docs/build/html/functions_func_o.html +++ b/docs/build/html/functions_func_o.html @@ -115,7 +115,7 @@ $(function(){initNavTree('functions_func_o.html',''); initResizable(true); });
  • operator T() : _MLX_BFloat16, complex64_t
  • operator Val() : mlx::core::Dtype
  • operator value_type() : mlx::steel::integral_constant< T, v >
    • -
  • operator()() : Abs, Add, ArcCos, ArcCosh, ArcSin, ArcSinh, ArcTan2, ArcTan, ArcTanh, BitwiseAnd, BitwiseOr, BitwiseXor, Ceil, Conjugate, Cos, Cosh, CumMax< U >, CumMin< U >, CumProd< bool >, Divide, DivMod, Equal, Erf, ErfInv, Exp, Expm1, Floor, FloorDivide, Greater, GreaterEqual, Imag, LeftShift, Less, LessEqual, LessThan< T >, Log10, Log1p, Log2, Log, LogAddExp, LogicalAnd, LogicalNot, LogicalOr, Maximum, Minimum, mlx::core::detail::Abs, mlx::core::detail::Add, mlx::core::detail::ArcCos, mlx::core::detail::ArcCosh, mlx::core::detail::ArcSin, mlx::core::detail::ArcSinh, mlx::core::detail::ArcTan2, mlx::core::detail::ArcTan, mlx::core::detail::ArcTanh, mlx::core::detail::BitwiseAnd, mlx::core::detail::BitwiseOr, mlx::core::detail::BitwiseXor, mlx::core::detail::Ceil, mlx::core::detail::Conjugate, mlx::core::detail::Cos, mlx::core::detail::Cosh, mlx::core::detail::Divide, mlx::core::detail::Equal, mlx::core::detail::Erf, mlx::core::detail::ErfInv, mlx::core::detail::Exp, mlx::core::detail::Expm1, mlx::core::detail::Floor, mlx::core::detail::Greater, mlx::core::detail::GreaterEqual, mlx::core::detail::Imag, mlx::core::detail::LeftShift, mlx::core::detail::Less, mlx::core::detail::LessEqual, mlx::core::detail::Log10, mlx::core::detail::Log1p, mlx::core::detail::Log2, mlx::core::detail::Log, mlx::core::detail::LogAddExp, mlx::core::detail::LogicalAnd, mlx::core::detail::LogicalNot, mlx::core::detail::LogicalOr, mlx::core::detail::Maximum, mlx::core::detail::Minimum, mlx::core::detail::Multiply, mlx::core::detail::NaNEqual, mlx::core::detail::Negative, mlx::core::detail::NotEqual, mlx::core::detail::Power, mlx::core::detail::Real, mlx::core::detail::Remainder, mlx::core::detail::RightShift, mlx::core::detail::Round, mlx::core::detail::Rsqrt, mlx::core::detail::Select, mlx::core::detail::Sigmoid, mlx::core::detail::Sign, mlx::core::detail::Sin, mlx::core::detail::Sinh, mlx::core::detail::Sqrt, mlx::core::detail::Square, mlx::core::detail::Subtract, mlx::core::detail::Tan, mlx::core::detail::Tanh, mlx::core::FunctionExporter, mlx::core::ImportedFunction, mlx::core::ScalarVector< Op >, mlx::core::VectorScalar< Op >, mlx::core::VectorVector< Op >, Multiply, NaNEqual, Negative, NotEqual, pocketfft::detail::ExecC2C, pocketfft::detail::ExecDcst, pocketfft::detail::ExecHartley, pocketfft::detail::ExecR2R, Power, Real, Remainder, RightShift, Round, Rsqrt, Select, Sigmoid, Sign, Sin, Sinh, Sqrt, Square, Subtract, Tan, Tanh
    • +
  • operator()() : Abs, Add, ArcCos, ArcCosh, ArcSin, ArcSinh, ArcTan2, ArcTan, ArcTanh, BitwiseAnd, BitwiseInvert, BitwiseOr, BitwiseXor, Ceil, Conjugate, Cos, Cosh, CumMax< U >, CumMin< U >, CumProd< bool >, Divide, DivMod, Equal, Erf, ErfInv, Exp, Expm1, Floor, FloorDivide, Greater, GreaterEqual, Imag, LeftShift, Less, LessEqual, LessThan< T >, Log10, Log1p, Log2, Log, LogAddExp, LogicalAnd, LogicalNot, LogicalOr, Maximum, Minimum, mlx::core::detail::Abs, mlx::core::detail::Add, mlx::core::detail::ArcCos, mlx::core::detail::ArcCosh, mlx::core::detail::ArcSin, mlx::core::detail::ArcSinh, mlx::core::detail::ArcTan2, mlx::core::detail::ArcTan, mlx::core::detail::ArcTanh, mlx::core::detail::BitwiseAnd, mlx::core::detail::BitwiseInvert, mlx::core::detail::BitwiseOr, mlx::core::detail::BitwiseXor, mlx::core::detail::Ceil, mlx::core::detail::Conjugate, mlx::core::detail::Cos, mlx::core::detail::Cosh, mlx::core::detail::Divide, mlx::core::detail::Equal, mlx::core::detail::Erf, mlx::core::detail::ErfInv, mlx::core::detail::Exp, mlx::core::detail::Expm1, mlx::core::detail::Floor, mlx::core::detail::Greater, mlx::core::detail::GreaterEqual, mlx::core::detail::Imag, mlx::core::detail::LeftShift, mlx::core::detail::Less, mlx::core::detail::LessEqual, mlx::core::detail::Log10, mlx::core::detail::Log1p, mlx::core::detail::Log2, mlx::core::detail::Log, mlx::core::detail::LogAddExp, mlx::core::detail::LogicalAnd, mlx::core::detail::LogicalNot, mlx::core::detail::LogicalOr, mlx::core::detail::Maximum, mlx::core::detail::Minimum, mlx::core::detail::Multiply, mlx::core::detail::NaNEqual, mlx::core::detail::Negative, mlx::core::detail::NotEqual, mlx::core::detail::Power, mlx::core::detail::Real, mlx::core::detail::Remainder, mlx::core::detail::RightShift, mlx::core::detail::Round, mlx::core::detail::Rsqrt, mlx::core::detail::Select, mlx::core::detail::Sigmoid, mlx::core::detail::Sign, mlx::core::detail::Sin, mlx::core::detail::Sinh, mlx::core::detail::Sqrt, mlx::core::detail::Square, mlx::core::detail::Subtract, mlx::core::detail::Tan, mlx::core::detail::Tanh, mlx::core::FunctionExporter, mlx::core::ImportedFunction, mlx::core::ScalarVector< Op >, mlx::core::VectorScalar< Op >, mlx::core::VectorVector< Op >, Multiply, NaNEqual, Negative, NotEqual, pocketfft::detail::ExecC2C, pocketfft::detail::ExecDcst, pocketfft::detail::ExecHartley, pocketfft::detail::ExecR2R, Power, Real, Remainder, RightShift, Round, Rsqrt, Select, Sigmoid, Sign, Sin, Sinh, Sqrt, Square, Subtract, Tan, Tanh
  • operator*() : mlx::core::array::ArrayIterator, pocketfft::detail::cmplx< T >
  • operator*=() : pocketfft::detail::cmplx< T >
  • operator+() : mlx::core::array::ArrayIterator, pocketfft::detail::cmplx< T >
    • @@ -127,7 +127,7 @@ $(function(){initNavTree('functions_func_o.html',''); initResizable(true); });
  • operator[]() : mlx::core::simd::Simd< T, N >, mlx::core::simd::Simd< float16_t, N >, mlx::core::simd::Simd< T, 1 >, pocketfft::detail::arr< T >, pocketfft::detail::cndarr< T >, pocketfft::detail::ndarr< T >, pocketfft::detail::sincos_2pibyn< T >
  • out_of_bounds() : ReadWriter< in_T, out_T, step, four_step_real >
  • output_shape() : mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::ExpandDims, mlx::core::Flatten, mlx::core::Reshape, mlx::core::Squeeze, mlx::core::Unflatten
    • -
  • output_shapes() : mlx::core::Abs, mlx::core::Add, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::Flatten, mlx::core::Floor, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten
    • +
  • output_shapes() : mlx::core::Abs, mlx::core::Add, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::Flatten, mlx::core::Floor, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten
  • outputs() : mlx::core::array, mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder
  • overwrite_descriptor() : mlx::core::array
    • diff --git a/docs/build/html/functions_func_p.html b/docs/build/html/functions_func_p.html index d7612e333..ee0b3b401 100644 --- a/docs/build/html/functions_func_p.html +++ b/docs/build/html/functions_func_p.html @@ -117,7 +117,7 @@ $(function(){initNavTree('functions_func_p.html',''); initResizable(true); });
  • primitive() : mlx::core::array
  • primitive_id() : mlx::core::array
  • primitive_ptr() : mlx::core::array
    • -
  • print() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::PrintFormatter, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
    • +
  • print() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::LUF, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::PrintFormatter, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
  • prod() : pocketfft::detail::util
  • ptr() : mlx::core::allocator::Buffer, mlx::core::metal::Buffer
  • push() : pocketfft::detail::threading::concurrent_queue< T >
    • diff --git a/docs/build/html/functions_func_v.html b/docs/build/html/functions_func_v.html index 7d65bff5f..2a4f355d8 100644 --- a/docs/build/html/functions_func_v.html +++ b/docs/build/html/functions_func_v.html @@ -112,7 +112,7 @@ $(function(){initNavTree('functions_func_v.html',''); initResizable(true); });
  • VectorVector() : mlx::core::VectorVector< Op >
  • View() : mlx::core::View
  • vjp() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::fast::LayerNorm, mlx::core::fast::RMSNorm, mlx::core::fast::RoPE, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten
    • -
  • vmap() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
    • +
  • vmap() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
    • diff --git a/docs/build/html/functions_g.html b/docs/build/html/functions_g.html index 82cb5dc70..52f41a96a 100644 --- a/docs/build/html/functions_g.html +++ b/docs/build/html/functions_g.html @@ -117,7 +117,6 @@ $(function(){initNavTree('functions_g.html',''); initResizable(true); });
  • get_architecture() : mlx::core::metal::Device
  • get_cache_memory() : mlx::core::metal::MetalAllocator
  • get_command_buffer() : mlx::core::metal::Device
    • -
  • get_command_buffer_ops() : mlx::core::metal::Device
  • get_command_encoder() : mlx::core::metal::Device
  • get_coord() : mlx::steel::BaseMMAFrag< T, 8, 8 >
  • get_default_stream() : mlx::core::scheduler::Scheduler
    • diff --git a/docs/build/html/functions_i.html b/docs/build/html/functions_i.html index 675eac1ed..2e808b6ec 100644 --- a/docs/build/html/functions_i.html +++ b/docs/build/html/functions_i.html @@ -116,7 +116,6 @@ $(function(){initNavTree('functions_i.html',''); initResizable(true); });
  • in_dynamic_tracing() : mlx::core::detail::InTracing
  • in_strides : MLXConvParams< NDIM >
  • in_tracing() : mlx::core::detail::InTracing
    • -
  • increment_command_buffer_ops() : mlx::core::metal::Device
  • index : LoopedElemToLoc< DIM, OffsetT, General >, LoopedElemToLoc< 1, OffsetT, false >, LoopedElemToLoc< 1, OffsetT, true >, mlx::core::Device, mlx::core::Stream
  • infinity() : metal::_numeric_limits_impl< bfloat16_t >, mlx::core::numeric_limits< bfloat16_t >, mlx::core::numeric_limits< float16_t >
  • init : CumMax< U >, CumMin< U >, CumProd< bool >, LessThan< T >
    • @@ -133,7 +132,7 @@ $(function(){initNavTree('functions_i.html',''); initResizable(true); });
  • iS : MLXConvParams< NDIM >
  • is_available() : mlx::core::array
  • is_donatable() : mlx::core::array
    • -
  • is_equivalent() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::fast::AffineQuantize, mlx::core::fast::ScaledDotProductAttention, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
    • +
  • is_equivalent() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::fast::AffineQuantize, mlx::core::fast::ScaledDotProductAttention, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
  • is_open() : mlx::core::io::FileWriter, mlx::core::io::ParallelFileReader, mlx::core::io::Reader, mlx::core::io::Writer
  • is_ready() : pocketfft::detail::threading::latch
  • is_signaled() : mlx::core::Event
    • diff --git a/docs/build/html/functions_l.html b/docs/build/html/functions_l.html index cb492399e..453a84e05 100644 --- a/docs/build/html/functions_l.html +++ b/docs/build/html/functions_l.html @@ -140,6 +140,7 @@ $(function(){initNavTree('functions_l.html',''); initResizable(true); });
  • LogicalOr() : mlx::core::LogicalOr
  • LoopedElemToLoc() : LoopedElemToLoc< DIM, OffsetT, General >, LoopedElemToLoc< 1, OffsetT, false >, LoopedElemToLoc< 1, OffsetT, true >
  • lowest() : metal::_numeric_limits_impl< bfloat16_t >, mlx::core::numeric_limits< bfloat16_t >, mlx::core::numeric_limits< float16_t >
    • +
  • LUF() : mlx::core::LUF
    • diff --git a/docs/build/html/functions_m.html b/docs/build/html/functions_m.html index cb9fe428e..ed2449bd4 100644 --- a/docs/build/html/functions_m.html +++ b/docs/build/html/functions_m.html @@ -115,7 +115,7 @@ $(function(){initNavTree('functions_m.html',''); initResizable(true); });
  • mat_type : mlx::steel::BaseMMAFrag< T, 8, 8 >, mlx::steel::MMATile< T, kTileRows_, kTileCols_, MMAFrag_ >
  • Matmul() : mlx::core::Matmul
  • Max : mlx::core::distributed::AllReduce, mlx::core::Reduce, mlx::core::Scan, mlx::core::Scatter
    • -
  • max : Limits< U >, Limits< bfloat16_t >, Limits< bool >, Limits< complex64_t >, Limits< float >, Limits< half >, Limits< int16_t >, Limits< int32_t >, Limits< int64_t >, Limits< int8_t >, Limits< uint16_t >, Limits< uint32_t >, Limits< uint64_t >, Limits< uint8_t >, metal::_numeric_limits_impl< bfloat16_t >, mlx::core::finfo, mlx::core::numeric_limits< bfloat16_t >, mlx::core::numeric_limits< float16_t >
    • +
  • max : Limits< U >, Limits< bfloat16_t >, Limits< bool >, Limits< complex64_t >, Limits< float >, Limits< half >, Limits< int16_t >, Limits< int32_t >, Limits< int64_t >, Limits< int8_t >, Limits< uint16_t >, Limits< uint32_t >, Limits< uint64_t >, Limits< uint8_t >, metal::_numeric_limits_impl< bfloat16_t >, mlx::core::finfo, mlx::core::numeric_limits< bfloat16_t >, mlx::core::numeric_limits< float16_t >
  • max_digits10 : metal::_numeric_limits_impl< bfloat16_t >
  • max_exponent : metal::_numeric_limits_impl< bfloat16_t >
  • max_exponent10 : metal::_numeric_limits_impl< bfloat16_t >
    • @@ -124,7 +124,7 @@ $(function(){initNavTree('functions_m.html',''); initResizable(true); });
  • merge_partition() : BlockMergeSort< ValT, IdxT, ARG_SORT, BLOCK_THREADS, N_PER_THREAD, CompareOp >, KernelMultiBlockMergeSort< ValT, IdxT, ARG_SORT, BLOCK_THREADS, N_PER_THREAD, CompareOp >
  • merge_step() : BlockMergeSort< ValT, IdxT, ARG_SORT, BLOCK_THREADS, N_PER_THREAD, CompareOp >
  • Min : mlx::core::distributed::AllReduce, mlx::core::Reduce, mlx::core::Scan, mlx::core::Scatter
    • -
  • min : Limits< U >, Limits< bfloat16_t >, Limits< bool >, Limits< complex64_t >, Limits< float >, Limits< half >, Limits< int16_t >, Limits< int32_t >, Limits< int64_t >, Limits< int8_t >, Limits< uint16_t >, Limits< uint32_t >, Limits< uint64_t >, Limits< uint8_t >, metal::_numeric_limits_impl< bfloat16_t >, mlx::core::finfo
    • +
  • min : Limits< U >, Limits< bfloat16_t >, Limits< bool >, Limits< complex64_t >, Limits< float >, Limits< half >, Limits< int16_t >, Limits< int32_t >, Limits< int64_t >, Limits< int8_t >, Limits< uint16_t >, Limits< uint32_t >, Limits< uint64_t >, Limits< uint8_t >, metal::_numeric_limits_impl< bfloat16_t >, mlx::core::finfo
  • min_exponent : metal::_numeric_limits_impl< bfloat16_t >
  • min_exponent10 : metal::_numeric_limits_impl< bfloat16_t >
  • Minimum() : mlx::core::Minimum
    • diff --git a/docs/build/html/functions_o.html b/docs/build/html/functions_o.html index ca50cfdb1..21b768e76 100644 --- a/docs/build/html/functions_o.html +++ b/docs/build/html/functions_o.html @@ -121,7 +121,7 @@ $(function(){initNavTree('functions_o.html',''); initResizable(true); });
  • operator Val() : mlx::core::Dtype
  • operator value_type() : mlx::steel::integral_constant< T, v >
  • operator!= : mlx::core::array::ArrayIterator
    • -
  • operator()() : Abs, Add, ArcCos, ArcCosh, ArcSin, ArcSinh, ArcTan2, ArcTan, ArcTanh, BitwiseAnd, BitwiseOr, BitwiseXor, Ceil, Conjugate, Cos, Cosh, CumMax< U >, CumMin< U >, CumProd< bool >, Divide, DivMod, Equal, Erf, ErfInv, Exp, Expm1, Floor, FloorDivide, Greater, GreaterEqual, Imag, LeftShift, Less, LessEqual, LessThan< T >, Log10, Log1p, Log2, Log, LogAddExp, LogicalAnd, LogicalNot, LogicalOr, Maximum, Minimum, mlx::core::detail::Abs, mlx::core::detail::Add, mlx::core::detail::ArcCos, mlx::core::detail::ArcCosh, mlx::core::detail::ArcSin, mlx::core::detail::ArcSinh, mlx::core::detail::ArcTan2, mlx::core::detail::ArcTan, mlx::core::detail::ArcTanh, mlx::core::detail::BitwiseAnd, mlx::core::detail::BitwiseOr, mlx::core::detail::BitwiseXor, mlx::core::detail::Ceil, mlx::core::detail::Conjugate, mlx::core::detail::Cos, mlx::core::detail::Cosh, mlx::core::detail::Divide, mlx::core::detail::Equal, mlx::core::detail::Erf, mlx::core::detail::ErfInv, mlx::core::detail::Exp, mlx::core::detail::Expm1, mlx::core::detail::Floor, mlx::core::detail::Greater, mlx::core::detail::GreaterEqual, mlx::core::detail::Imag, mlx::core::detail::LeftShift, mlx::core::detail::Less, mlx::core::detail::LessEqual, mlx::core::detail::Log10, mlx::core::detail::Log1p, mlx::core::detail::Log2, mlx::core::detail::Log, mlx::core::detail::LogAddExp, mlx::core::detail::LogicalAnd, mlx::core::detail::LogicalNot, mlx::core::detail::LogicalOr, mlx::core::detail::Maximum, mlx::core::detail::Minimum, mlx::core::detail::Multiply, mlx::core::detail::NaNEqual, mlx::core::detail::Negative, mlx::core::detail::NotEqual, mlx::core::detail::Power, mlx::core::detail::Real, mlx::core::detail::Remainder, mlx::core::detail::RightShift, mlx::core::detail::Round, mlx::core::detail::Rsqrt, mlx::core::detail::Select, mlx::core::detail::Sigmoid, mlx::core::detail::Sign, mlx::core::detail::Sin, mlx::core::detail::Sinh, mlx::core::detail::Sqrt, mlx::core::detail::Square, mlx::core::detail::Subtract, mlx::core::detail::Tan, mlx::core::detail::Tanh, mlx::core::FunctionExporter, mlx::core::ImportedFunction, mlx::core::ScalarVector< Op >, mlx::core::VectorScalar< Op >, mlx::core::VectorVector< Op >, Multiply, NaNEqual, Negative, NotEqual, pocketfft::detail::ExecC2C, pocketfft::detail::ExecDcst, pocketfft::detail::ExecHartley, pocketfft::detail::ExecR2R, Power, Real, Remainder, RightShift, Round, Rsqrt, Select, Sigmoid, Sign, Sin, Sinh, Sqrt, Square, Subtract, Tan, Tanh
    • +
  • operator()() : Abs, Add, ArcCos, ArcCosh, ArcSin, ArcSinh, ArcTan2, ArcTan, ArcTanh, BitwiseAnd, BitwiseInvert, BitwiseOr, BitwiseXor, Ceil, Conjugate, Cos, Cosh, CumMax< U >, CumMin< U >, CumProd< bool >, Divide, DivMod, Equal, Erf, ErfInv, Exp, Expm1, Floor, FloorDivide, Greater, GreaterEqual, Imag, LeftShift, Less, LessEqual, LessThan< T >, Log10, Log1p, Log2, Log, LogAddExp, LogicalAnd, LogicalNot, LogicalOr, Maximum, Minimum, mlx::core::detail::Abs, mlx::core::detail::Add, mlx::core::detail::ArcCos, mlx::core::detail::ArcCosh, mlx::core::detail::ArcSin, mlx::core::detail::ArcSinh, mlx::core::detail::ArcTan2, mlx::core::detail::ArcTan, mlx::core::detail::ArcTanh, mlx::core::detail::BitwiseAnd, mlx::core::detail::BitwiseInvert, mlx::core::detail::BitwiseOr, mlx::core::detail::BitwiseXor, mlx::core::detail::Ceil, mlx::core::detail::Conjugate, mlx::core::detail::Cos, mlx::core::detail::Cosh, mlx::core::detail::Divide, mlx::core::detail::Equal, mlx::core::detail::Erf, mlx::core::detail::ErfInv, mlx::core::detail::Exp, mlx::core::detail::Expm1, mlx::core::detail::Floor, mlx::core::detail::Greater, mlx::core::detail::GreaterEqual, mlx::core::detail::Imag, mlx::core::detail::LeftShift, mlx::core::detail::Less, mlx::core::detail::LessEqual, mlx::core::detail::Log10, mlx::core::detail::Log1p, mlx::core::detail::Log2, mlx::core::detail::Log, mlx::core::detail::LogAddExp, mlx::core::detail::LogicalAnd, mlx::core::detail::LogicalNot, mlx::core::detail::LogicalOr, mlx::core::detail::Maximum, mlx::core::detail::Minimum, mlx::core::detail::Multiply, mlx::core::detail::NaNEqual, mlx::core::detail::Negative, mlx::core::detail::NotEqual, mlx::core::detail::Power, mlx::core::detail::Real, mlx::core::detail::Remainder, mlx::core::detail::RightShift, mlx::core::detail::Round, mlx::core::detail::Rsqrt, mlx::core::detail::Select, mlx::core::detail::Sigmoid, mlx::core::detail::Sign, mlx::core::detail::Sin, mlx::core::detail::Sinh, mlx::core::detail::Sqrt, mlx::core::detail::Square, mlx::core::detail::Subtract, mlx::core::detail::Tan, mlx::core::detail::Tanh, mlx::core::FunctionExporter, mlx::core::ImportedFunction, mlx::core::ScalarVector< Op >, mlx::core::VectorScalar< Op >, mlx::core::VectorVector< Op >, Multiply, NaNEqual, Negative, NotEqual, pocketfft::detail::ExecC2C, pocketfft::detail::ExecDcst, pocketfft::detail::ExecHartley, pocketfft::detail::ExecR2R, Power, Real, Remainder, RightShift, Round, Rsqrt, Select, Sigmoid, Sign, Sin, Sinh, Sqrt, Square, Subtract, Tan, Tanh
  • operator*() : mlx::core::array::ArrayIterator, pocketfft::detail::cmplx< T >
  • operator*=() : pocketfft::detail::cmplx< T >
  • operator+() : mlx::core::array::ArrayIterator, pocketfft::detail::cmplx< T >
    • @@ -139,7 +139,7 @@ $(function(){initNavTree('functions_o.html',''); initResizable(true); });
  • out_of_bounds() : ReadWriter< in_T, out_T, step, four_step_real >
  • out_strides : MLXConvParams< NDIM >
  • output_shape() : mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::ExpandDims, mlx::core::Flatten, mlx::core::Reshape, mlx::core::Squeeze, mlx::core::Unflatten
    • -
  • output_shapes() : mlx::core::Abs, mlx::core::Add, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::Flatten, mlx::core::Floor, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten
    • +
  • output_shapes() : mlx::core::Abs, mlx::core::Add, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::AffineQuantize, mlx::core::Flatten, mlx::core::Floor, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten
  • outputs() : mlx::core::array, mlx::core::CommandEncoder, mlx::core::metal::CommandEncoder, mlx::core::metal::DeviceStream
  • overwrite_descriptor() : mlx::core::array
    • diff --git a/docs/build/html/functions_p.html b/docs/build/html/functions_p.html index a6cae87d8..afc13a670 100644 --- a/docs/build/html/functions_p.html +++ b/docs/build/html/functions_p.html @@ -120,7 +120,7 @@ $(function(){initNavTree('functions_p.html',''); initResizable(true); });
  • primitive() : mlx::core::array
  • primitive_id() : mlx::core::array
  • primitive_ptr() : mlx::core::array
    • -
  • print() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::PrintFormatter, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
    • +
  • print() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::Arange, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Load, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::LUF, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::PrintFormatter, mlx::core::QRF, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
  • Prod : mlx::core::distributed::AllReduce, mlx::core::Reduce, mlx::core::Scan, mlx::core::Scatter
  • prod() : pocketfft::detail::util
  • ptr() : mlx::core::allocator::Buffer, mlx::core::metal::Buffer
    • diff --git a/docs/build/html/functions_v.html b/docs/build/html/functions_v.html index e513612cb..e6a5a12ac 100644 --- a/docs/build/html/functions_v.html +++ b/docs/build/html/functions_v.html @@ -119,7 +119,7 @@ $(function(){initNavTree('functions_v.html',''); initResizable(true); });
  • VectorVector() : mlx::core::VectorVector< Op >
  • View() : mlx::core::View
  • vjp() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::AsStrided, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BlockMaskedMM, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Contiguous, mlx::core::Convolution, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::Depends, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::fast::LayerNorm, mlx::core::fast::RMSNorm, mlx::core::fast::RoPE, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherMM, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::Subtract, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten
    • -
  • vmap() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
    • +
  • vmap() : mlx::core::Abs, mlx::core::Add, mlx::core::AddMM, mlx::core::ArcCos, mlx::core::ArcCosh, mlx::core::ArcSin, mlx::core::ArcSinh, mlx::core::ArcTan2, mlx::core::ArcTan, mlx::core::ArcTanh, mlx::core::ArgPartition, mlx::core::ArgReduce, mlx::core::ArgSort, mlx::core::AsType, mlx::core::BitwiseBinary, mlx::core::BitwiseInvert, mlx::core::Broadcast, mlx::core::BroadcastAxes, mlx::core::Ceil, mlx::core::Cholesky, mlx::core::Compiled, mlx::core::Concatenate, mlx::core::Conjugate, mlx::core::Contiguous, mlx::core::Copy, mlx::core::Cos, mlx::core::Cosh, mlx::core::CustomTransforms, mlx::core::distributed::AllGather, mlx::core::distributed::AllReduce, mlx::core::distributed::Send, mlx::core::Divide, mlx::core::DivMod, mlx::core::DynamicSlice, mlx::core::DynamicSliceUpdate, mlx::core::Eigh, mlx::core::Equal, mlx::core::Erf, mlx::core::ErfInv, mlx::core::Exp, mlx::core::ExpandDims, mlx::core::Expm1, mlx::core::fast::Custom, mlx::core::FFT, mlx::core::Flatten, mlx::core::Floor, mlx::core::Full, mlx::core::Gather, mlx::core::GatherAxis, mlx::core::GatherQMM, mlx::core::Greater, mlx::core::GreaterEqual, mlx::core::Hadamard, mlx::core::Imag, mlx::core::Inverse, mlx::core::Less, mlx::core::LessEqual, mlx::core::Log1p, mlx::core::Log, mlx::core::LogAddExp, mlx::core::LogicalAnd, mlx::core::LogicalNot, mlx::core::LogicalOr, mlx::core::Matmul, mlx::core::Maximum, mlx::core::Minimum, mlx::core::Multiply, mlx::core::Negative, mlx::core::NotEqual, mlx::core::NumberOfElements, mlx::core::Pad, mlx::core::Partition, mlx::core::Power, mlx::core::Primitive, mlx::core::QuantizedMatmul, mlx::core::RandomBits, mlx::core::Real, mlx::core::Reduce, mlx::core::Remainder, mlx::core::Reshape, mlx::core::Round, mlx::core::Scan, mlx::core::Scatter, mlx::core::ScatterAxis, mlx::core::Select, mlx::core::Sigmoid, mlx::core::Sign, mlx::core::Sin, mlx::core::Sinh, mlx::core::Slice, mlx::core::SliceUpdate, mlx::core::Softmax, mlx::core::Sort, mlx::core::Split, mlx::core::Sqrt, mlx::core::Square, mlx::core::Squeeze, mlx::core::StopGradient, mlx::core::Subtract, mlx::core::SVD, mlx::core::Tan, mlx::core::Tanh, mlx::core::Transpose, mlx::core::Unflatten, mlx::core::View
    • diff --git a/docs/build/html/functions_vars_b.html b/docs/build/html/functions_vars_b.html index cc68ed1be..2228eb02d 100644 --- a/docs/build/html/functions_vars_b.html +++ b/docs/build/html/functions_vars_b.html @@ -132,6 +132,7 @@ $(function(){initNavTree('functions_vars_b.html',''); initResizable(true); });
  • buf : ReadWriter< in_T, out_T, step, four_step_real >
  • buffer : mlx::core::array::Data, mlx::core::metal::DeviceStream
  • buffer_ops : mlx::core::metal::DeviceStream
    • +
  • buffer_sizes : mlx::core::metal::DeviceStream
  • buffers : Indices< IdxT, NIDX >
  • bytes_per_pack : QuantizedBlockLoader< T, BROWS, BCOLS, dst_ld, reduction_dim, tgp_size, group_size, bits >
    • diff --git a/docs/build/html/functions_vars_m.html b/docs/build/html/functions_vars_m.html index 8d8d6a910..05e98c931 100644 --- a/docs/build/html/functions_vars_m.html +++ b/docs/build/html/functions_vars_m.html @@ -108,11 +108,11 @@ $(function(){initNavTree('functions_vars_m.html',''); initResizable(true); });
  • M : mlx::steel::GEMMParams, mlx::steel::GEMMSpiltKParams, mlx::steel::ImplicitGemmConv2DParams
  • mask_h : mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >
  • mask_w : mlx::steel::Conv2DInputBlockLoaderSmallFilter< T, BM, BN, BK, tgp_size, tgp_padding >
    • -
  • max : Limits< U >, Limits< bfloat16_t >, Limits< bool >, Limits< complex64_t >, Limits< float >, Limits< half >, Limits< int16_t >, Limits< int32_t >, Limits< int64_t >, Limits< int8_t >, Limits< uint16_t >, Limits< uint32_t >, Limits< uint64_t >, Limits< uint8_t >, mlx::core::finfo
    • +
  • max : Limits< U >, Limits< bfloat16_t >, Limits< bool >, Limits< complex64_t >, Limits< float >, Limits< half >, Limits< int16_t >, Limits< int32_t >, Limits< int64_t >, Limits< int8_t >, Limits< uint16_t >, Limits< uint32_t >, Limits< uint64_t >, Limits< uint8_t >, mlx::core::finfo
  • max_digits10 : metal::_numeric_limits_impl< bfloat16_t >
  • max_exponent : metal::_numeric_limits_impl< bfloat16_t >
  • max_exponent10 : metal::_numeric_limits_impl< bfloat16_t >
    • -
  • min : Limits< U >, Limits< bfloat16_t >, Limits< bool >, Limits< complex64_t >, Limits< float >, Limits< half >, Limits< int16_t >, Limits< int32_t >, Limits< int64_t >, Limits< int8_t >, Limits< uint16_t >, Limits< uint32_t >, Limits< uint64_t >, Limits< uint8_t >, mlx::core::finfo
    • +
  • min : Limits< U >, Limits< bfloat16_t >, Limits< bool >, Limits< complex64_t >, Limits< float >, Limits< half >, Limits< int16_t >, Limits< int32_t >, Limits< int64_t >, Limits< int8_t >, Limits< uint16_t >, Limits< uint32_t >, Limits< uint64_t >, Limits< uint8_t >, mlx::core::finfo
  • min_exponent : metal::_numeric_limits_impl< bfloat16_t >
  • min_exponent10 : metal::_numeric_limits_impl< bfloat16_t >
  • mtx : mlx::core::scheduler::StreamThread
    • diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html index 92c582f30..bf0667e43 100644 --- a/docs/build/html/genindex.html +++ b/docs/build/html/genindex.html @@ -7,7 +7,7 @@ - Index — MLX 0.22.1 documentation + Index — MLX 0.23.0 documentation @@ -38,7 +38,7 @@ - + @@ -48,7 +48,7 @@ - + @@ -129,8 +129,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home @@ -275,6 +275,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -485,6 +486,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
  • log10 (C++ function)
    • - - +
  • LSTM (class in mlx.nn) +
    • +
  • lu() (in module mlx.core.linalg) +
    • +
  • lu_factor() (in module mlx.core.linalg)
    • @@ -1866,10 +1879,10 @@
  • operator/ (C++ function), [1], [2]
    • - - + - +
  • Metal
  • Metal
    diff --git a/docs/build/html/namespacemembers_func_m.html b/docs/build/html/namespacemembers_func_m.html index c40fa6b97..7a2f310c7 100644 --- a/docs/build/html/namespacemembers_func_m.html +++ b/docs/build/html/namespacemembers_func_m.html @@ -114,7 +114,8 @@ $(function(){initNavTree('namespacemembers_func_m.html',''); initResizable(true)
  • matmul() : mlx::core
  • max() : metal::fast, metal, metal::precise, mlx::core, mlx::core::simd
  • max3() : metal::fast, metal, metal::precise
    • -
  • max_ops_per_buffer() : mlx::core::env
    • +
  • max_mb_per_buffer() : mlx::core::env
    • +
  • max_ops_per_buffer() : mlx::core::env
  • maximum() : mlx::core, mlx::core::simd
  • mean() : mlx::core
  • median3() : metal::fast, metal, metal::precise
    • diff --git a/docs/build/html/namespacemembers_func_o.html b/docs/build/html/namespacemembers_func_o.html index e2bd4e77c..1197176fc 100644 --- a/docs/build/html/namespacemembers_func_o.html +++ b/docs/build/html/namespacemembers_func_o.html @@ -133,6 +133,7 @@ $(function(){initNavTree('namespacemembers_func_o.html',''); initResizable(true)
  • operator|() : mlx::core, mlx::core::simd
  • operator|=() : mlx::core
  • operator||() : mlx::core, mlx::core::simd, mlx::steel
    • +
  • operator~() : mlx::core, mlx::core::simd
  • outer() : mlx::core
    • diff --git a/docs/build/html/namespacemembers_func_s.html b/docs/build/html/namespacemembers_func_s.html index 4c020879a..16ec089f2 100644 --- a/docs/build/html/namespacemembers_func_s.html +++ b/docs/build/html/namespacemembers_func_s.html @@ -162,6 +162,8 @@ $(function(){initNavTree('namespacemembers_func_s.html',''); initResizable(true)
  • slice_gpu() : mlx::core
  • slice_update() : mlx::core
  • softmax() : mlx::core::metal, mlx::core
    • +
  • solve() : mlx::core::linalg
    • +
  • solve_triangular() : mlx::core::linalg
  • sort() : mlx::core::metal, mlx::core
  • special_mul() : pocketfft::detail
  • split() : mlx::core::random, mlx::core
    • diff --git a/docs/build/html/namespacemembers_func_u.html b/docs/build/html/namespacemembers_func_u.html index ed2f86a6d..42d1a8683 100644 --- a/docs/build/html/namespacemembers_func_u.html +++ b/docs/build/html/namespacemembers_func_u.html @@ -107,12 +107,14 @@ $(function(){initNavTree('namespacemembers_func_u.html',''); initResizable(true)

    - u -

    diff --git a/docs/build/html/namespacemembers_l.html b/docs/build/html/namespacemembers_l.html index ea9a44d40..d181b82db 100644 --- a/docs/build/html/namespacemembers_l.html +++ b/docs/build/html/namespacemembers_l.html @@ -124,6 +124,8 @@ $(function(){initNavTree('namespacemembers_l.html',''); initResizable(true); });
  • logical_not() : mlx::core
  • logical_or() : mlx::core
  • logsumexp() : mlx::core
    • +
  • lu() : mlx::core::linalg
    • +
  • lu_factor() : mlx::core::linalg
    • diff --git a/docs/build/html/namespacemembers_m.html b/docs/build/html/namespacemembers_m.html index 1190416b5..a817239ba 100644 --- a/docs/build/html/namespacemembers_m.html +++ b/docs/build/html/namespacemembers_m.html @@ -114,7 +114,8 @@ $(function(){initNavTree('namespacemembers_m.html',''); initResizable(true); });
  • matmul() : mlx::core
  • max() : metal::fast, metal, metal::precise, mlx::core, mlx::core::simd
  • max3() : metal::fast, metal, metal::precise
    • -
  • max_ops_per_buffer() : mlx::core::env
    • +
  • max_mb_per_buffer() : mlx::core::env
    • +
  • max_ops_per_buffer() : mlx::core::env
  • max_size : mlx::core::simd
  • max_size< double > : mlx::core::simd
  • max_size< float > : mlx::core::simd
    • diff --git a/docs/build/html/namespacemembers_o.html b/docs/build/html/namespacemembers_o.html index d1d27ef9b..9f4521ff9 100644 --- a/docs/build/html/namespacemembers_o.html +++ b/docs/build/html/namespacemembers_o.html @@ -133,6 +133,7 @@ $(function(){initNavTree('namespacemembers_o.html',''); initResizable(true); });
  • operator|() : mlx::core, mlx::core::simd
  • operator|=() : mlx::core
  • operator||() : mlx::core, mlx::core::simd, mlx::steel
    • +
  • operator~() : mlx::core, mlx::core::simd
  • outer() : mlx::core
    • diff --git a/docs/build/html/namespacemembers_s.html b/docs/build/html/namespacemembers_s.html index d21fe2ed0..4ba27edbd 100644 --- a/docs/build/html/namespacemembers_s.html +++ b/docs/build/html/namespacemembers_s.html @@ -168,6 +168,8 @@ $(function(){initNavTree('namespacemembers_s.html',''); initResizable(true); });
  • slice_gpu() : mlx::core
  • slice_update() : mlx::core
  • softmax() : mlx::core::metal, mlx::core
    • +
  • solve() : mlx::core::linalg
    • +
  • solve_triangular() : mlx::core::linalg
  • sort() : mlx::core::metal, mlx::core
  • special_mul() : pocketfft::detail
  • split() : mlx::core::random, mlx::core
    • diff --git a/docs/build/html/namespacemembers_u.html b/docs/build/html/namespacemembers_u.html index ccb3ada5c..bf5525d75 100644 --- a/docs/build/html/namespacemembers_u.html +++ b/docs/build/html/namespacemembers_u.html @@ -111,12 +111,14 @@ $(function(){initNavTree('namespacemembers_u.html',''); initResizable(true); });
  • uint8 : mlx::core
  • unary() : mlx::core::metal, mlx::core
  • unary_fp() : mlx::core
    • +
  • unary_int() : mlx::core
  • unary_op() : mlx::core
  • unary_op_gpu() : mlx::core
  • unary_op_gpu_inplace() : mlx::core
  • unary_ops() : mlx::core::metal
  • unflatten() : mlx::core
  • uniform() : mlx::core::random
    • +
  • unsafe_weak_copy() : mlx::core
  • unsignedinteger : mlx::core
  • utils() : mlx::core::metal
    • diff --git a/docs/build/html/namespacemembers_vars.html b/docs/build/html/namespacemembers_vars.html index 7a1d24bdc..05f70e49b 100644 --- a/docs/build/html/namespacemembers_vars.html +++ b/docs/build/html/namespacemembers_vars.html @@ -122,6 +122,7 @@ $(function(){initNavTree('namespacemembers_vars.html',''); initResizable(true);

    - f -

    diff --git a/docs/build/html/namespacemlx_1_1core.html b/docs/build/html/namespacemlx_1_1core.html index bf353281c..676a5f60e 100644 --- a/docs/build/html/namespacemlx_1_1core.html +++ b/docs/build/html/namespacemlx_1_1core.html @@ -182,6 +182,8 @@ Classes   class  BitwiseBinary   +class  BitwiseInvert +  class  BlockMaskedMM   class  Broadcast @@ -303,6 +305,8 @@ Classes   class  LogicalOr   +class  LUF +  class  Matmul   class  Maximum @@ -323,6 +327,8 @@ Classes   struct  numeric_limits< bfloat16_t >   +struct  numeric_limits< double > +  struct  numeric_limits< float >   struct  numeric_limits< float16_t > @@ -620,6 +626,9 @@ Functions template<typename Op> void unary_fp (const array &a, array &out, Op op)   +template<typename Op> +void unary_int (const array &a, array &out, Op op) +  void binary_op_gpu (const std::vector< array > &inputs, std::vector< array > &outputs, const std::string &op, const Stream &s)   void binary_op_gpu (const std::vector< array > &inputs, array &out, const std::string &op, const Stream &s) @@ -739,11 +748,14 @@ Functions template<typename T, typename... Args> void concatenate (std::string &acc, T first, Args... args)   +array unsafe_weak_copy (const array &x) + Get a new array that refers to the same data but has a non-owning pointer to them.
    +  std::function< std::vector< array >(const std::vector< array > &)> compile (std::function< std::vector< array >(const std::vector< array > &)> fun, bool shapeless=false)  Compile takes a function and returns a compiled function.
      -std::function< std::vector< array >(const std::vector< array > &)> compile (std::vector< array >(fun)(const std::vector< array > &), bool shapeless=false) -  +std::function< std::vector< array >(const std::vector< array > &)> compile (std::vector< array >(*fun)(const std::vector< array > &), bool shapeless=false) +  template<typename F> std::function< std::vector< array >(const std::vector< array > &)> compile (F &&f, bool shapeless=false)   @@ -1674,6 +1686,11 @@ Functions   array operator>> (const array &a, const array &b)   +array bitwise_invert (const array &a, StreamOrDevice s={}) + Invert the bits.
    +  +array operator~ (const array &a) +  array view (const array &a, const Dtype &dtype, StreamOrDevice s={})   array roll (const array &a, int shift, StreamOrDevice s={}) @@ -2571,6 +2588,8 @@ Variables   constexpr Dtype float32 {Dtype::Val::float32, sizeof(float)}   +constexpr Dtype float64 {Dtype::Val::float64, sizeof(double)} +  constexpr Dtype bfloat16 {Dtype::Val::bfloat16, sizeof(uint16_t)}   constexpr Dtype complex64 {Dtype::Val::complex64, sizeof(complex64_t)} @@ -3702,8 +3721,8 @@ template<typename F> - -

    ◆ compile() [3/3]

    + +

    ◆ compile() [3/3]

    @@ -3711,7 +3730,7 @@ template<typename F>
    std::function< std::vector< array >(const std::vector< array > &)> mlx::core::compile ( - std::vector< array > fun)(const std::vector< array > &, + std::vector< array >(* fun )(const std::vector< array > &), @@ -19183,6 +19202,34 @@ template<typename Op>
    +
    + + +

    ◆ unary_int()

    + +
    +
    +
    +template<typename Op>
    + + + + + + + + + + + + + + + + +
    void mlx::core::unary_int (const array & a,
    array & out,
    Op op )
    +
    +
    @@ -19311,6 +19358,33 @@ template<typename T, typename U = T, typename Op>
    +
    + + +

    ◆ unsafe_weak_copy()

    + +
    +
    + + + + + +
    + + + + + + + +
    array mlx::core::unsafe_weak_copy (const array & x)
    +     		+inline
    +
    + +

    Get a new array that refers to the same data but has a non-owning pointer to them.

    +
    @@ -19739,7 +19813,7 @@ template<typename T>
    Initial value:
    =
    Dtype::Category::complexfloating
    -
    mlx::core::Dtype::Category::complexfloating
    @ complexfloating
    Definition dtype.h:40
    +
    mlx::core::Dtype::Category::complexfloating
    @ complexfloating
    Definition dtype.h:41
    @@ -19785,6 +19859,28 @@ template<typename T>
    +
    + + +

    ◆ float64

    + +
    +
    + + + + + +
    + + + + +
    Dtype mlx::core::float64 {Dtype::Val::float64, sizeof(double)}
    +     		+inlineconstexpr
    +
    +
    @@ -20299,7 +20395,7 @@ template<typename... T>
    Initial value:
    =
    Dtype::Category::unsignedinteger
    -
    mlx::core::Dtype::Category::unsignedinteger
    @ unsignedinteger
    Definition dtype.h:44
    +
    mlx::core::Dtype::Category::unsignedinteger
    @ unsignedinteger
    Definition dtype.h:45
    diff --git a/docs/build/html/namespacemlx_1_1core.js b/docs/build/html/namespacemlx_1_1core.js index 0928c9dbe..b1012d4a3 100644 --- a/docs/build/html/namespacemlx_1_1core.js +++ b/docs/build/html/namespacemlx_1_1core.js @@ -6,7 +6,8 @@ var namespacemlx_1_1core = [ "env", "namespacemlx_1_1core_1_1env.html", [ [ "bfs_max_width", "namespacemlx_1_1core_1_1env.html#ac3266e1259a64c8b56bdc6c7029179f2", null ], [ "get_var", "namespacemlx_1_1core_1_1env.html#a0efecbf9efe695adafad12b5a4945df3", null ], - [ "max_ops_per_buffer", "namespacemlx_1_1core_1_1env.html#aedbf4e739553024c33dd0094dd9107aa", null ], + [ "max_mb_per_buffer", "namespacemlx_1_1core_1_1env.html#afc55d7755889157ded85d52cde14f413", null ], + [ "max_ops_per_buffer", "namespacemlx_1_1core_1_1env.html#aa532471d4506e11e0da615b9d6451083", null ], [ "metal_fast_synch", "namespacemlx_1_1core_1_1env.html#afa1ecf087fe0c633d5460ddb2c31c945", null ] ] ], [ "fast", "namespacemlx_1_1core_1_1fast.html", "namespacemlx_1_1core_1_1fast" ], @@ -48,6 +49,8 @@ var namespacemlx_1_1core = [ "eigh", "namespacemlx_1_1core_1_1linalg.html#a2180be504f639fd471ea622641c1b0ca", null ], [ "eigvalsh", "namespacemlx_1_1core_1_1linalg.html#a00c8e24432b0773dac64b8602bd142ba", null ], [ "inv", "namespacemlx_1_1core_1_1linalg.html#ad966a0b6bff176c9f933534ed62389a2", null ], + [ "lu", "namespacemlx_1_1core_1_1linalg.html#a7a426a92cb02c0d125e41f8915e66f7f", null ], + [ "lu_factor", "namespacemlx_1_1core_1_1linalg.html#abf10561bef3450b83a45aef161ee8b6e", null ], [ "norm", "namespacemlx_1_1core_1_1linalg.html#aba765b8e95e9a1d33d31f727a185919d", null ], [ "norm", "namespacemlx_1_1core_1_1linalg.html#acaa85b4146821c268abecec2422c02d2", null ], [ "norm", "namespacemlx_1_1core_1_1linalg.html#a229018071d5602e38d6248230f334a10", null ], @@ -56,6 +59,8 @@ var namespacemlx_1_1core = [ "norm", "namespacemlx_1_1core_1_1linalg.html#a44250cff34238f01471fd61e76036f03", null ], [ "pinv", "namespacemlx_1_1core_1_1linalg.html#ad9f8348091e5ff4f74ad456e9fbd3e01", null ], [ "qr", "namespacemlx_1_1core_1_1linalg.html#ae6d97829459353fe3b31c8a0867c0ca2", null ], + [ "solve", "namespacemlx_1_1core_1_1linalg.html#a66590bfcec381e952b27630da0a31953", null ], + [ "solve_triangular", "namespacemlx_1_1core_1_1linalg.html#a5e6e53f7a04688baa1329d166511febe", null ], [ "svd", "namespacemlx_1_1core_1_1linalg.html#a64364b880e99914cf47bf756fa8dbaf0", null ], [ "tri_inv", "namespacemlx_1_1core_1_1linalg.html#aba1994571326326717b5b5e38c2e0661", null ] ] ], @@ -83,6 +88,7 @@ var namespacemlx_1_1core = [ "AsStrided", "classmlx_1_1core_1_1_as_strided.html", "classmlx_1_1core_1_1_as_strided" ], [ "AsType", "classmlx_1_1core_1_1_as_type.html", "classmlx_1_1core_1_1_as_type" ], [ "BitwiseBinary", "classmlx_1_1core_1_1_bitwise_binary.html", "classmlx_1_1core_1_1_bitwise_binary" ], + [ "BitwiseInvert", "classmlx_1_1core_1_1_bitwise_invert.html", "classmlx_1_1core_1_1_bitwise_invert" ], [ "BlockMaskedMM", "classmlx_1_1core_1_1_block_masked_m_m.html", "classmlx_1_1core_1_1_block_masked_m_m" ], [ "Broadcast", "classmlx_1_1core_1_1_broadcast.html", "classmlx_1_1core_1_1_broadcast" ], [ "BroadcastAxes", "classmlx_1_1core_1_1_broadcast_axes.html", "classmlx_1_1core_1_1_broadcast_axes" ], @@ -143,6 +149,7 @@ var namespacemlx_1_1core = [ "LogicalAnd", "classmlx_1_1core_1_1_logical_and.html", "classmlx_1_1core_1_1_logical_and" ], [ "LogicalNot", "classmlx_1_1core_1_1_logical_not.html", "classmlx_1_1core_1_1_logical_not" ], [ "LogicalOr", "classmlx_1_1core_1_1_logical_or.html", "classmlx_1_1core_1_1_logical_or" ], + [ "LUF", "classmlx_1_1core_1_1_l_u_f.html", "classmlx_1_1core_1_1_l_u_f" ], [ "Matmul", "classmlx_1_1core_1_1_matmul.html", "classmlx_1_1core_1_1_matmul" ], [ "Maximum", "classmlx_1_1core_1_1_maximum.html", "classmlx_1_1core_1_1_maximum" ], [ "Minimum", "classmlx_1_1core_1_1_minimum.html", "classmlx_1_1core_1_1_minimum" ], @@ -153,6 +160,7 @@ var namespacemlx_1_1core = [ "NumberOfElements", "classmlx_1_1core_1_1_number_of_elements.html", "classmlx_1_1core_1_1_number_of_elements" ], [ "numeric_limits", "structmlx_1_1core_1_1numeric__limits.html", null ], [ "numeric_limits< bfloat16_t >", "structmlx_1_1core_1_1numeric__limits_3_01bfloat16__t_01_4.html", "structmlx_1_1core_1_1numeric__limits_3_01bfloat16__t_01_4" ], + [ "numeric_limits< double >", "structmlx_1_1core_1_1numeric__limits_3_01double_01_4.html", null ], [ "numeric_limits< float >", "structmlx_1_1core_1_1numeric__limits_3_01float_01_4.html", null ], [ "numeric_limits< float16_t >", "structmlx_1_1core_1_1numeric__limits_3_01float16__t_01_4.html", "structmlx_1_1core_1_1numeric__limits_3_01float16__t_01_4" ], [ "Pad", "classmlx_1_1core_1_1_pad.html", "classmlx_1_1core_1_1_pad" ], @@ -310,6 +318,7 @@ var namespacemlx_1_1core = [ "binary_op_gpu_inplace", "namespacemlx_1_1core.html#a7e6af6624e322e7ad60a3873a66e18a3", null ], [ "binary_op_gpu_inplace", "namespacemlx_1_1core.html#a8616c0b7b0fc118a75400bc86404c367", null ], [ "bitwise_and", "group__ops.html#ga752fd2707dabb05d0308ba3d55346ada", null ], + [ "bitwise_invert", "group__ops.html#gaf1182ae7c049fbc9ee190f3e0fffbf83", null ], [ "bitwise_or", "group__ops.html#ga8af4f22c08c11c4ffab7e3d45e0f3cd6", null ], [ "bitwise_xor", "group__ops.html#ga3188638fba3a60e264baf69956a1e08b", null ], [ "block_masked_mm", "group__ops.html#ga6b76c8ea46b19e6866af155fa5910be6", null ], @@ -328,7 +337,7 @@ var namespacemlx_1_1core = [ "collapse_contiguous_dims", "namespacemlx_1_1core.html#a977c7c84de79ad67055ae2a89b7f6869", null ], [ "compile", "namespacemlx_1_1core.html#ace67713d269595f5f2265e46728a6f9c", null ], [ "compile", "namespacemlx_1_1core.html#a55933c6665de9f81059120d6b0de1c87", null ], - [ "compile", "namespacemlx_1_1core.html#a56de948c2dffbf35c88035bc1561db53", null ], + [ "compile", "namespacemlx_1_1core.html#abf57076f6d2351ba9f1e0cbe478f8afa", null ], [ "compiled_allocate_outputs", "namespacemlx_1_1core.html#ab8c3c4fc05745f586de922c8266f4fce", null ], [ "compiled_check_contiguity", "namespacemlx_1_1core.html#a562040f4a03f2c0a5d50eb9c8f14a8be", null ], [ "concatenate", "namespacemlx_1_1core.html#a76a2e310857f60f5ea6f1388d45b964d", null ], @@ -952,6 +961,7 @@ var namespacemlx_1_1core = [ "operator|=", "namespacemlx_1_1core.html#a2d8470b69cbbeefece08d3ffd46c0082", null ], [ "operator|=", "namespacemlx_1_1core.html#a359c6257097a304c00d41d64296ef4c9", null ], [ "operator||", "group__ops.html#ga27af56a98270d4d76d139f0f9171b83a", null ], + [ "operator~", "group__ops.html#ga849365a62878579a33b3d3ad09bbc7be", null ], [ "outer", "group__ops.html#ga866af24e10db2797e1c5a5986dbf6c0d", null ], [ "pad", "group__ops.html#gab2d5a17d3d5225fed34905e786c31c5f", null ], [ "pad", "group__ops.html#gab95ebd20bd7c6d1c840007cc020cbc0c", null ], @@ -1103,11 +1113,13 @@ var namespacemlx_1_1core = [ "type_to_name", "namespacemlx_1_1core.html#aef60e3a8d9c987c9c338b193673d2164", null ], [ "unary", "namespacemlx_1_1core.html#a6c8fdd03ef891d7f47804bf02e9a8507", null ], [ "unary_fp", "namespacemlx_1_1core.html#a76a2cb4634f5fd6970a8c3b3753d7a4a", null ], + [ "unary_int", "namespacemlx_1_1core.html#a078859db0d66ff77f97af6dc9764e8eb", null ], [ "unary_op", "namespacemlx_1_1core.html#ae20f207ad1ed3badc17cecf08f118b5e", null ], [ "unary_op", "namespacemlx_1_1core.html#a27f00519f9756896734fd4d47fec0625", null ], [ "unary_op_gpu", "namespacemlx_1_1core.html#aba2b4accc059f30d4dca88db9f7a6e13", null ], [ "unary_op_gpu_inplace", "namespacemlx_1_1core.html#a668fde2bd280a88f63a68b68a343d375", null ], [ "unflatten", "group__ops.html#ga666bcc2187a144247e8c0c224b016625", null ], + [ "unsafe_weak_copy", "namespacemlx_1_1core.html#a357f4172305d2021bde8cf07d99adb7d", null ], [ "value_and_grad", "namespacemlx_1_1core.html#a5a64dc878b29403d27e50bd7a288cc04", null ], [ "value_and_grad", "namespacemlx_1_1core.html#a7620f1ae298127cb6181db9162f012a7", null ], [ "value_and_grad", "namespacemlx_1_1core.html#a2f69ffc30d66b1fca8f24b65be161a51", null ], @@ -1135,6 +1147,7 @@ var namespacemlx_1_1core = [ "complexfloating", "namespacemlx_1_1core.html#a70b8e88c9df750af984757105af33423", null ], [ "float16", "namespacemlx_1_1core.html#abf228ee9d8ec48c03bb15adcc4e1f3ec", null ], [ "float32", "namespacemlx_1_1core.html#a6894543b340321193dfb8052c438a319", null ], + [ "float64", "namespacemlx_1_1core.html#a474bf5eb8bca8c380207c9f659aef3b1", null ], [ "floating", "namespacemlx_1_1core.html#ac9f9ea13cf0661e671569d37d14a128a", null ], [ "generic", "namespacemlx_1_1core.html#a34d69c4d46aa9b2a4a79dba7aba093d2", null ], [ "h12", "namespacemlx_1_1core.html#a4beeeec4413be7adcfb14feaa9cf0e2e", null ], diff --git a/docs/build/html/namespacemlx_1_1core_1_1detail.html b/docs/build/html/namespacemlx_1_1core_1_1detail.html index c828e1733..bb584a663 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1detail.html +++ b/docs/build/html/namespacemlx_1_1core_1_1detail.html @@ -132,6 +132,8 @@ Classes   struct  BitwiseAnd   +struct  BitwiseInvert +  struct  BitwiseOr   struct  BitwiseXor diff --git a/docs/build/html/namespacemlx_1_1core_1_1detail.js b/docs/build/html/namespacemlx_1_1core_1_1detail.js index 8c1e84687..a0f88621c 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1detail.js +++ b/docs/build/html/namespacemlx_1_1core_1_1detail.js @@ -10,6 +10,7 @@ var namespacemlx_1_1core_1_1detail = [ "ArcTan2", "structmlx_1_1core_1_1detail_1_1_arc_tan2.html", "structmlx_1_1core_1_1detail_1_1_arc_tan2" ], [ "ArcTanh", "structmlx_1_1core_1_1detail_1_1_arc_tanh.html", "structmlx_1_1core_1_1detail_1_1_arc_tanh" ], [ "BitwiseAnd", "structmlx_1_1core_1_1detail_1_1_bitwise_and.html", "structmlx_1_1core_1_1detail_1_1_bitwise_and" ], + [ "BitwiseInvert", "structmlx_1_1core_1_1detail_1_1_bitwise_invert.html", "structmlx_1_1core_1_1detail_1_1_bitwise_invert" ], [ "BitwiseOr", "structmlx_1_1core_1_1detail_1_1_bitwise_or.html", "structmlx_1_1core_1_1detail_1_1_bitwise_or" ], [ "BitwiseXor", "structmlx_1_1core_1_1detail_1_1_bitwise_xor.html", "structmlx_1_1core_1_1detail_1_1_bitwise_xor" ], [ "Ceil", "structmlx_1_1core_1_1detail_1_1_ceil.html", "structmlx_1_1core_1_1detail_1_1_ceil" ], diff --git a/docs/build/html/namespacemlx_1_1core_1_1env.html b/docs/build/html/namespacemlx_1_1core_1_1env.html index 2f440451e..98a6d37ca 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1env.html +++ b/docs/build/html/namespacemlx_1_1core_1_1env.html @@ -114,8 +114,10 @@ Functions   int bfs_max_width ()   -int max_ops_per_buffer () -  +int max_ops_per_buffer (int default_value) +  +int max_mb_per_buffer (int default_value) +  bool metal_fast_synch ()   @@ -166,8 +168,33 @@ Functions - -

    ◆ max_ops_per_buffer()

    + +

    ◆ max_mb_per_buffer()

    + +
    +
    + + + + + +
    + + + + + + + +
    int mlx::core::env::max_mb_per_buffer (int default_value)
    +     		+inline
    +
    + +
    +
    + +

    ◆ max_ops_per_buffer()

    @@ -178,7 +205,7 @@ Functions int mlx::core::env::max_ops_per_buffer ( - ) + int default_value) diff --git a/docs/build/html/namespacemlx_1_1core_1_1linalg.html b/docs/build/html/namespacemlx_1_1core_1_1linalg.html index 9057da09e..b9bbb034a 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1linalg.html +++ b/docs/build/html/namespacemlx_1_1core_1_1linalg.html @@ -137,6 +137,14 @@ Functions   array cholesky_inv (const array &a, bool upper=false, StreamOrDevice s={})   +std::vector< array > lu (const array &a, StreamOrDevice s={}) +  +std::pair< array, array > lu_factor (const array &a, StreamOrDevice s={}) +  +array solve (const array &a, const array &b, StreamOrDevice s={}) +  +array solve_triangular (const array &a, const array &b, bool upper=false, StreamOrDevice s={}) +  array cross (const array &a, const array &b, int axis=-1, StreamOrDevice s={})  Compute the cross product of two arrays along the given axis.
      @@ -302,6 +310,48 @@ Functions
    +
    +
    + +

    ◆ lu()

    + +
    +
    + + + + + + + + + + + +
    std::vector< array > mlx::core::linalg::lu (const array & a,
    StreamOrDevice s = {} )
    +
    + +
    +
    + +

    ◆ lu_factor()

    + +
    +
    + + + + + + + + + + + +
    std::pair< array, array > mlx::core::linalg::lu_factor (const array & a,
    StreamOrDevice s = {} )
    +
    +
    @@ -582,6 +632,63 @@ Functions
    +
    + + +

    ◆ solve()

    + +
    +
    + + + + + + + + + + + + + + + + +
    array mlx::core::linalg::solve (const array & a,
    const array & b,
    StreamOrDevice s = {} )
    +
    + +
    +
    + +

    ◆ solve_triangular()

    + +
    +
    + + + + + + + + + + + + + + + + + + + + + +
    array mlx::core::linalg::solve_triangular (const array & a,
    const array & b,
    bool upper = false,
    StreamOrDevice s = {} )
    +
    +
    diff --git a/docs/build/html/namespacemlx_1_1core_1_1simd.html b/docs/build/html/namespacemlx_1_1core_1_1simd.html index dbba24fd7..6f7fca282 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1simd.html +++ b/docs/build/html/namespacemlx_1_1core_1_1simd.html @@ -254,6 +254,9 @@ Functions template<typename T, int N> Simd< T, N > operator- (Simd< T, N > v)   +template<typename T, int N> +Simd< T, N > operator~ (Simd< T, N > v) +  template<typename T, int N> Simd< bool, N > isnan (Simd< T, N > v)   @@ -536,6 +539,9 @@ Functions template<typename T> Simd< T, 1 > tanh (Simd< T, 1 > in)   +template<typename T> +Simd< T, 1 > operator~ (Simd< T, 1 > in) +  template<typename T> auto real (Simd< T, 1 > in) -> Simd< decltype(std::real(in.value)), 1 >   @@ -6200,6 +6206,44 @@ template<typename T1, typename T2, int N>
    +
    + + +

    ◆ operator~() [1/2]

    + +
    +
    +
    +template<typename T>
    + + + + + + + +
    Simd< T, 1 > mlx::core::simd::operator~ (Simd< T, 1 > in)
    +
    + +
    +
    + +

    ◆ operator~() [2/2]

    + +
    +
    +
    +template<typename T, int N>
    + + + + + + + +
    Simd< T, N > mlx::core::simd::operator~ (Simd< T, N > v)
    +
    +
    diff --git a/docs/build/html/namespacemlx_1_1core_1_1simd.js b/docs/build/html/namespacemlx_1_1core_1_1simd.js index 5c108f7c0..9329d4e25 100644 --- a/docs/build/html/namespacemlx_1_1core_1_1simd.js +++ b/docs/build/html/namespacemlx_1_1core_1_1simd.js @@ -236,6 +236,8 @@ var namespacemlx_1_1core_1_1simd = [ "operator||", "namespacemlx_1_1core_1_1simd.html#aa9ac1951153211b2ff95dd34a3427797", null ], [ "operator||", "namespacemlx_1_1core_1_1simd.html#a0c8bd67982681ecd53cd8d739be3a5a9", null ], [ "operator||", "namespacemlx_1_1core_1_1simd.html#ac34f6b278627949d2ee68cdbf3d2f50f", null ], + [ "operator~", "namespacemlx_1_1core_1_1simd.html#a4c6ed06d523db05f99df7ef21b374c41", null ], + [ "operator~", "namespacemlx_1_1core_1_1simd.html#a290787dda17296d27af7afdef3c732a9", null ], [ "pow", "namespacemlx_1_1core_1_1simd.html#a19d535de1fc179cc39ec9643c9863cbc", null ], [ "pow", "namespacemlx_1_1core_1_1simd.html#afe3d50bc4a11061898aa57377fa9536d", null ], [ "pow", 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    212} // namespace mlx::core::simd
    base_simd.h
    mlx::core::simd
    Definition accelerate_fp16_simd.h:9
    -
    mlx::core::simd::isnan
    Simd< bool, N > isnan(Simd< T, N > v)
    Definition accelerate_simd.h:141
    +
    mlx::core::simd::isnan
    Simd< bool, N > isnan(Simd< T, N > v)
    Definition accelerate_simd.h:146
    mlx::core::simd::N
    constexpr int N
    Definition neon_fp16_simd.h:9
    -
    mlx::core::simd::minimum
    Simd< T, N > minimum(Simd< T, N > a, Simd< T, N > b)
    Definition accelerate_simd.h:210
    -
    mlx::core::simd::prod
    T prod(Simd< T, N > x)
    Definition accelerate_simd.h:292
    +
    mlx::core::simd::minimum
    Simd< T, N > minimum(Simd< T, N > a, Simd< T, N > b)
    Definition accelerate_simd.h:215
    +
    mlx::core::simd::prod
    T prod(Simd< T, N > x)
    Definition accelerate_simd.h:297
    mlx::core::simd::rint
    Simd< T, N > rint(Simd< T, N > v)
    Definition accelerate_simd.h:127
    -
    mlx::core::simd::load
    Simd< T, N > load(const T *x)
    Definition base_simd.h:27
    -
    mlx::core::simd::operator!=
    Simd< bool, N > operator!=(Simd< T, N > a, U b)
    Definition accelerate_simd.h:196
    +
    mlx::core::simd::load
    Simd< T, N > load(const T *x)
    Definition base_simd.h:28
    +
    mlx::core::simd::operator!=
    Simd< bool, N > operator!=(Simd< T, N > a, U b)
    Definition accelerate_simd.h:201
    mlx::core::simd::abs
    Simd< T, N > abs(Simd< T, N > v)
    Definition accelerate_simd.h:112
    -
    mlx::core::simd::sum
    T sum(Simd< T, N > x)
    Definition accelerate_simd.h:279
    -
    mlx::core::simd::max
    T max(Simd< T, N > x)
    Definition accelerate_simd.h:283
    -
    mlx::core::simd::operator!
    Simd< bool, N > operator!(Simd< T, N > v)
    Definition accelerate_simd.h:147
    -
    mlx::core::simd::maximum
    Simd< T, N > maximum(Simd< T, N > a, Simd< T, N > b)
    Definition accelerate_simd.h:204
    -
    mlx::core::simd::operator&&
    Simd< T, N > operator&&(Simd< T, N > x, U y)
    Definition accelerate_simd.h:174
    +
    mlx::core::simd::sum
    T sum(Simd< T, N > x)
    Definition accelerate_simd.h:284
    +
    mlx::core::simd::max
    T max(Simd< T, N > x)
    Definition accelerate_simd.h:288
    +
    mlx::core::simd::operator!
    Simd< bool, N > operator!(Simd< T, N > v)
    Definition accelerate_simd.h:152
    +
    mlx::core::simd::maximum
    Simd< T, N > maximum(Simd< T, N > a, Simd< T, N > b)
    Definition accelerate_simd.h:209
    +
    mlx::core::simd::operator&&
    Simd< T, N > operator&&(Simd< T, N > x, U y)
    Definition accelerate_simd.h:179
    mlx::core::simd::floor
    Simd< T, N > floor(Simd< T, N > v)
    Definition accelerate_simd.h:113
    -
    mlx::core::simd::fma
    Simd< T, N > fma(Simd< T, N > x, Simd< T, N > y, U z)
    Definition accelerate_simd.h:264
    -
    mlx::core::simd::operator||
    Simd< T, N > operator||(Simd< T, N > x, U y)
    Definition accelerate_simd.h:175
    -
    mlx::core::simd::min
    T min(Simd< T, N > x)
    Definition accelerate_simd.h:287
    +
    mlx::core::simd::fma
    Simd< T, N > fma(Simd< T, N > x, Simd< T, N > y, U z)
    Definition accelerate_simd.h:269
    +
    mlx::core::simd::operator||
    Simd< T, N > operator||(Simd< T, N > x, U y)
    Definition accelerate_simd.h:180
    +
    mlx::core::simd::min
    T min(Simd< T, N > x)
    Definition accelerate_simd.h:292
    mlx::core::simd::ceil
    Simd< T, N > ceil(Simd< T, N > v)
    Definition accelerate_simd.h:120
    mlx::core::simd::recip
    Simd< T, N > recip(Simd< T, N > v)
    Definition accelerate_simd.h:131
    mlx::core::simd::sqrt
    Simd< T, N > sqrt(Simd< T, N > v)
    Definition accelerate_simd.h:129
    -
    mlx::core::simd::clamp
    Simd< T, N > clamp(Simd< T, N > v, Simd< T, N > min, Simd< T, N > max)
    Definition accelerate_simd.h:259
    +
    mlx::core::simd::clamp
    Simd< T, N > clamp(Simd< T, N > v, Simd< T, N > min, Simd< T, N > max)
    Definition accelerate_simd.h:264
    mlx::core::simd::rsqrt
    Simd< T, N > rsqrt(Simd< T, N > v)
    Definition accelerate_simd.h:130
    mlx::core::simd::operator-
    Simd< T, N > operator-(Simd< T, N > v)
    Definition accelerate_simd.h:136
    -
    mlx::core::simd::select
    Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
    Definition accelerate_simd.h:231
    +
    mlx::core::simd::select
    Simd< T1, N > select(Simd< MaskT, N > mask, Simd< T1, N > x, Simd< T2, N > y)
    Definition accelerate_simd.h:236
    mlx::core::float16_t
    struct _MLX_Float16 float16_t
    Definition half_types.h:17
    DEFINE_NEON_BINARY_OP
    #define DEFINE_NEON_BINARY_OP(name, op)
    Definition neon_fp16_simd.h:68
    DEFINE_NEON_COMPARISON
    #define DEFINE_NEON_COMPARISON(Op, op)
    Definition neon_fp16_simd.h:97
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    +  +array mlx::core::operator~ (const array &a) +  array mlx::core::view (const array &a, const Dtype &dtype, StreamOrDevice s={})   array mlx::core::roll (const array &a, int shift, StreamOrDevice s={}) diff --git a/docs/build/html/ops_8h.js b/docs/build/html/ops_8h.js index 73e478f51..3aa94cdcb 100644 --- a/docs/build/html/ops_8h.js +++ b/docs/build/html/ops_8h.js @@ -49,6 +49,7 @@ var ops_8h = [ "mlx::core::atleast_3d", "group__ops.html#ga4afd919601e67782ff964465919956a0", null ], [ "mlx::core::atleast_3d", "group__ops.html#gaffdf742ad79440a60dda40062a8074fe", null ], [ "mlx::core::bitwise_and", "group__ops.html#ga752fd2707dabb05d0308ba3d55346ada", null ], + [ "mlx::core::bitwise_invert", "group__ops.html#gaf1182ae7c049fbc9ee190f3e0fffbf83", null ], [ "mlx::core::bitwise_or", "group__ops.html#ga8af4f22c08c11c4ffab7e3d45e0f3cd6", null ], [ "mlx::core::bitwise_xor", "group__ops.html#ga3188638fba3a60e264baf69956a1e08b", null ], [ "mlx::core::block_masked_mm", "group__ops.html#ga6b76c8ea46b19e6866af155fa5910be6", null ], @@ -202,6 +203,7 @@ var ops_8h = [ "mlx::core::operator^", "group__ops.html#gac3a6fe18694e84b3d63458e9553ac181", null ], [ "mlx::core::operator|", "group__ops.html#ga52392a2a98f09a80da8d338c4908bd02", null ], [ "mlx::core::operator||", "group__ops.html#ga27af56a98270d4d76d139f0f9171b83a", null ], + [ "mlx::core::operator~", "group__ops.html#ga849365a62878579a33b3d3ad09bbc7be", null ], [ "mlx::core::outer", "group__ops.html#ga866af24e10db2797e1c5a5986dbf6c0d", null ], [ "mlx::core::pad", "group__ops.html#gab2d5a17d3d5225fed34905e786c31c5f", null ], [ "mlx::core::pad", "group__ops.html#gab95ebd20bd7c6d1c840007cc020cbc0c", null ], diff --git a/docs/build/html/ops_8h_source.html b/docs/build/html/ops_8h_source.html index 1d78c7003..ee75b1820 100644 --- a/docs/build/html/ops_8h_source.html +++ b/docs/build/html/ops_8h_source.html @@ -1367,38 +1367,41 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
    1474
    1476array right_shift(const array& a, const array& b, StreamOrDevice s = {});
    1477array operator>>(const array& a, const array& b);
    -
    1478
    -
    1479array view(const array& a, const Dtype& dtype, StreamOrDevice s = {});
    -
    1480
    -
    1482array roll(const array& a, int shift, StreamOrDevice s = {});
    -
    1483array roll(const array& a, const Shape& shift, StreamOrDevice s = {});
    -
    1484array roll(const array& a, int shift, int axis, StreamOrDevice s = {});
    -
    1485array roll(
    -
    1486 const array& a,
    -
    1487 int shift,
    -
    1488 const std::vector<int>& axes,
    -
    1489 StreamOrDevice s = {});
    -
    1490array roll(const array& a, const Shape& shift, int axis, StreamOrDevice s = {});
    -
    1491array roll(
    -
    1492 const array& a,
    -
    1493 const Shape& shift,
    -
    1494 const std::vector<int>& axes,
    -
    1495 StreamOrDevice s = {});
    -
    1496
    -
    1497/* The real part of a complex array. */
    -
    1498array real(const array& a, StreamOrDevice s = {});
    -
    1499
    -
    1500/* The imaginary part of a complex array. */
    -
    1501array imag(const array& a, StreamOrDevice s = {});
    -
    1502
    -
    1503/* Ensure the array's underlying memory is contiguous. */
    -
    1504array contiguous(
    -
    1505 const array& a,
    -
    1506 bool allow_col_major = false,
    -
    1507 StreamOrDevice s = {});
    -
    1508
    -
    1510
    -
    1511} // namespace mlx::core
    +
    1478
    +
    1480array bitwise_invert(const array& a, StreamOrDevice s = {});
    +
    1481array operator~(const array& a);
    +
    1482
    +
    1483array view(const array& a, const Dtype& dtype, StreamOrDevice s = {});
    +
    1484
    +
    1486array roll(const array& a, int shift, StreamOrDevice s = {});
    +
    1487array roll(const array& a, const Shape& shift, StreamOrDevice s = {});
    +
    1488array roll(const array& a, int shift, int axis, StreamOrDevice s = {});
    +
    1489array roll(
    +
    1490 const array& a,
    +
    1491 int shift,
    +
    1492 const std::vector<int>& axes,
    +
    1493 StreamOrDevice s = {});
    +
    1494array roll(const array& a, const Shape& shift, int axis, StreamOrDevice s = {});
    +
    1495array roll(
    +
    1496 const array& a,
    +
    1497 const Shape& shift,
    +
    1498 const std::vector<int>& axes,
    +
    1499 StreamOrDevice s = {});
    +
    1500
    +
    1501/* The real part of a complex array. */
    +
    1502array real(const array& a, StreamOrDevice s = {});
    +
    1503
    +
    1504/* The imaginary part of a complex array. */
    +
    1505array imag(const array& a, StreamOrDevice s = {});
    +
    1506
    +
    1507/* Ensure the array's underlying memory is contiguous. */
    +
    1508array contiguous(
    +
    1509 const array& a,
    +
    1510 bool allow_col_major = false,
    +
    1511 StreamOrDevice s = {});
    +
    1512
    +
    1514
    +
    1515} // namespace mlx::core
    mlx::core::array
    Definition array.h:24
    @@ -1501,6 +1504,7 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
    mlx::core::imag
    array imag(const array &a, StreamOrDevice s={})
    mlx::core::addmm
    array addmm(array c, array a, array b, const float &alpha=1.f, const float &beta=1.f, StreamOrDevice s={})
    Compute D = beta * C + alpha * (A @ B)
    mlx::core::tril
    array tril(array x, int k=0, StreamOrDevice s={})
    +
    mlx::core::operator~
    array operator~(const array &a)
    mlx::core::any
    array any(const array &a, bool keepdims, StreamOrDevice s={})
    True if any elements in the array are true (or non-zero).
    mlx::core::outer
    array outer(const array &a, const array &b, StreamOrDevice s={})
    Compute the outer product of two vectors.
    mlx::core::hadamard_transform
    array hadamard_transform(const array &a, std::optional< float > scale=std::nullopt, StreamOrDevice s={})
    Multiply the array by the Hadamard matrix of corresponding size.
    @@ -1574,6 +1578,7 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
    mlx::core::operator/
    array operator/(const array &a, const array &b)
    mlx::core::allclose
    array allclose(const array &a, const array &b, double rtol=1e-5, double atol=1e-8, bool equal_nan=false, StreamOrDevice s={})
    True if the two arrays are equal within the specified tolerance.
    mlx::core::operator&
    array operator&(const array &a, const array &b)
    +
    mlx::core::bitwise_invert
    array bitwise_invert(const array &a, StreamOrDevice s={})
    Invert the bits.
    mlx::core::argpartition
    array argpartition(const array &a, int kth, StreamOrDevice s={})
    Returns indices that partition the flattened array such that the smaller kth elements are first.
    mlx::core::greater
    array greater(const array &a, const array &b, StreamOrDevice s={})
    Returns bool array with (a > b) element-wise.
    mlx::core::sinh
    array sinh(const array &a, StreamOrDevice s={})
    Hyperbolic Sine of the elements of an array.
    @@ -1589,8 +1594,8 @@ $(function(){initNavTree('ops_8h_source.html',''); initResizable(true); });
    mlx::core::to_stream
    Stream to_stream(StreamOrDevice s)
    mlx::core::copy
    void copy(const array &src, array &dst, CopyType ctype)
    mlx::core::slice
    void slice(const array &in, array &out, const Shape &start_indices, const Shape &strides)
    -
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:76
    -
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:80
    +
    mlx::core::int32
    constexpr Dtype int32
    Definition dtype.h:77
    +
    mlx::core::float32
    constexpr Dtype float32
    Definition dtype.h:81
    mlx::core::Shape
    std::vector< ShapeElem > Shape
    Definition array.h:21
    mlx::core::concatenate
    void concatenate(std::string &acc, T first)
    Definition utils.h:62
    mlx::core::Strides
    std::vector< int64_t > Strides
    Definition array.h:22
    diff --git a/docs/build/html/primitives_8h.html b/docs/build/html/primitives_8h.html index 269b945d8..3c4ef0046 100644 --- a/docs/build/html/primitives_8h.html +++ b/docs/build/html/primitives_8h.html @@ -157,6 +157,8 @@ Classes   class  mlx::core::BitwiseBinary   +class  mlx::core::BitwiseInvert +  class  mlx::core::BlockMaskedMM   class  mlx::core::GatherMM @@ -337,6 +339,8 @@ Classes   class  mlx::core::Eigh   +class  mlx::core::LUF +  diff --git a/docs/build/html/primitives_8h.js b/docs/build/html/primitives_8h.js index 359a6fd38..1a25e2abc 100644 --- a/docs/build/html/primitives_8h.js +++ b/docs/build/html/primitives_8h.js @@ -19,6 +19,7 @@ var primitives_8h = [ "mlx::core::AsType", "classmlx_1_1core_1_1_as_type.html", "classmlx_1_1core_1_1_as_type" ], [ "mlx::core::AsStrided", "classmlx_1_1core_1_1_as_strided.html", "classmlx_1_1core_1_1_as_strided" ], [ "mlx::core::BitwiseBinary", "classmlx_1_1core_1_1_bitwise_binary.html", "classmlx_1_1core_1_1_bitwise_binary" ], + [ "mlx::core::BitwiseInvert", "classmlx_1_1core_1_1_bitwise_invert.html", "classmlx_1_1core_1_1_bitwise_invert" ], [ "mlx::core::BlockMaskedMM", "classmlx_1_1core_1_1_block_masked_m_m.html", "classmlx_1_1core_1_1_block_masked_m_m" ], [ "mlx::core::GatherMM", "classmlx_1_1core_1_1_gather_m_m.html", "classmlx_1_1core_1_1_gather_m_m" ], [ "mlx::core::BroadcastAxes", "classmlx_1_1core_1_1_broadcast_axes.html", "classmlx_1_1core_1_1_broadcast_axes" ], @@ -109,6 +110,7 @@ var primitives_8h = [ "mlx::core::Inverse", "classmlx_1_1core_1_1_inverse.html", "classmlx_1_1core_1_1_inverse" ], [ "mlx::core::Cholesky", "classmlx_1_1core_1_1_cholesky.html", "classmlx_1_1core_1_1_cholesky" ], [ "mlx::core::Eigh", "classmlx_1_1core_1_1_eigh.html", "classmlx_1_1core_1_1_eigh" ], + [ "mlx::core::LUF", "classmlx_1_1core_1_1_l_u_f.html", "classmlx_1_1core_1_1_l_u_f" ], [ "DEFINE_DEFAULT_IS_EQUIVALENT", "primitives_8h.html#a0fb9d19207dc4869aca35abfbdf4d70a", null ], [ "DEFINE_GRADS", "primitives_8h.html#a77abdcb55bc2eb0f9a45edc5ee639bf6", null ], [ "DEFINE_INPUT_OUTPUT_SHAPE", "primitives_8h.html#a649a06267b75e007224ea4ddefedb999", null ], diff --git a/docs/build/html/primitives_8h_source.html b/docs/build/html/primitives_8h_source.html index 369280891..7720028bc 100644 --- a/docs/build/html/primitives_8h_source.html +++ b/docs/build/html/primitives_8h_source.html @@ -631,2259 +631,2287 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
    461
    -
    462class BlockMaskedMM : public UnaryPrimitive {
    +
    462class BitwiseInvert : public UnaryPrimitive {
    463 public:
    -
    -
    464 explicit BlockMaskedMM(Stream stream, int block_size)
    -
    465 : UnaryPrimitive(stream), block_size_(block_size) {}
    +
    464 explicit BitwiseInvert(Stream stream) : UnaryPrimitive(stream) {}
    +
    465
    +
    466 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    467 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    468
    +
    469 DEFINE_VMAP()
    +
    470 DEFINE_PRINT(BitwiseInvert)
    +
    471 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    472 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    473};
    -
    466
    -
    467 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    468 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    469
    -
    470 std::vector<array> vjp(
    -
    471 const std::vector<array>& primals,
    -
    472 const std::vector<array>& cotangents,
    -
    473 const std::vector<int>& argnums,
    -
    474 const std::vector<array>& outputs) override;
    -
    475
    -
    476 DEFINE_PRINT(BlockMaskedMM)
    -
    477 bool is_equivalent(const Primitive& other) const override;
    -
    -
    478 auto state() const {
    -
    479 return block_size_;
    -
    480 }
    +
    474
    +
    +
    475class BlockMaskedMM : public UnaryPrimitive {
    +
    476 public:
    +
    +
    477 explicit BlockMaskedMM(Stream stream, int block_size)
    +
    478 : UnaryPrimitive(stream), block_size_(block_size) {}
    -
    481
    -
    482 private:
    -
    483 int block_size_;
    -
    484};
    +
    479
    +
    480 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    481 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    482
    +
    483 std::vector<array> vjp(
    +
    484 const std::vector<array>& primals,
    +
    485 const std::vector<array>& cotangents,
    +
    486 const std::vector<int>& argnums,
    +
    487 const std::vector<array>& outputs) override;
    +
    488
    +
    489 DEFINE_PRINT(BlockMaskedMM)
    +
    490 bool is_equivalent(const Primitive& other) const override;
    +
    +
    491 auto state() const {
    +
    492 return block_size_;
    +
    493 }
    +
    +
    494
    +
    495 private:
    +
    496 int block_size_;
    +
    497};
    -
    485
    -
    -
    486class GatherMM : public UnaryPrimitive {
    -
    487 public:
    -
    488 explicit GatherMM(Stream stream) : UnaryPrimitive(stream) {}
    -
    489
    -
    490 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    491 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    492
    -
    493 std::vector<array> vjp(
    -
    494 const std::vector<array>& primals,
    -
    495 const std::vector<array>& cotangents,
    -
    496 const std::vector<int>& argnums,
    -
    497 const std::vector<array>& outputs) override;
    498
    -
    499 DEFINE_PRINT(GatherMM)
    -
    500 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    501};
    -
    +
    +
    499class GatherMM : public UnaryPrimitive {
    +
    500 public:
    +
    501 explicit GatherMM(Stream stream) : UnaryPrimitive(stream) {}
    502
    -
    -
    503class BroadcastAxes : public UnaryPrimitive {
    -
    504 public:
    -
    -
    505 explicit BroadcastAxes(Stream stream, std::vector<int> ignore_axes = {})
    -
    506 : UnaryPrimitive(stream), ignore_axes_(std::move(ignore_axes)) {}
    +
    503 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    504 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    505
    +
    506 std::vector<array> vjp(
    +
    507 const std::vector<array>& primals,
    +
    508 const std::vector<array>& cotangents,
    +
    509 const std::vector<int>& argnums,
    +
    510 const std::vector<array>& outputs) override;
    +
    511
    +
    512 DEFINE_PRINT(GatherMM)
    +
    513 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    514};
    -
    507
    -
    508 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    509 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    510
    -
    511 DEFINE_VMAP()
    -
    512 DEFINE_GRADS()
    -
    513 DEFINE_PRINT(BroadcastAxes)
    -
    514 bool is_equivalent(const Primitive& other) const override;
    -
    515 static Shape output_shape(
    -
    516 const std::vector<array>& inputs,
    -
    517 const std::vector<int>& ignore_axes);
    -
    518 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    -
    519 auto state() const {
    -
    520 return ignore_axes_;
    -
    521 }
    +
    515
    +
    +
    516class BroadcastAxes : public UnaryPrimitive {
    +
    517 public:
    +
    +
    518 explicit BroadcastAxes(Stream stream, std::vector<int> ignore_axes = {})
    +
    519 : UnaryPrimitive(stream), ignore_axes_(std::move(ignore_axes)) {}
    -
    522
    -
    523 private:
    -
    524 void eval(const std::vector<array>& inputs, array& out);
    -
    525 std::vector<int> ignore_axes_;
    -
    526};
    +
    520
    +
    521 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    522 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    523
    +
    524 DEFINE_VMAP()
    +
    525 DEFINE_GRADS()
    +
    526 DEFINE_PRINT(BroadcastAxes)
    +
    527 bool is_equivalent(const Primitive& other) const override;
    +
    528 static Shape output_shape(
    +
    529 const std::vector<array>& inputs,
    +
    530 const std::vector<int>& ignore_axes);
    +
    531 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    532 auto state() const {
    +
    533 return ignore_axes_;
    +
    534 }
    -
    527
    -
    -
    528class Broadcast : public UnaryPrimitive {
    -
    529 public:
    -
    -
    530 explicit Broadcast(Stream stream, const Shape& shape)
    -
    531 : UnaryPrimitive(stream), shape_(shape) {}
    -
    -
    532
    -
    533 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    534 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    535
    -
    536 DEFINE_VMAP()
    -
    537 DEFINE_GRADS()
    -
    538 DEFINE_PRINT(Broadcast)
    -
    539 static Shape output_shape(const std::vector<array>& inputs);
    -
    540 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    541 bool is_equivalent(const Primitive& other) const override;
    -
    -
    542 std::vector<int> state() const {
    -
    543 return shape_;
    -
    544 };
    +
    536 private:
    +
    537 void eval(const std::vector<array>& inputs, array& out);
    +
    538 std::vector<int> ignore_axes_;
    +
    539};
    +
    +
    540
    +
    +
    541class Broadcast : public UnaryPrimitive {
    +
    542 public:
    +
    +
    543 explicit Broadcast(Stream stream, const Shape& shape)
    +
    544 : UnaryPrimitive(stream), shape_(shape) {}
    545
    -
    546 private:
    -
    547 Shape shape_;
    +
    546 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    547 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    548
    -
    549 void eval(const std::vector<array>& inputs, array& out);
    -
    550};
    +
    549 DEFINE_VMAP()
    +
    550 DEFINE_GRADS()
    +
    551 DEFINE_PRINT(Broadcast)
    +
    552 static Shape output_shape(const std::vector<array>& inputs);
    +
    553 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    554 bool is_equivalent(const Primitive& other) const override;
    +
    +
    555 std::vector<int> state() const {
    +
    556 return shape_;
    +
    557 };
    -
    551
    -
    -
    552class Ceil : public UnaryPrimitive {
    -
    553 public:
    -
    554 explicit Ceil(Stream stream) : UnaryPrimitive(stream) {}
    -
    555
    -
    556 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    557 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    558
    -
    559 DEFINE_VMAP()
    -
    560 DEFINE_GRADS()
    -
    561 DEFINE_PRINT(Ceil)
    -
    562 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    563 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    564};
    +
    559 private:
    +
    560 Shape shape_;
    +
    561
    +
    562 void eval(const std::vector<array>& inputs, array& out);
    +
    563};
    -
    565
    -
    -
    566class Compiled : public Primitive {
    -
    567 public:
    -
    568 /*
    -
    569 * The inputs, outputs and tape are either tracers or constants.
    -
    570 * - The tape should not contain the inputs, but it should contain the
    -
    571 * outputs.
    -
    572 * - The tape should also have only one array per primitive for multi-output
    -
    573 * primitives.
    -
    574 * - The constant_ids contains ids of arrays in the input list that are safe
    -
    575 * to treat as scalar constants.
    -
    576 */
    -
    577 explicit Compiled(
    -
    578 Stream stream,
    -
    579 std::vector<array> inputs,
    -
    580 std::vector<array> outputs,
    -
    581 std::vector<array> tape,
    -
    582 std::unordered_set<uintptr_t> constant_ids);
    -
    583
    -
    584 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    585 override;
    -
    586 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    587 override;
    -
    588
    -
    589 DEFINE_VMAP()
    -
    590 DEFINE_GRADS()
    -
    591 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    592 void print(std::ostream& os) override;
    -
    593 bool is_equivalent(const Primitive& other) const override;
    -
    594
    -
    -
    595 std::string lib_name() const {
    -
    596 return kernel_lib_;
    -
    597 }
    -
    -
    598
    -
    599 private:
    -
    600 const std::vector<array> inputs_;
    -
    601 const std::vector<array> outputs_;
    -
    602 const std::vector<array> tape_;
    -
    603 const std::unordered_set<uintptr_t> constant_ids_;
    -
    604
    -
    605 std::string kernel_lib_;
    -
    606};
    +
    564
    +
    +
    565class Ceil : public UnaryPrimitive {
    +
    566 public:
    +
    567 explicit Ceil(Stream stream) : UnaryPrimitive(stream) {}
    +
    568
    +
    569 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    570 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    571
    +
    572 DEFINE_VMAP()
    +
    573 DEFINE_GRADS()
    +
    574 DEFINE_PRINT(Ceil)
    +
    575 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    576 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    577};
    +
    578
    +
    +
    579class Compiled : public Primitive {
    +
    580 public:
    +
    581 /*
    +
    582 * The inputs, outputs and tape are either tracers or constants.
    +
    583 * - The tape should not contain the inputs, but it should contain the
    +
    584 * outputs.
    +
    585 * - The tape should also have only one array per primitive for multi-output
    +
    586 * primitives.
    +
    587 * - The constant_ids contains ids of arrays in the input list that are safe
    +
    588 * to treat as scalar constants.
    +
    589 */
    +
    590 explicit Compiled(
    +
    591 Stream stream,
    +
    592 std::vector<array> inputs,
    +
    593 std::vector<array> outputs,
    +
    594 std::vector<array> tape,
    +
    595 std::unordered_set<uintptr_t> constant_ids);
    +
    596
    +
    597 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    598 override;
    +
    599 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    600 override;
    +
    601
    +
    602 DEFINE_VMAP()
    +
    603 DEFINE_GRADS()
    +
    604 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    605 void print(std::ostream& os) override;
    +
    606 bool is_equivalent(const Primitive& other) const override;
    607
    -
    -
    608class Concatenate : public UnaryPrimitive {
    -
    609 public:
    -
    -
    610 explicit Concatenate(Stream stream, int axis)
    -
    611 : UnaryPrimitive(stream), axis_(axis) {}
    +
    +
    608 std::string lib_name() const {
    +
    609 return kernel_lib_;
    +
    610 }
    -
    612
    -
    613 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    614 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    615
    -
    616 DEFINE_VMAP()
    -
    617 DEFINE_GRADS()
    -
    618 DEFINE_PRINT(Concatenate)
    -
    619 bool is_equivalent(const Primitive& other) const override;
    -
    620 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    -
    621 auto state() const {
    -
    622 return axis_;
    -
    623 }
    +
    611
    +
    612 private:
    +
    613 const std::vector<array> inputs_;
    +
    614 const std::vector<array> outputs_;
    +
    615 const std::vector<array> tape_;
    +
    616 const std::unordered_set<uintptr_t> constant_ids_;
    +
    617
    +
    618 std::string kernel_lib_;
    +
    619};
    -
    624
    -
    625 private:
    -
    626 int axis_;
    -
    627};
    +
    620
    +
    +
    621class Concatenate : public UnaryPrimitive {
    +
    622 public:
    +
    +
    623 explicit Concatenate(Stream stream, int axis)
    +
    624 : UnaryPrimitive(stream), axis_(axis) {}
    +
    625
    +
    626 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    627 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    628
    -
    -
    629class Conjugate : public UnaryPrimitive {
    -
    630 public:
    -
    631 explicit Conjugate(Stream stream) : UnaryPrimitive(stream) {}
    -
    632
    -
    633 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    634 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    635
    -
    636 DEFINE_VMAP()
    -
    637 DEFINE_PRINT(Conjugate)
    -
    638 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    639 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    629 DEFINE_VMAP()
    +
    630 DEFINE_GRADS()
    +
    631 DEFINE_PRINT(Concatenate)
    +
    632 bool is_equivalent(const Primitive& other) const override;
    +
    633 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    634 auto state() const {
    +
    635 return axis_;
    +
    636 }
    +
    +
    637
    +
    638 private:
    +
    639 int axis_;
    640};
    641
    -
    642class Contiguous : public UnaryPrimitive {
    +
    642class Conjugate : public UnaryPrimitive {
    643 public:
    -
    -
    644 explicit Contiguous(Stream stream, bool allow_col_major)
    -
    645 : UnaryPrimitive(stream), allow_col_major_(allow_col_major) {}
    +
    644 explicit Conjugate(Stream stream) : UnaryPrimitive(stream) {}
    +
    645
    +
    646 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    647 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    648
    +
    649 DEFINE_VMAP()
    +
    650 DEFINE_PRINT(Conjugate)
    +
    651 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    652 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    653};
    -
    646
    -
    647 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    648 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    649
    -
    650 DEFINE_VMAP()
    -
    651 DEFINE_GRADS()
    -
    652 DEFINE_PRINT(Contiguous)
    -
    653 DEFINE_INPUT_OUTPUT_SHAPE()
    654
    -
    655 bool is_equivalent(const Primitive& other) const override;
    -
    656
    -
    657 private:
    -
    658 bool allow_col_major_;
    -
    659};
    +
    +
    655class Contiguous : public UnaryPrimitive {
    +
    656 public:
    +
    +
    657 explicit Contiguous(Stream stream, bool allow_col_major)
    +
    658 : UnaryPrimitive(stream), allow_col_major_(allow_col_major) {}
    -
    660
    -
    -
    661class Convolution : public UnaryPrimitive {
    -
    662 public:
    -
    -
    663 explicit Convolution(
    -
    664 Stream stream,
    -
    665 const std::vector<int>& kernel_strides,
    -
    666 const std::vector<int>& padding,
    -
    667 const std::vector<int>& kernel_dilation,
    -
    668 const std::vector<int>& input_dilation,
    -
    669 const int groups = 1,
    -
    670 const bool flip = false)
    -
    671 : UnaryPrimitive(stream),
    -
    672 padding_(padding),
    -
    673 kernel_strides_(kernel_strides),
    -
    674 kernel_dilation_(kernel_dilation),
    -
    675 input_dilation_(input_dilation),
    -
    676 groups_(groups),
    -
    677 flip_(flip) {}
    +
    659
    +
    660 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    661 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    662
    +
    663 DEFINE_VMAP()
    +
    664 DEFINE_GRADS()
    +
    665 DEFINE_PRINT(Contiguous)
    +
    666 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    667
    +
    668 bool is_equivalent(const Primitive& other) const override;
    +
    669
    +
    670 private:
    +
    671 bool allow_col_major_;
    +
    672};
    -
    678
    -
    679 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    680 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    681
    -
    682 std::vector<array> vjp(
    -
    683 const std::vector<array>& primals,
    -
    684 const std::vector<array>& cotangents,
    -
    685 const std::vector<int>& argnums,
    -
    686 const std::vector<array>& outputs) override;
    -
    687
    -
    688 DEFINE_PRINT(Convolution)
    -
    689 bool is_equivalent(const Primitive& other) const override;
    -
    -
    690 auto state() const {
    -
    691 return std::make_tuple(
    -
    692 padding_,
    -
    693 kernel_strides_,
    -
    694 kernel_dilation_,
    -
    695 input_dilation_,
    -
    696 groups_,
    -
    697 flip_);
    -
    698 }
    +
    673
    +
    +
    674class Convolution : public UnaryPrimitive {
    +
    675 public:
    +
    +
    676 explicit Convolution(
    +
    677 Stream stream,
    +
    678 const std::vector<int>& kernel_strides,
    +
    679 const std::vector<int>& padding,
    +
    680 const std::vector<int>& kernel_dilation,
    +
    681 const std::vector<int>& input_dilation,
    +
    682 const int groups = 1,
    +
    683 const bool flip = false)
    +
    684 : UnaryPrimitive(stream),
    +
    685 padding_(padding),
    +
    686 kernel_strides_(kernel_strides),
    +
    687 kernel_dilation_(kernel_dilation),
    +
    688 input_dilation_(input_dilation),
    +
    689 groups_(groups),
    +
    690 flip_(flip) {}
    -
    699
    -
    700 private:
    -
    701 std::vector<int> padding_;
    -
    702 std::vector<int> kernel_strides_;
    -
    703 std::vector<int> kernel_dilation_;
    -
    704 std::vector<int> input_dilation_;
    -
    705 int groups_;
    -
    706 bool flip_;
    -
    707};
    +
    691
    +
    692 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    693 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    694
    +
    695 std::vector<array> vjp(
    +
    696 const std::vector<array>& primals,
    +
    697 const std::vector<array>& cotangents,
    +
    698 const std::vector<int>& argnums,
    +
    699 const std::vector<array>& outputs) override;
    +
    700
    +
    701 DEFINE_PRINT(Convolution)
    +
    702 bool is_equivalent(const Primitive& other) const override;
    +
    +
    703 auto state() const {
    +
    704 return std::make_tuple(
    +
    705 padding_,
    +
    706 kernel_strides_,
    +
    707 kernel_dilation_,
    +
    708 input_dilation_,
    +
    709 groups_,
    +
    710 flip_);
    +
    711 }
    -
    708
    -
    -
    709class Copy : public UnaryPrimitive {
    -
    710 public:
    -
    711 explicit Copy(Stream stream) : UnaryPrimitive(stream) {}
    712
    -
    713 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    714 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    715
    -
    716 DEFINE_VMAP()
    -
    717 DEFINE_GRADS()
    -
    718 DEFINE_PRINT(Copy)
    -
    719 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    720 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    713 private:
    +
    714 std::vector<int> padding_;
    +
    715 std::vector<int> kernel_strides_;
    +
    716 std::vector<int> kernel_dilation_;
    +
    717 std::vector<int> input_dilation_;
    +
    718 int groups_;
    +
    719 bool flip_;
    +
    720};
    +
    721
    -
    722 private:
    -
    723 void eval(const std::vector<array>& inputs, array& out);
    -
    724};
    -
    +
    +
    722class Copy : public UnaryPrimitive {
    +
    723 public:
    +
    724 explicit Copy(Stream stream) : UnaryPrimitive(stream) {}
    725
    -
    -
    726class Cos : public UnaryPrimitive {
    -
    727 public:
    -
    728 explicit Cos(Stream stream) : UnaryPrimitive(stream) {}
    -
    729
    -
    730 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    731 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    732
    -
    733 DEFINE_VMAP()
    -
    734 DEFINE_GRADS()
    -
    735 DEFINE_PRINT(Cos)
    -
    736 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    737 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    738};
    +
    726 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    727 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    728
    +
    729 DEFINE_VMAP()
    +
    730 DEFINE_GRADS()
    +
    731 DEFINE_PRINT(Copy)
    +
    732 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    733 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    734
    +
    735 private:
    +
    736 void eval(const std::vector<array>& inputs, array& out);
    +
    737};
    -
    739
    -
    -
    740class Cosh : public UnaryPrimitive {
    -
    741 public:
    -
    742 explicit Cosh(Stream stream) : UnaryPrimitive(stream) {}
    -
    743
    -
    744 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    745 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    746
    -
    747 DEFINE_VMAP()
    -
    748 DEFINE_GRADS()
    -
    749 DEFINE_PRINT(Cosh)
    -
    750 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    751 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    752};
    +
    738
    +
    +
    739class Cos : public UnaryPrimitive {
    +
    740 public:
    +
    741 explicit Cos(Stream stream) : UnaryPrimitive(stream) {}
    +
    742
    +
    743 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    744 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    745
    +
    746 DEFINE_VMAP()
    +
    747 DEFINE_GRADS()
    +
    748 DEFINE_PRINT(Cos)
    +
    749 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    750 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    751};
    -
    753
    -
    -
    754class CustomTransforms : public Primitive {
    -
    755 public:
    -
    -
    756 explicit CustomTransforms(
    -
    757 Stream stream,
    -
    758 int num_outputs,
    -
    759 std::function<std::vector<array>(
    -
    760 const std::vector<array>&,
    -
    761 const std::vector<array>&,
    -
    762 const std::vector<array>&)> vjp,
    -
    763 std::function<std::vector<array>(
    -
    764 const std::vector<array>&,
    -
    765 const std::vector<array>&,
    -
    766 const std::vector<int>&)> jvp,
    -
    767 std::function<std::pair<std::vector<array>, std::vector<int>>(
    -
    768 const std::vector<array>&,
    -
    769 const std::vector<int>&)> vmap)
    -
    770 : Primitive(stream),
    -
    771 num_outputs_(num_outputs),
    -
    772 vjp_fun_(std::move(vjp)),
    -
    773 jvp_fun_(std::move(jvp)),
    -
    774 vmap_fun_(std::move(vmap)) {}
    +
    752
    +
    +
    753class Cosh : public UnaryPrimitive {
    +
    754 public:
    +
    755 explicit Cosh(Stream stream) : UnaryPrimitive(stream) {}
    +
    756
    +
    757 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    758 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    759
    +
    760 DEFINE_VMAP()
    +
    761 DEFINE_GRADS()
    +
    762 DEFINE_PRINT(Cosh)
    +
    763 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    764 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    765};
    -
    775
    -
    776 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    777 override;
    -
    778 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    779 override;
    -
    780
    -
    781 DEFINE_GRADS();
    -
    782 DEFINE_VMAP();
    -
    783 DEFINE_PRINT(CustomTransforms);
    -
    784
    -
    785 private:
    -
    786 void eval(const std::vector<array>& inputs, std::vector<array>& outputs);
    -
    787
    -
    788 int num_outputs_;
    -
    789
    -
    790 std::function<std::vector<array>(
    -
    791 const std::vector<array>&,
    -
    792 const std::vector<array>&,
    -
    793 const std::vector<array>&)>
    -
    794 vjp_fun_;
    -
    795 std::function<std::vector<array>(
    -
    796 const std::vector<array>&,
    -
    797 const std::vector<array>&,
    -
    798 const std::vector<int>&)>
    -
    799 jvp_fun_;
    -
    800 std::function<std::pair<std::vector<array>, std::vector<int>>(
    -
    801 const std::vector<array>&,
    -
    802 const std::vector<int>&)>
    -
    803 vmap_fun_;
    -
    804};
    +
    766
    +
    +
    767class CustomTransforms : public Primitive {
    +
    768 public:
    +
    +
    769 explicit CustomTransforms(
    +
    770 Stream stream,
    +
    771 int num_outputs,
    +
    772 std::function<std::vector<array>(
    +
    773 const std::vector<array>&,
    +
    774 const std::vector<array>&,
    +
    775 const std::vector<array>&)> vjp,
    +
    776 std::function<std::vector<array>(
    +
    777 const std::vector<array>&,
    +
    778 const std::vector<array>&,
    +
    779 const std::vector<int>&)> jvp,
    +
    780 std::function<std::pair<std::vector<array>, std::vector<int>>(
    +
    781 const std::vector<array>&,
    +
    782 const std::vector<int>&)> vmap)
    +
    783 : Primitive(stream),
    +
    784 num_outputs_(num_outputs),
    +
    785 vjp_fun_(std::move(vjp)),
    +
    786 jvp_fun_(std::move(jvp)),
    +
    787 vmap_fun_(std::move(vmap)) {}
    -
    805
    -
    -
    806class Depends : public Primitive {
    -
    807 public:
    -
    808 explicit Depends(Stream stream) : Primitive(stream) {}
    -
    809
    -
    810 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    811 override;
    -
    812 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    813 override;
    -
    814
    -
    815 std::vector<array> vjp(
    -
    816 const std::vector<array>& primals,
    -
    817 const std::vector<array>& cotan,
    -
    818 const std::vector<int>& argnums,
    -
    819 const std::vector<array>& outputs) override;
    -
    820
    -
    821 DEFINE_PRINT(Depends);
    +
    788
    +
    789 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    790 override;
    +
    791 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    792 override;
    +
    793
    +
    794 DEFINE_GRADS();
    +
    795 DEFINE_VMAP();
    +
    796 DEFINE_PRINT(CustomTransforms);
    +
    797
    +
    798 private:
    +
    799 void eval(const std::vector<array>& inputs, std::vector<array>& outputs);
    +
    800
    +
    801 int num_outputs_;
    +
    802
    +
    803 std::function<std::vector<array>(
    +
    804 const std::vector<array>&,
    +
    805 const std::vector<array>&,
    +
    806 const std::vector<array>&)>
    +
    807 vjp_fun_;
    +
    808 std::function<std::vector<array>(
    +
    809 const std::vector<array>&,
    +
    810 const std::vector<array>&,
    +
    811 const std::vector<int>&)>
    +
    812 jvp_fun_;
    +
    813 std::function<std::pair<std::vector<array>, std::vector<int>>(
    +
    814 const std::vector<array>&,
    +
    815 const std::vector<int>&)>
    +
    816 vmap_fun_;
    +
    817};
    +
    +
    818
    +
    +
    819class Depends : public Primitive {
    +
    820 public:
    +
    821 explicit Depends(Stream stream) : Primitive(stream) {}
    822
    -
    823 private:
    -
    824 void eval(const std::vector<array>& inputs, std::vector<array>& outputs);
    -
    825};
    -
    -
    826
    -
    -
    827class Divide : public UnaryPrimitive {
    -
    828 public:
    -
    829 explicit Divide(Stream stream) : UnaryPrimitive(stream) {}
    -
    830
    -
    831 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    832 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    823 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    824 override;
    +
    825 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    826 override;
    +
    827
    +
    828 std::vector<array> vjp(
    +
    829 const std::vector<array>& primals,
    +
    830 const std::vector<array>& cotan,
    +
    831 const std::vector<int>& argnums,
    +
    832 const std::vector<array>& outputs) override;
    833
    -
    834 DEFINE_VMAP()
    -
    835 DEFINE_GRADS()
    -
    836 DEFINE_PRINT(Divide)
    -
    837 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    838 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    839};
    +
    834 DEFINE_PRINT(Depends);
    +
    835
    +
    836 private:
    +
    837 void eval(const std::vector<array>& inputs, std::vector<array>& outputs);
    +
    838};
    -
    840
    -
    -
    841class DivMod : public Primitive {
    -
    842 public:
    -
    843 explicit DivMod(Stream stream) : Primitive(stream) {}
    -
    844
    -
    845 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    846 override;
    -
    847 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    848 override;
    -
    849
    -
    850 DEFINE_VMAP()
    -
    851 DEFINE_GRADS()
    -
    852 DEFINE_PRINT(DivMod)
    -
    853 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    -
    854 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override {
    -
    855 return std::vector{inputs[0].shape(), inputs[0].shape()};
    -
    856 }
    +
    839
    +
    +
    840class Divide : public UnaryPrimitive {
    +
    841 public:
    +
    842 explicit Divide(Stream stream) : UnaryPrimitive(stream) {}
    +
    843
    +
    844 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    845 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    846
    +
    847 DEFINE_VMAP()
    +
    848 DEFINE_GRADS()
    +
    849 DEFINE_PRINT(Divide)
    +
    850 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    851 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    852};
    -
    857};
    -
    -
    858
    -
    -
    859class Select : public UnaryPrimitive {
    -
    860 public:
    -
    861 explicit Select(Stream stream) : UnaryPrimitive(stream) {}
    +
    853
    +
    +
    854class DivMod : public Primitive {
    +
    855 public:
    +
    856 explicit DivMod(Stream stream) : Primitive(stream) {}
    +
    857
    +
    858 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    859 override;
    +
    860 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    861 override;
    862
    -
    863 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    864 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    865
    -
    866 DEFINE_VMAP()
    -
    867 DEFINE_GRADS()
    -
    868 DEFINE_PRINT(Select)
    -
    869 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    870 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    871};
    +
    863 DEFINE_VMAP()
    +
    864 DEFINE_GRADS()
    +
    865 DEFINE_PRINT(DivMod)
    +
    866 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    +
    867 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override {
    +
    868 return std::vector{inputs[0].shape(), inputs[0].shape()};
    +
    869 }
    -
    872
    -
    -
    873class Remainder : public UnaryPrimitive {
    -
    874 public:
    -
    875 explicit Remainder(Stream stream) : UnaryPrimitive(stream) {}
    -
    876
    -
    877 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    878 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    879
    -
    880 DEFINE_VMAP()
    -
    881 DEFINE_GRADS()
    -
    882 DEFINE_PRINT(Remainder)
    -
    883 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    884 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    885};
    +
    870};
    -
    886
    -
    -
    887class Equal : public UnaryPrimitive {
    -
    888 public:
    -
    -
    889 explicit Equal(Stream stream, bool equal_nan = false)
    -
    890 : UnaryPrimitive(stream), equal_nan_(equal_nan) {}
    +
    871
    +
    +
    872class Select : public UnaryPrimitive {
    +
    873 public:
    +
    874 explicit Select(Stream stream) : UnaryPrimitive(stream) {}
    +
    875
    +
    876 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    877 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    878
    +
    879 DEFINE_VMAP()
    +
    880 DEFINE_GRADS()
    +
    881 DEFINE_PRINT(Select)
    +
    882 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    883 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    884};
    +
    +
    885
    +
    +
    886class Remainder : public UnaryPrimitive {
    +
    887 public:
    +
    888 explicit Remainder(Stream stream) : UnaryPrimitive(stream) {}
    +
    889
    +
    890 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    891 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    892
    +
    893 DEFINE_VMAP()
    +
    894 DEFINE_GRADS()
    +
    895 DEFINE_PRINT(Remainder)
    +
    896 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    897 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    898};
    -
    891
    -
    892 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    893 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    894
    -
    895 DEFINE_VMAP()
    -
    896 DEFINE_GRADS()
    -
    897 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    898 DEFINE_INPUT_OUTPUT_SHAPE()
    899
    -
    -
    900 void print(std::ostream& os) override {
    -
    901 if (equal_nan_) {
    -
    902 os << "NaNEqual";
    -
    903 } else {
    -
    904 os << "Equal";
    -
    905 }
    -
    906 }
    +
    +
    900class Equal : public UnaryPrimitive {
    +
    901 public:
    +
    +
    902 explicit Equal(Stream stream, bool equal_nan = false)
    +
    903 : UnaryPrimitive(stream), equal_nan_(equal_nan) {}
    -
    -
    907 auto state() const {
    -
    908 return equal_nan_;
    -
    909 };
    +
    904
    +
    905 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    906 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    907
    +
    908 DEFINE_VMAP()
    +
    909 DEFINE_GRADS()
    +
    910 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    911 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    912
    +
    +
    913 void print(std::ostream& os) override {
    +
    914 if (equal_nan_) {
    +
    915 os << "NaNEqual";
    +
    916 } else {
    +
    917 os << "Equal";
    +
    918 }
    +
    919 }
    -
    910
    -
    911 private:
    -
    912 bool equal_nan_;
    -
    913};
    +
    +
    920 auto state() const {
    +
    921 return equal_nan_;
    +
    922 };
    -
    914
    -
    -
    915class Erf : public UnaryPrimitive {
    -
    916 public:
    -
    917 explicit Erf(Stream stream) : UnaryPrimitive(stream) {}
    -
    918
    -
    919 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    920 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    921
    -
    922 DEFINE_VMAP()
    -
    923 DEFINE_GRADS()
    -
    924 DEFINE_PRINT(Erf)
    -
    925 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    926 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    927};
    +
    923
    +
    924 private:
    +
    925 bool equal_nan_;
    +
    926};
    -
    928
    -
    -
    929class ErfInv : public UnaryPrimitive {
    -
    930 public:
    -
    931 explicit ErfInv(Stream stream) : UnaryPrimitive(stream) {}
    -
    932
    -
    933 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    934 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    935
    -
    936 DEFINE_VMAP()
    -
    937 DEFINE_GRADS()
    -
    938 DEFINE_PRINT(ErfInv)
    -
    939 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    940 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    941};
    +
    927
    +
    +
    928class Erf : public UnaryPrimitive {
    +
    929 public:
    +
    930 explicit Erf(Stream stream) : UnaryPrimitive(stream) {}
    +
    931
    +
    932 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    933 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    934
    +
    935 DEFINE_VMAP()
    +
    936 DEFINE_GRADS()
    +
    937 DEFINE_PRINT(Erf)
    +
    938 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    939 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    940};
    -
    942
    -
    -
    943class Exp : public UnaryPrimitive {
    -
    944 public:
    -
    945 explicit Exp(Stream stream) : UnaryPrimitive(stream) {}
    -
    946
    -
    947 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    948 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    949
    -
    950 DEFINE_VMAP()
    -
    951 DEFINE_GRADS()
    -
    952 DEFINE_PRINT(Exp)
    -
    953 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    954 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    955};
    +
    941
    +
    +
    942class ErfInv : public UnaryPrimitive {
    +
    943 public:
    +
    944 explicit ErfInv(Stream stream) : UnaryPrimitive(stream) {}
    +
    945
    +
    946 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    947 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    948
    +
    949 DEFINE_VMAP()
    +
    950 DEFINE_GRADS()
    +
    951 DEFINE_PRINT(ErfInv)
    +
    952 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    953 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    954};
    -
    956
    -
    -
    957class Expm1 : public UnaryPrimitive {
    -
    958 public:
    -
    959 explicit Expm1(Stream stream) : UnaryPrimitive(stream) {}
    -
    960
    -
    961 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    962 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    963
    -
    964 DEFINE_VMAP()
    -
    965 DEFINE_GRADS()
    -
    966 DEFINE_PRINT(Expm1)
    -
    967 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    955
    +
    +
    956class Exp : public UnaryPrimitive {
    +
    957 public:
    +
    958 explicit Exp(Stream stream) : UnaryPrimitive(stream) {}
    +
    959
    +
    960 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    961 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    962
    +
    963 DEFINE_VMAP()
    +
    964 DEFINE_GRADS()
    +
    965 DEFINE_PRINT(Exp)
    +
    966 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    967 DEFINE_INPUT_OUTPUT_SHAPE()
    968};
    969
    -
    970class ExpandDims : public UnaryPrimitive {
    +
    970class Expm1 : public UnaryPrimitive {
    971 public:
    -
    -
    972 explicit ExpandDims(Stream stream, std::vector<int> axes)
    -
    973 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
    +
    972 explicit Expm1(Stream stream) : UnaryPrimitive(stream) {}
    +
    973
    +
    974 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    975 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    976
    +
    977 DEFINE_VMAP()
    +
    978 DEFINE_GRADS()
    +
    979 DEFINE_PRINT(Expm1)
    +
    980 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    981};
    -
    974
    -
    975 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    976 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    977
    -
    978 DEFINE_VMAP()
    -
    979 DEFINE_GRADS()
    -
    980 DEFINE_PRINT(ExpandDims)
    -
    981
    -
    982 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    983 bool is_equivalent(const Primitive& other) const override;
    -
    984
    -
    985 static Shape output_shape(const array& input, const std::vector<int>& axes);
    -
    -
    986 auto state() const {
    -
    987 return axes_;
    -
    988 }
    -
    -
    989
    -
    990 private:
    -
    991 void eval(const std::vector<array>& inputs, array& out);
    -
    992 std::vector<int> axes_;
    -
    993};
    +
    982
    +
    +
    983class ExpandDims : public UnaryPrimitive {
    +
    984 public:
    +
    +
    985 explicit ExpandDims(Stream stream, std::vector<int> axes)
    +
    986 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
    +
    987
    +
    988 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    989 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    990
    +
    991 DEFINE_VMAP()
    +
    992 DEFINE_GRADS()
    +
    993 DEFINE_PRINT(ExpandDims)
    994
    -
    -
    995class FFT : public UnaryPrimitive {
    -
    996 public:
    -
    -
    997 explicit FFT(
    -
    998 Stream stream,
    -
    999 const std::vector<size_t>& axes,
    -
    1000 bool inverse,
    -
    1001 bool real)
    -
    1002 : UnaryPrimitive(stream), axes_(axes), inverse_(inverse), real_(real) {}
    +
    995 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    996 bool is_equivalent(const Primitive& other) const override;
    +
    997
    +
    998 static Shape output_shape(const array& input, const std::vector<int>& axes);
    +
    +
    999 auto state() const {
    +
    1000 return axes_;
    +
    1001 }
    -
    1003
    -
    1004 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1005 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1006
    -
    1007 DEFINE_VMAP()
    -
    1008 DEFINE_GRADS()
    -
    1009 DEFINE_PRINT(FFT)
    -
    1010
    -
    1011 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1012 auto state() const {
    -
    1013 return std::make_tuple(axes_, inverse_, real_);
    -
    1014 }
    +
    1002
    +
    1003 private:
    +
    1004 void eval(const std::vector<array>& inputs, array& out);
    +
    1005 std::vector<int> axes_;
    +
    1006};
    -
    1015
    -
    1016 private:
    -
    1017 std::vector<size_t> axes_;
    -
    1018 bool inverse_;
    -
    1019 bool real_;
    -
    1020};
    +
    1007
    +
    +
    1008class FFT : public UnaryPrimitive {
    +
    1009 public:
    +
    +
    1010 explicit FFT(
    +
    1011 Stream stream,
    +
    1012 const std::vector<size_t>& axes,
    +
    1013 bool inverse,
    +
    1014 bool real)
    +
    1015 : UnaryPrimitive(stream), axes_(axes), inverse_(inverse), real_(real) {}
    -
    1021
    -
    -
    1022class Flatten : public UnaryPrimitive {
    -
    1023 public:
    -
    -
    1024 explicit Flatten(Stream stream, int start_axis, int end_axis)
    -
    1025 : UnaryPrimitive(stream), start_axis_(start_axis), end_axis_(end_axis) {}
    +
    1016
    +
    1017 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1018 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1019
    +
    1020 DEFINE_VMAP()
    +
    1021 DEFINE_GRADS()
    +
    1022 DEFINE_PRINT(FFT)
    +
    1023
    +
    1024 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1025 auto state() const {
    +
    1026 return std::make_tuple(axes_, inverse_, real_);
    +
    1027 }
    -
    1026
    -
    1027 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1028 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1029
    -
    1030 DEFINE_VMAP()
    -
    1031 DEFINE_GRADS()
    -
    1032 DEFINE_PRINT(Flatten)
    -
    1033 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    1034 bool is_equivalent(const Primitive& other) const override;
    -
    1035
    -
    1036 static Shape output_shape(const array& input, int start_axis, int end_axis);
    +
    1028
    +
    1029 private:
    +
    1030 std::vector<size_t> axes_;
    +
    1031 bool inverse_;
    +
    1032 bool real_;
    +
    1033};
    +
    +
    1034
    +
    +
    1035class Flatten : public UnaryPrimitive {
    +
    1036 public:
    -
    1037 auto state() const {
    -
    1038 return std::make_pair(start_axis_, end_axis_);
    -
    1039 }
    +
    1037 explicit Flatten(Stream stream, int start_axis, int end_axis)
    +
    1038 : UnaryPrimitive(stream), start_axis_(start_axis), end_axis_(end_axis) {}
    -
    1040
    -
    1041 private:
    -
    1042 int start_axis_;
    -
    1043 int end_axis_;
    -
    1044 void eval(const std::vector<array>& inputs, array& out);
    -
    1045};
    +
    1039
    +
    1040 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1041 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1042
    +
    1043 DEFINE_VMAP()
    +
    1044 DEFINE_GRADS()
    +
    1045 DEFINE_PRINT(Flatten)
    +
    1046 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    1047 bool is_equivalent(const Primitive& other) const override;
    +
    1048
    +
    1049 static Shape output_shape(const array& input, int start_axis, int end_axis);
    +
    +
    1050 auto state() const {
    +
    1051 return std::make_pair(start_axis_, end_axis_);
    +
    1052 }
    -
    1046
    -
    -
    1047class Floor : public UnaryPrimitive {
    -
    1048 public:
    -
    1049 explicit Floor(Stream stream) : UnaryPrimitive(stream) {}
    -
    1050
    -
    1051 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1052 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    1053
    -
    1054 DEFINE_VMAP()
    -
    1055 DEFINE_GRADS()
    -
    1056 DEFINE_PRINT(Floor)
    -
    1057 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1058 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1059};
    +
    1054 private:
    +
    1055 int start_axis_;
    +
    1056 int end_axis_;
    +
    1057 void eval(const std::vector<array>& inputs, array& out);
    +
    1058};
    -
    1060
    -
    -
    1061class Full : public UnaryPrimitive {
    -
    1062 public:
    -
    1063 explicit Full(Stream stream) : UnaryPrimitive(stream) {}
    -
    1064
    -
    1065 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1066 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1067
    -
    1068 DEFINE_VMAP()
    -
    1069 DEFINE_GRADS()
    -
    1070 DEFINE_PRINT(Full)
    -
    1071 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1059
    +
    +
    1060class Floor : public UnaryPrimitive {
    +
    1061 public:
    +
    1062 explicit Floor(Stream stream) : UnaryPrimitive(stream) {}
    +
    1063
    +
    1064 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1065 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1066
    +
    1067 DEFINE_VMAP()
    +
    1068 DEFINE_GRADS()
    +
    1069 DEFINE_PRINT(Floor)
    +
    1070 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1071 DEFINE_INPUT_OUTPUT_SHAPE()
    1072};
    1073
    -
    1074class Gather : public UnaryPrimitive {
    +
    1074class Full : public UnaryPrimitive {
    1075 public:
    -
    -
    1076 explicit Gather(Stream stream, std::vector<int> axes, Shape slice_sizes)
    -
    1077 : UnaryPrimitive(stream),
    -
    1078 axes_(std::move(axes)),
    -
    1079 slice_sizes_(std::move(slice_sizes)) {}
    -
    +
    1076 explicit Full(Stream stream) : UnaryPrimitive(stream) {}
    +
    1077
    +
    1078 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1079 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    1080
    -
    1081 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1082 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1083
    -
    1084 DEFINE_VMAP()
    -
    1085 DEFINE_GRADS()
    -
    1086 DEFINE_PRINT(Gather)
    -
    1087 bool is_equivalent(const Primitive& other) const override;
    -
    1088 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    1081 DEFINE_VMAP()
    +
    1082 DEFINE_GRADS()
    +
    1083 DEFINE_PRINT(Full)
    +
    1084 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1085};
    +
    +
    1086
    +
    +
    1087class Gather : public UnaryPrimitive {
    +
    1088 public:
    -
    1089 std::pair<std::vector<int>, std::vector<int>> state() const {
    -
    1090 return {axes_, slice_sizes_};
    -
    1091 }
    +
    1089 explicit Gather(Stream stream, std::vector<int> axes, Shape slice_sizes)
    +
    1090 : UnaryPrimitive(stream),
    +
    1091 axes_(std::move(axes)),
    +
    1092 slice_sizes_(std::move(slice_sizes)) {}
    -
    1092
    -
    1093 private:
    -
    1094 std::vector<int> axes_;
    -
    1095 Shape slice_sizes_;
    -
    1096};
    +
    1093
    +
    1094 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1095 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1096
    +
    1097 DEFINE_VMAP()
    +
    1098 DEFINE_GRADS()
    +
    1099 DEFINE_PRINT(Gather)
    +
    1100 bool is_equivalent(const Primitive& other) const override;
    +
    1101 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    1102 std::pair<std::vector<int>, std::vector<int>> state() const {
    +
    1103 return {axes_, slice_sizes_};
    +
    1104 }
    -
    1097
    -
    -
    1098class GatherAxis : public UnaryPrimitive {
    -
    1099 public:
    -
    -
    1100 explicit GatherAxis(Stream stream, int axis)
    -
    1101 : UnaryPrimitive(stream), axis_(axis) {}
    -
    -
    1102
    -
    1103 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1104 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    1105
    -
    1106 DEFINE_VMAP()
    -
    1107 DEFINE_GRADS()
    -
    1108 DEFINE_PRINT(GatherAxis)
    -
    1109 bool is_equivalent(const Primitive& other) const override;
    -
    1110 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    -
    1111 auto state() const {
    -
    1112 return axis_;
    -
    1113 }
    +
    1106 private:
    +
    1107 std::vector<int> axes_;
    +
    1108 Shape slice_sizes_;
    +
    1109};
    -
    1114
    -
    1115 private:
    -
    1116 int axis_;
    -
    1117};
    +
    1110
    +
    +
    1111class GatherAxis : public UnaryPrimitive {
    +
    1112 public:
    +
    +
    1113 explicit GatherAxis(Stream stream, int axis)
    +
    1114 : UnaryPrimitive(stream), axis_(axis) {}
    +
    1115
    +
    1116 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1117 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    1118
    -
    -
    1119class Greater : public UnaryPrimitive {
    -
    1120 public:
    -
    1121 explicit Greater(Stream stream) : UnaryPrimitive(stream) {}
    -
    1122
    -
    1123 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1124 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1125
    -
    1126 DEFINE_VMAP()
    -
    1127 DEFINE_GRADS()
    -
    1128 DEFINE_PRINT(Greater)
    -
    1129 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1130 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1131};
    +
    1119 DEFINE_VMAP()
    +
    1120 DEFINE_GRADS()
    +
    1121 DEFINE_PRINT(GatherAxis)
    +
    1122 bool is_equivalent(const Primitive& other) const override;
    +
    1123 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    1124 auto state() const {
    +
    1125 return axis_;
    +
    1126 }
    -
    1132
    -
    -
    1133class GreaterEqual : public UnaryPrimitive {
    -
    1134 public:
    -
    1135 explicit GreaterEqual(Stream stream) : UnaryPrimitive(stream) {}
    -
    1136
    -
    1137 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1138 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1139
    -
    1140 DEFINE_VMAP()
    -
    1141 DEFINE_GRADS()
    -
    1142 DEFINE_PRINT(GreaterEqual)
    -
    1143 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1144 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1145};
    +
    1127
    +
    1128 private:
    +
    1129 int axis_;
    +
    1130};
    -
    1146
    -
    -
    1147class Hadamard : public UnaryPrimitive {
    -
    1148 public:
    -
    -
    1149 explicit Hadamard(Stream stream, float scale)
    -
    1150 : UnaryPrimitive(stream), scale_(scale) {}
    +
    1131
    +
    +
    1132class Greater : public UnaryPrimitive {
    +
    1133 public:
    +
    1134 explicit Greater(Stream stream) : UnaryPrimitive(stream) {}
    +
    1135
    +
    1136 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1137 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1138
    +
    1139 DEFINE_VMAP()
    +
    1140 DEFINE_GRADS()
    +
    1141 DEFINE_PRINT(Greater)
    +
    1142 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1143 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1144};
    +
    +
    1145
    +
    +
    1146class GreaterEqual : public UnaryPrimitive {
    +
    1147 public:
    +
    1148 explicit GreaterEqual(Stream stream) : UnaryPrimitive(stream) {}
    +
    1149
    +
    1150 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1151 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1152
    +
    1153 DEFINE_VMAP()
    +
    1154 DEFINE_GRADS()
    +
    1155 DEFINE_PRINT(GreaterEqual)
    +
    1156 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1157 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1158};
    -
    1151
    -
    1152 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1153 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1154
    -
    1155 DEFINE_VMAP()
    -
    1156 DEFINE_GRADS()
    -
    1157 DEFINE_PRINT(Hadamard)
    -
    1158 DEFINE_INPUT_OUTPUT_SHAPE()
    1159
    -
    1160 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1161 auto state() const {
    -
    1162 return scale_;
    -
    1163 }
    +
    +
    1160class Hadamard : public UnaryPrimitive {
    +
    1161 public:
    +
    +
    1162 explicit Hadamard(Stream stream, float scale)
    +
    1163 : UnaryPrimitive(stream), scale_(scale) {}
    1164
    -
    1165 private:
    -
    1166 float scale_;
    -
    1167};
    -
    -
    1168
    -
    -
    1169class Imag : public UnaryPrimitive {
    -
    1170 public:
    -
    1171 explicit Imag(Stream stream) : UnaryPrimitive(stream) {}
    +
    1165 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1166 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1167
    +
    1168 DEFINE_VMAP()
    +
    1169 DEFINE_GRADS()
    +
    1170 DEFINE_PRINT(Hadamard)
    +
    1171 DEFINE_INPUT_OUTPUT_SHAPE()
    1172
    -
    1173 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1174 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1175
    -
    1176 DEFINE_VMAP()
    -
    1177 DEFINE_GRADS()
    -
    1178 DEFINE_PRINT(Imag)
    -
    1179 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1180 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1181};
    +
    1173 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1174 auto state() const {
    +
    1175 return scale_;
    +
    1176 }
    -
    1182
    -
    -
    1183class Less : public UnaryPrimitive {
    -
    1184 public:
    -
    1185 explicit Less(Stream stream) : UnaryPrimitive(stream) {}
    -
    1186
    -
    1187 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1188 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1189
    -
    1190 DEFINE_VMAP()
    -
    1191 DEFINE_GRADS()
    -
    1192 DEFINE_PRINT(Less)
    -
    1193 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1194 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1195};
    +
    1177
    +
    1178 private:
    +
    1179 float scale_;
    +
    1180};
    -
    1196
    -
    -
    1197class LessEqual : public UnaryPrimitive {
    -
    1198 public:
    -
    1199 explicit LessEqual(Stream stream) : UnaryPrimitive(stream) {}
    -
    1200
    -
    1201 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1202 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1203
    -
    1204 DEFINE_VMAP()
    -
    1205 DEFINE_GRADS()
    -
    1206 DEFINE_PRINT(LessEqual)
    -
    1207 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1208 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1209};
    +
    1181
    +
    +
    1182class Imag : public UnaryPrimitive {
    +
    1183 public:
    +
    1184 explicit Imag(Stream stream) : UnaryPrimitive(stream) {}
    +
    1185
    +
    1186 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1187 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1188
    +
    1189 DEFINE_VMAP()
    +
    1190 DEFINE_GRADS()
    +
    1191 DEFINE_PRINT(Imag)
    +
    1192 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1193 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1194};
    -
    1210
    -
    -
    1211class Load : public UnaryPrimitive {
    -
    1212 public:
    -
    -
    1213 explicit Load(
    -
    1214 Stream stream,
    -
    1215 std::shared_ptr<io::Reader> reader,
    -
    1216 size_t offset,
    -
    1217 bool swap_endianness = false)
    -
    1218 : UnaryPrimitive(stream),
    -
    1219 reader_(std::move(reader)),
    -
    1220 offset_(offset),
    -
    1221 swap_endianness_(swap_endianness) {
    -
    1222 if (stream.device == Device::gpu) {
    -
    1223 io_stream();
    -
    1224 }
    -
    1225 }
    +
    1195
    +
    +
    1196class Less : public UnaryPrimitive {
    +
    1197 public:
    +
    1198 explicit Less(Stream stream) : UnaryPrimitive(stream) {}
    +
    1199
    +
    1200 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1201 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1202
    +
    1203 DEFINE_VMAP()
    +
    1204 DEFINE_GRADS()
    +
    1205 DEFINE_PRINT(Less)
    +
    1206 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1207 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1208};
    -
    1226
    -
    1227 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1228 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1229
    -
    1230 DEFINE_PRINT(Load)
    -
    1231
    -
    1232 private:
    -
    1233 Stream& io_stream() {
    -
    1234 static Stream io_stream = new_stream(Device::cpu);
    -
    1235 return io_stream;
    -
    1236 };
    -
    1237 std::shared_ptr<io::Reader> reader_;
    -
    1238 size_t offset_;
    -
    1239 bool swap_endianness_;
    -
    1240};
    +
    1209
    +
    +
    1210class LessEqual : public UnaryPrimitive {
    +
    1211 public:
    +
    1212 explicit LessEqual(Stream stream) : UnaryPrimitive(stream) {}
    +
    1213
    +
    1214 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1215 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1216
    +
    1217 DEFINE_VMAP()
    +
    1218 DEFINE_GRADS()
    +
    1219 DEFINE_PRINT(LessEqual)
    +
    1220 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1221 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1222};
    -
    1241
    -
    -
    1242class Log : public UnaryPrimitive {
    -
    1243 public:
    -
    1244 enum Base { two, ten, e };
    -
    1245
    -
    -
    1246 explicit Log(Stream stream, Base base)
    -
    1247 : UnaryPrimitive(stream), base_(base) {}
    +
    1223
    +
    +
    1224class Load : public UnaryPrimitive {
    +
    1225 public:
    +
    +
    1226 explicit Load(
    +
    1227 Stream stream,
    +
    1228 std::shared_ptr<io::Reader> reader,
    +
    1229 size_t offset,
    +
    1230 bool swap_endianness = false)
    +
    1231 : UnaryPrimitive(stream),
    +
    1232 reader_(std::move(reader)),
    +
    1233 offset_(offset),
    +
    1234 swap_endianness_(swap_endianness) {
    +
    1235 if (stream.device == Device::gpu) {
    +
    1236 io_stream();
    +
    1237 }
    +
    1238 }
    -
    1248
    -
    1249 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1250 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1251
    -
    1252 DEFINE_VMAP()
    -
    1253 DEFINE_GRADS()
    -
    1254 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1255 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1256
    -
    -
    1257 Base state() const {
    -
    1258 return base_;
    -
    1259 };
    +
    1239
    +
    1240 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1241 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1242
    +
    1243 DEFINE_PRINT(Load)
    +
    1244
    +
    1245 private:
    +
    1246 Stream& io_stream() {
    +
    1247 static Stream io_stream = new_stream(Device::cpu);
    +
    1248 return io_stream;
    +
    1249 };
    +
    1250 std::shared_ptr<io::Reader> reader_;
    +
    1251 size_t offset_;
    +
    1252 bool swap_endianness_;
    +
    1253};
    -
    1260
    -
    -
    1261 void print(std::ostream& os) override {
    -
    1262 switch (base_) {
    -
    1263 case e:
    -
    1264 os << "Log";
    -
    1265 break;
    -
    1266 case two:
    -
    1267 os << "Log2";
    -
    1268 break;
    -
    1269 case ten:
    -
    1270 os << "Log10";
    -
    1271 break;
    -
    1272 }
    -
    1273 }
    +
    1254
    +
    +
    1255class Log : public UnaryPrimitive {
    +
    1256 public:
    +
    1257 enum Base { two, ten, e };
    +
    1258
    +
    +
    1259 explicit Log(Stream stream, Base base)
    +
    1260 : UnaryPrimitive(stream), base_(base) {}
    -
    1274
    -
    1275 private:
    -
    1276 Base base_;
    -
    1277};
    +
    1261
    +
    1262 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1263 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1264
    +
    1265 DEFINE_VMAP()
    +
    1266 DEFINE_GRADS()
    +
    1267 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1268 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1269
    +
    +
    1270 Base state() const {
    +
    1271 return base_;
    +
    1272 };
    -
    1278
    -
    -
    1279class Log1p : public UnaryPrimitive {
    -
    1280 public:
    -
    1281 explicit Log1p(Stream stream) : UnaryPrimitive(stream) {}
    -
    1282
    -
    1283 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1284 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1285
    -
    1286 DEFINE_VMAP()
    -
    1287 DEFINE_GRADS()
    -
    1288 DEFINE_PRINT(Log1p)
    -
    1289 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1273
    +
    +
    1274 void print(std::ostream& os) override {
    +
    1275 switch (base_) {
    +
    1276 case e:
    +
    1277 os << "Log";
    +
    1278 break;
    +
    1279 case two:
    +
    1280 os << "Log2";
    +
    1281 break;
    +
    1282 case ten:
    +
    1283 os << "Log10";
    +
    1284 break;
    +
    1285 }
    +
    1286 }
    +
    +
    1287
    +
    1288 private:
    +
    1289 Base base_;
    1290};
    1291
    -
    1292class LogicalNot : public UnaryPrimitive {
    +
    1292class Log1p : public UnaryPrimitive {
    1293 public:
    -
    1294 explicit LogicalNot(Stream stream) : UnaryPrimitive(stream) {}
    +
    1294 explicit Log1p(Stream stream) : UnaryPrimitive(stream) {}
    1295
    -
    1296 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1297 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1296 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1297 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    1298
    -
    1299 DEFINE_VMAP()
    -
    1300 DEFINE_GRADS()
    -
    1301 DEFINE_PRINT(LogicalNot)
    -
    1302 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1303 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1304};
    +
    1299 DEFINE_VMAP()
    +
    1300 DEFINE_GRADS()
    +
    1301 DEFINE_PRINT(Log1p)
    +
    1302 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1303};
    -
    1305
    -
    -
    1306class LogicalAnd : public UnaryPrimitive {
    -
    1307 public:
    -
    1308 explicit LogicalAnd(Stream stream) : UnaryPrimitive(stream) {}
    -
    1309
    -
    1310 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1311 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1312
    -
    1313 DEFINE_VMAP()
    -
    1314 DEFINE_GRADS()
    -
    1315 DEFINE_PRINT(LogicalAnd)
    -
    1316 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1317 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1318};
    +
    1304
    +
    +
    1305class LogicalNot : public UnaryPrimitive {
    +
    1306 public:
    +
    1307 explicit LogicalNot(Stream stream) : UnaryPrimitive(stream) {}
    +
    1308
    +
    1309 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1310 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1311
    +
    1312 DEFINE_VMAP()
    +
    1313 DEFINE_GRADS()
    +
    1314 DEFINE_PRINT(LogicalNot)
    +
    1315 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1316 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1317};
    -
    1319
    -
    -
    1320class LogicalOr : public UnaryPrimitive {
    -
    1321 public:
    -
    1322 explicit LogicalOr(Stream stream) : UnaryPrimitive(stream) {}
    -
    1323
    -
    1324 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1325 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1326
    -
    1327 DEFINE_VMAP()
    -
    1328 DEFINE_GRADS()
    -
    1329 DEFINE_PRINT(LogicalOr)
    -
    1330 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1331 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1332};
    +
    1318
    +
    +
    1319class LogicalAnd : public UnaryPrimitive {
    +
    1320 public:
    +
    1321 explicit LogicalAnd(Stream stream) : UnaryPrimitive(stream) {}
    +
    1322
    +
    1323 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1324 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1325
    +
    1326 DEFINE_VMAP()
    +
    1327 DEFINE_GRADS()
    +
    1328 DEFINE_PRINT(LogicalAnd)
    +
    1329 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1330 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1331};
    -
    1333
    -
    -
    1334class LogAddExp : public UnaryPrimitive {
    -
    1335 public:
    -
    1336 explicit LogAddExp(Stream stream) : UnaryPrimitive(stream) {}
    -
    1337
    -
    1338 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1339 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1340
    -
    1341 DEFINE_VMAP()
    -
    1342 DEFINE_GRADS()
    -
    1343 DEFINE_PRINT(LogAddExp)
    -
    1344 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1345 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1346};
    +
    1332
    +
    +
    1333class LogicalOr : public UnaryPrimitive {
    +
    1334 public:
    +
    1335 explicit LogicalOr(Stream stream) : UnaryPrimitive(stream) {}
    +
    1336
    +
    1337 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1338 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1339
    +
    1340 DEFINE_VMAP()
    +
    1341 DEFINE_GRADS()
    +
    1342 DEFINE_PRINT(LogicalOr)
    +
    1343 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1344 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1345};
    -
    1347
    -
    -
    1348class Matmul : public UnaryPrimitive {
    -
    1349 public:
    -
    1350 explicit Matmul(Stream stream) : UnaryPrimitive(stream) {}
    -
    1351
    -
    1352 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1353 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1354
    -
    1355 DEFINE_GRADS()
    -
    1356 DEFINE_VMAP()
    -
    1357 DEFINE_PRINT(Matmul)
    -
    1358 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1359 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    1360};
    +
    1346
    +
    +
    1347class LogAddExp : public UnaryPrimitive {
    +
    1348 public:
    +
    1349 explicit LogAddExp(Stream stream) : UnaryPrimitive(stream) {}
    +
    1350
    +
    1351 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1352 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1353
    +
    1354 DEFINE_VMAP()
    +
    1355 DEFINE_GRADS()
    +
    1356 DEFINE_PRINT(LogAddExp)
    +
    1357 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1358 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1359};
    -
    1361
    -
    -
    1362class Maximum : public UnaryPrimitive {
    -
    1363 public:
    -
    1364 explicit Maximum(Stream stream) : UnaryPrimitive(stream) {}
    -
    1365
    -
    1366 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1367 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1368
    -
    1369 DEFINE_VMAP()
    -
    1370 DEFINE_GRADS()
    -
    1371 DEFINE_PRINT(Maximum)
    -
    1372 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1373 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1374};
    +
    1360
    +
    +
    1361class Matmul : public UnaryPrimitive {
    +
    1362 public:
    +
    1363 explicit Matmul(Stream stream) : UnaryPrimitive(stream) {}
    +
    1364
    +
    1365 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1366 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1367
    +
    1368 DEFINE_GRADS()
    +
    1369 DEFINE_VMAP()
    +
    1370 DEFINE_PRINT(Matmul)
    +
    1371 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1372 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    1373};
    -
    1375
    -
    -
    1376class Minimum : public UnaryPrimitive {
    -
    1377 public:
    -
    1378 explicit Minimum(Stream stream) : UnaryPrimitive(stream) {}
    -
    1379
    -
    1380 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1381 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1382
    -
    1383 DEFINE_VMAP()
    -
    1384 DEFINE_GRADS()
    -
    1385 DEFINE_PRINT(Minimum)
    -
    1386 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1387 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1388};
    +
    1374
    +
    +
    1375class Maximum : public UnaryPrimitive {
    +
    1376 public:
    +
    1377 explicit Maximum(Stream stream) : UnaryPrimitive(stream) {}
    +
    1378
    +
    1379 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1380 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1381
    +
    1382 DEFINE_VMAP()
    +
    1383 DEFINE_GRADS()
    +
    1384 DEFINE_PRINT(Maximum)
    +
    1385 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1386 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1387};
    -
    1389
    -
    -
    1390class Multiply : public UnaryPrimitive {
    -
    1391 public:
    -
    1392 explicit Multiply(Stream stream) : UnaryPrimitive(stream) {}
    -
    1393
    -
    1394 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1395 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1396
    -
    1397 DEFINE_VMAP()
    -
    1398 DEFINE_GRADS()
    -
    1399 DEFINE_PRINT(Multiply)
    -
    1400 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1401 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1402};
    +
    1388
    +
    +
    1389class Minimum : public UnaryPrimitive {
    +
    1390 public:
    +
    1391 explicit Minimum(Stream stream) : UnaryPrimitive(stream) {}
    +
    1392
    +
    1393 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1394 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1395
    +
    1396 DEFINE_VMAP()
    +
    1397 DEFINE_GRADS()
    +
    1398 DEFINE_PRINT(Minimum)
    +
    1399 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1400 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1401};
    -
    1403
    -
    -
    1404class Negative : public UnaryPrimitive {
    -
    1405 public:
    -
    1406 explicit Negative(Stream stream) : UnaryPrimitive(stream) {}
    -
    1407
    -
    1408 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1409 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1410
    -
    1411 DEFINE_VMAP()
    -
    1412 DEFINE_GRADS()
    -
    1413 DEFINE_PRINT(Negative)
    -
    1414 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1415 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1416};
    +
    1402
    +
    +
    1403class Multiply : public UnaryPrimitive {
    +
    1404 public:
    +
    1405 explicit Multiply(Stream stream) : UnaryPrimitive(stream) {}
    +
    1406
    +
    1407 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1408 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1409
    +
    1410 DEFINE_VMAP()
    +
    1411 DEFINE_GRADS()
    +
    1412 DEFINE_PRINT(Multiply)
    +
    1413 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1414 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1415};
    -
    1417
    -
    -
    1418class NotEqual : public UnaryPrimitive {
    -
    1419 public:
    -
    1420 explicit NotEqual(Stream stream) : UnaryPrimitive(stream) {}
    -
    1421
    -
    1422 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1423 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1424
    -
    1425 DEFINE_VMAP()
    -
    1426 DEFINE_GRADS()
    -
    1427 DEFINE_PRINT(NotEqual)
    -
    1428 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1429 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1430};
    +
    1416
    +
    +
    1417class Negative : public UnaryPrimitive {
    +
    1418 public:
    +
    1419 explicit Negative(Stream stream) : UnaryPrimitive(stream) {}
    +
    1420
    +
    1421 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1422 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1423
    +
    1424 DEFINE_VMAP()
    +
    1425 DEFINE_GRADS()
    +
    1426 DEFINE_PRINT(Negative)
    +
    1427 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1428 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1429};
    -
    1431
    -
    -
    1432class NumberOfElements : public UnaryPrimitive {
    -
    1433 public:
    -
    -
    1434 explicit NumberOfElements(
    -
    1435 Stream stream,
    -
    1436 std::vector<int> axes,
    -
    1437 bool inverted,
    -
    1438 Dtype dtype)
    -
    1439 : UnaryPrimitive(stream),
    -
    1440 axes_(std::move(axes)),
    -
    1441 inverted_(inverted),
    -
    1442 dtype_(dtype) {}
    +
    1430
    +
    +
    1431class NotEqual : public UnaryPrimitive {
    +
    1432 public:
    +
    1433 explicit NotEqual(Stream stream) : UnaryPrimitive(stream) {}
    +
    1434
    +
    1435 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1436 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1437
    +
    1438 DEFINE_VMAP()
    +
    1439 DEFINE_GRADS()
    +
    1440 DEFINE_PRINT(NotEqual)
    +
    1441 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1442 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1443};
    -
    1443
    -
    1444 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1445 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1446
    -
    1447 DEFINE_VMAP()
    -
    1448 DEFINE_PRINT(NumberOfElements)
    -
    1449 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1450 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override {
    -
    1451 return {{}};
    -
    1452 }
    -
    -
    -
    1453 std::tuple<std::vector<int>, bool, Dtype> state() const {
    -
    1454 return {axes_, inverted_, dtype_};
    -
    1455 }
    +
    1444
    +
    +
    1445class NumberOfElements : public UnaryPrimitive {
    +
    1446 public:
    +
    +
    1447 explicit NumberOfElements(
    +
    1448 Stream stream,
    +
    1449 std::vector<int> axes,
    +
    1450 bool inverted,
    +
    1451 Dtype dtype)
    +
    1452 : UnaryPrimitive(stream),
    +
    1453 axes_(std::move(axes)),
    +
    1454 inverted_(inverted),
    +
    1455 dtype_(dtype) {}
    1456
    -
    1457 private:
    -
    1458 std::vector<int> axes_;
    -
    1459 bool inverted_;
    -
    1460 Dtype dtype_;
    -
    1461
    -
    1462 void eval(const std::vector<array>& inputs, array& out);
    -
    1463};
    +
    1457 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1458 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1459
    +
    1460 DEFINE_VMAP()
    +
    1461 DEFINE_PRINT(NumberOfElements)
    +
    1462 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1463 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override {
    +
    1464 return {{}};
    +
    1465 }
    -
    1464
    -
    -
    1465class Pad : public UnaryPrimitive {
    -
    1466 public:
    -
    -
    1467 explicit Pad(
    -
    1468 Stream stream,
    -
    1469 const std::vector<int>& axes,
    -
    1470 const Shape& low_pad_size,
    -
    1471 const Shape& high_pad_size)
    -
    1472 : UnaryPrimitive(stream),
    -
    1473 axes_(axes),
    -
    1474 low_pad_size_(low_pad_size),
    -
    1475 high_pad_size_(high_pad_size) {}
    +
    +
    1466 std::tuple<std::vector<int>, bool, Dtype> state() const {
    +
    1467 return {axes_, inverted_, dtype_};
    +
    1468 }
    -
    1476
    -
    1477 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1478 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1479
    -
    1480 DEFINE_VMAP()
    -
    1481 DEFINE_GRADS()
    -
    1482 DEFINE_PRINT(Pad)
    -
    1483 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1484 auto state() const {
    -
    1485 return std::make_tuple(axes_, low_pad_size_, high_pad_size_);
    -
    1486 }
    +
    1469
    +
    1470 private:
    +
    1471 std::vector<int> axes_;
    +
    1472 bool inverted_;
    +
    1473 Dtype dtype_;
    +
    1474
    +
    1475 void eval(const std::vector<array>& inputs, array& out);
    +
    1476};
    -
    1487
    -
    1488 private:
    -
    1489 std::vector<int> axes_;
    -
    1490 Shape low_pad_size_;
    -
    1491 Shape high_pad_size_;
    -
    1492};
    +
    1477
    +
    +
    1478class Pad : public UnaryPrimitive {
    +
    1479 public:
    +
    +
    1480 explicit Pad(
    +
    1481 Stream stream,
    +
    1482 const std::vector<int>& axes,
    +
    1483 const Shape& low_pad_size,
    +
    1484 const Shape& high_pad_size)
    +
    1485 : UnaryPrimitive(stream),
    +
    1486 axes_(axes),
    +
    1487 low_pad_size_(low_pad_size),
    +
    1488 high_pad_size_(high_pad_size) {}
    -
    1493
    -
    -
    1494class Partition : public UnaryPrimitive {
    -
    1495 public:
    -
    -
    1496 explicit Partition(Stream stream, int kth, int axis)
    -
    1497 : UnaryPrimitive(stream), kth_(kth), axis_(axis) {}
    +
    1489
    +
    1490 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1491 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1492
    +
    1493 DEFINE_VMAP()
    +
    1494 DEFINE_GRADS()
    +
    1495 DEFINE_PRINT(Pad)
    +
    1496 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1497 auto state() const {
    +
    1498 return std::make_tuple(axes_, low_pad_size_, high_pad_size_);
    +
    1499 }
    -
    1498
    -
    1499 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1500 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1501
    -
    1502 DEFINE_VMAP()
    -
    1503 DEFINE_GRADS()
    -
    1504 DEFINE_PRINT(Partition)
    -
    1505 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1506 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1507 auto state() const {
    -
    1508 return std::make_pair(kth_, axis_);
    -
    1509 };
    +
    1500
    +
    1501 private:
    +
    1502 std::vector<int> axes_;
    +
    1503 Shape low_pad_size_;
    +
    1504 Shape high_pad_size_;
    +
    1505};
    -
    1510
    -
    1511 private:
    -
    1512 int kth_;
    -
    1513 int axis_;
    -
    1514};
    +
    1506
    +
    +
    1507class Partition : public UnaryPrimitive {
    +
    1508 public:
    +
    +
    1509 explicit Partition(Stream stream, int kth, int axis)
    +
    1510 : UnaryPrimitive(stream), kth_(kth), axis_(axis) {}
    -
    1515
    -
    -
    1516class Power : public UnaryPrimitive {
    -
    1517 public:
    -
    1518 explicit Power(Stream stream) : UnaryPrimitive(stream) {}
    -
    1519
    -
    1520 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1521 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1522
    -
    1523 DEFINE_VMAP()
    -
    1524 DEFINE_GRADS()
    -
    1525 DEFINE_PRINT(Power)
    -
    1526 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1527 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1528};
    +
    1511
    +
    1512 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1513 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1514
    +
    1515 DEFINE_VMAP()
    +
    1516 DEFINE_GRADS()
    +
    1517 DEFINE_PRINT(Partition)
    +
    1518 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1519 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1520 auto state() const {
    +
    1521 return std::make_pair(kth_, axis_);
    +
    1522 };
    -
    1529
    -
    -
    1530class QuantizedMatmul : public UnaryPrimitive {
    -
    1531 public:
    -
    -
    1532 explicit QuantizedMatmul(
    -
    1533 Stream stream,
    -
    1534 int group_size,
    -
    1535 int bits,
    -
    1536 bool transpose)
    -
    1537 : UnaryPrimitive(stream),
    -
    1538 group_size_(group_size),
    -
    1539 bits_(bits),
    -
    1540 transpose_(transpose) {}
    +
    1523
    +
    1524 private:
    +
    1525 int kth_;
    +
    1526 int axis_;
    +
    1527};
    -
    1541
    -
    1542 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1543 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1544
    -
    1545 DEFINE_VMAP()
    -
    1546 DEFINE_GRADS()
    -
    1547 DEFINE_PRINT(QuantizedMatmul)
    -
    1548 bool is_equivalent(const Primitive& other) const override;
    -
    1549 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    -
    1550 auto state() const {
    -
    1551 return std::make_tuple(group_size_, bits_, transpose_);
    -
    1552 }
    +
    1528
    +
    +
    1529class Power : public UnaryPrimitive {
    +
    1530 public:
    +
    1531 explicit Power(Stream stream) : UnaryPrimitive(stream) {}
    +
    1532
    +
    1533 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1534 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1535
    +
    1536 DEFINE_VMAP()
    +
    1537 DEFINE_GRADS()
    +
    1538 DEFINE_PRINT(Power)
    +
    1539 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1540 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1541};
    -
    1553
    -
    1554 private:
    -
    1555 int group_size_;
    -
    1556 int bits_;
    -
    1557 bool transpose_;
    -
    1558};
    +
    1542
    +
    +
    1543class QuantizedMatmul : public UnaryPrimitive {
    +
    1544 public:
    +
    +
    1545 explicit QuantizedMatmul(
    +
    1546 Stream stream,
    +
    1547 int group_size,
    +
    1548 int bits,
    +
    1549 bool transpose)
    +
    1550 : UnaryPrimitive(stream),
    +
    1551 group_size_(group_size),
    +
    1552 bits_(bits),
    +
    1553 transpose_(transpose) {}
    -
    1559
    -
    -
    1560class GatherQMM : public UnaryPrimitive {
    -
    1561 public:
    -
    -
    1562 explicit GatherQMM(Stream stream, int group_size, int bits, bool transpose)
    -
    1563 : UnaryPrimitive(stream),
    -
    1564 group_size_(group_size),
    -
    1565 bits_(bits),
    -
    1566 transpose_(transpose) {}
    +
    1554
    +
    1555 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1556 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1557
    +
    1558 DEFINE_VMAP()
    +
    1559 DEFINE_GRADS()
    +
    1560 DEFINE_PRINT(QuantizedMatmul)
    +
    1561 bool is_equivalent(const Primitive& other) const override;
    +
    1562 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    1563 auto state() const {
    +
    1564 return std::make_tuple(group_size_, bits_, transpose_);
    +
    1565 }
    -
    1567
    -
    1568 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1569 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1570
    -
    1571 DEFINE_VMAP()
    -
    1572 DEFINE_GRADS()
    -
    1573 DEFINE_PRINT(GatherQMM)
    -
    1574 bool is_equivalent(const Primitive& other) const override;
    +
    1566
    +
    1567 private:
    +
    1568 int group_size_;
    +
    1569 int bits_;
    +
    1570 bool transpose_;
    +
    1571};
    +
    +
    1572
    +
    +
    1573class GatherQMM : public UnaryPrimitive {
    +
    1574 public:
    -
    1575 auto state() const {
    -
    1576 return std::make_tuple(group_size_, bits_, transpose_);
    -
    1577 }
    +
    1575 explicit GatherQMM(Stream stream, int group_size, int bits, bool transpose)
    +
    1576 : UnaryPrimitive(stream),
    +
    1577 group_size_(group_size),
    +
    1578 bits_(bits),
    +
    1579 transpose_(transpose) {}
    -
    1578
    -
    1579 private:
    -
    1580 int group_size_;
    -
    1581 int bits_;
    -
    1582 bool transpose_;
    -
    1583};
    +
    1580
    +
    1581 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1582 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1583
    +
    1584 DEFINE_VMAP()
    +
    1585 DEFINE_GRADS()
    +
    1586 DEFINE_PRINT(GatherQMM)
    +
    1587 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1588 auto state() const {
    +
    1589 return std::make_tuple(group_size_, bits_, transpose_);
    +
    1590 }
    -
    1584
    -
    -
    1585class RandomBits : public UnaryPrimitive {
    -
    1586 public:
    -
    -
    1587 explicit RandomBits(Stream stream, const Shape& shape, int width)
    -
    1588 : UnaryPrimitive(stream), shape_(shape), width_(width) {}
    +
    1591
    +
    1592 private:
    +
    1593 int group_size_;
    +
    1594 int bits_;
    +
    1595 bool transpose_;
    +
    1596};
    -
    1589
    -
    1590 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1591 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1592
    -
    1593 DEFINE_VMAP()
    -
    1594 DEFINE_PRINT(RandomBits)
    -
    1595 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1596 std::pair<std::vector<int>, int> state() const {
    -
    1597 return {shape_, width_};
    -
    1598 };
    +
    1597
    +
    +
    1598class RandomBits : public UnaryPrimitive {
    +
    1599 public:
    +
    +
    1600 explicit RandomBits(Stream stream, const Shape& shape, int width)
    +
    1601 : UnaryPrimitive(stream), shape_(shape), width_(width) {}
    -
    1599
    -
    1600 private:
    -
    1601 Shape shape_;
    -
    1602 int width_;
    -
    1603};
    +
    1602
    +
    1603 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1604 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1605
    +
    1606 DEFINE_VMAP()
    +
    1607 DEFINE_PRINT(RandomBits)
    +
    1608 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1609 std::pair<std::vector<int>, int> state() const {
    +
    1610 return {shape_, width_};
    +
    1611 };
    -
    1604
    -
    -
    1605class Real : public UnaryPrimitive {
    -
    1606 public:
    -
    1607 explicit Real(Stream stream) : UnaryPrimitive(stream) {}
    -
    1608
    -
    1609 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1610 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1611
    -
    1612 DEFINE_VMAP()
    -
    1613 DEFINE_GRADS()
    -
    1614 DEFINE_PRINT(Real)
    -
    1615 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1616 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1617};
    +
    1612
    +
    1613 private:
    +
    1614 Shape shape_;
    +
    1615 int width_;
    +
    1616};
    -
    1618
    -
    -
    1619class Reshape : public UnaryPrimitive {
    -
    1620 public:
    -
    -
    1621 explicit Reshape(Stream stream, const Shape& shape)
    -
    1622 : UnaryPrimitive(stream), shape_(shape) {}
    +
    1617
    +
    +
    1618class Real : public UnaryPrimitive {
    +
    1619 public:
    +
    1620 explicit Real(Stream stream) : UnaryPrimitive(stream) {}
    +
    1621
    +
    1622 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1623 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1624
    +
    1625 DEFINE_VMAP()
    +
    1626 DEFINE_GRADS()
    +
    1627 DEFINE_PRINT(Real)
    +
    1628 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1629 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1630};
    -
    1623
    -
    1624 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1625 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1626
    -
    1627 DEFINE_VMAP()
    -
    1628 DEFINE_GRADS()
    -
    1629 DEFINE_PRINT(Reshape)
    -
    1630 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1631 std::vector<int> state() const {
    -
    1632 return shape_;
    -
    1633 };
    +
    1631
    +
    +
    1632class Reshape : public UnaryPrimitive {
    +
    1633 public:
    +
    +
    1634 explicit Reshape(Stream stream, const Shape& shape)
    +
    1635 : UnaryPrimitive(stream), shape_(shape) {}
    -
    1634 static Shape output_shape(const array& input, Shape shape);
    -
    1635 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    1636
    -
    1637 private:
    -
    1638 Shape shape_;
    -
    1639};
    +
    1637 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1638 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1639
    +
    1640 DEFINE_VMAP()
    +
    1641 DEFINE_GRADS()
    +
    1642 DEFINE_PRINT(Reshape)
    +
    1643 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1644 std::vector<int> state() const {
    +
    1645 return shape_;
    +
    1646 };
    -
    1640
    -
    -
    1641class Reduce : public UnaryPrimitive {
    -
    1642 public:
    -
    1643 enum ReduceType { And, Or, Sum, Prod, Min, Max };
    -
    1644
    -
    -
    1645 explicit Reduce(
    -
    1646 Stream stream,
    -
    1647 ReduceType reduce_type,
    -
    1648 const std::vector<int>& axes)
    -
    1649 : UnaryPrimitive(stream), reduce_type_(reduce_type), axes_(axes) {}
    +
    1647 static Shape output_shape(const array& input, Shape shape);
    +
    1648 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    1649
    +
    1650 private:
    +
    1651 Shape shape_;
    +
    1652};
    -
    1650
    -
    1651 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1652 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    1653
    -
    1654 DEFINE_VMAP()
    -
    1655
    -
    1656 std::vector<array> vjp(
    -
    1657 const std::vector<array>& primals,
    -
    1658 const std::vector<array>& cotangents,
    -
    1659 const std::vector<int>& argnums,
    -
    1660 const std::vector<array>& outputs) override;
    -
    1661
    -
    1662 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    1654class Reduce : public UnaryPrimitive {
    +
    1655 public:
    +
    1656 enum ReduceType { And, Or, Sum, Prod, Min, Max };
    +
    1657
    +
    +
    1658 explicit Reduce(
    +
    1659 Stream stream,
    +
    1660 ReduceType reduce_type,
    +
    1661 const std::vector<int>& axes)
    +
    1662 : UnaryPrimitive(stream), reduce_type_(reduce_type), axes_(axes) {}
    +
    1663
    -
    -
    1664 void print(std::ostream& os) override {
    -
    1665 switch (reduce_type_) {
    -
    1666 case And:
    -
    1667 os << "And";
    -
    1668 break;
    -
    1669 case Or:
    -
    1670 os << "Or";
    -
    1671 break;
    -
    1672 case Sum:
    -
    1673 os << "Sum";
    -
    1674 break;
    -
    1675 case Prod:
    -
    1676 os << "Prod";
    -
    1677 break;
    -
    1678 case Min:
    -
    1679 os << "Min";
    -
    1680 break;
    -
    1681 case Max:
    -
    1682 os << "Max";
    -
    1683 break;
    -
    1684 }
    -
    1685 }
    +
    1664 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1665 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1666
    +
    1667 DEFINE_VMAP()
    +
    1668
    +
    1669 std::vector<array> vjp(
    +
    1670 const std::vector<array>& primals,
    +
    1671 const std::vector<array>& cotangents,
    +
    1672 const std::vector<int>& argnums,
    +
    1673 const std::vector<array>& outputs) override;
    +
    1674
    +
    1675 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    1676
    +
    +
    1677 void print(std::ostream& os) override {
    +
    1678 switch (reduce_type_) {
    +
    1679 case And:
    +
    1680 os << "And";
    +
    1681 break;
    +
    1682 case Or:
    +
    1683 os << "Or";
    +
    1684 break;
    +
    1685 case Sum:
    +
    1686 os << "Sum";
    +
    1687 break;
    +
    1688 case Prod:
    +
    1689 os << "Prod";
    +
    1690 break;
    +
    1691 case Min:
    +
    1692 os << "Min";
    +
    1693 break;
    +
    1694 case Max:
    +
    1695 os << "Max";
    +
    1696 break;
    +
    1697 }
    +
    1698 }
    -
    1686 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1687 std::pair<ReduceType, std::vector<int>> state() const {
    -
    1688 return {reduce_type_, axes_};
    -
    1689 };
    +
    1699 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1700 std::pair<ReduceType, std::vector<int>> state() const {
    +
    1701 return {reduce_type_, axes_};
    +
    1702 };
    -
    1690
    -
    1691 private:
    -
    1692 ReduceType reduce_type_;
    -
    1693 std::vector<int> axes_;
    -
    1694};
    +
    1703
    +
    1704 private:
    +
    1705 ReduceType reduce_type_;
    +
    1706 std::vector<int> axes_;
    +
    1707};
    -
    1695
    -
    -
    1696class Round : public UnaryPrimitive {
    -
    1697 public:
    -
    1698 explicit Round(Stream stream) : UnaryPrimitive(stream) {}
    -
    1699
    -
    1700 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1701 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1702
    -
    1703 DEFINE_VMAP()
    -
    1704 DEFINE_GRADS()
    -
    1705 DEFINE_PRINT(Round)
    -
    1706 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1707 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1708};
    +
    1708
    +
    +
    1709class Round : public UnaryPrimitive {
    +
    1710 public:
    +
    1711 explicit Round(Stream stream) : UnaryPrimitive(stream) {}
    +
    1712
    +
    1713 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1714 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1715
    +
    1716 DEFINE_VMAP()
    +
    1717 DEFINE_GRADS()
    +
    1718 DEFINE_PRINT(Round)
    +
    1719 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1720 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1721};
    -
    1709
    -
    -
    1710class Scan : public UnaryPrimitive {
    -
    1711 public:
    -
    1712 enum ReduceType { Max, Min, Sum, Prod };
    -
    1713
    -
    -
    1714 explicit Scan(
    -
    1715 Stream stream,
    -
    1716 ReduceType reduce_type,
    -
    1717 int axis,
    -
    1718 bool reverse,
    -
    1719 bool inclusive)
    -
    1720 : UnaryPrimitive(stream),
    -
    1721 reduce_type_(reduce_type),
    -
    1722 axis_(axis),
    -
    1723 reverse_(reverse),
    -
    1724 inclusive_(inclusive) {}
    +
    1722
    +
    +
    1723class Scan : public UnaryPrimitive {
    +
    1724 public:
    +
    1725 enum ReduceType { Max, Min, Sum, Prod };
    +
    1726
    +
    +
    1727 explicit Scan(
    +
    1728 Stream stream,
    +
    1729 ReduceType reduce_type,
    +
    1730 int axis,
    +
    1731 bool reverse,
    +
    1732 bool inclusive)
    +
    1733 : UnaryPrimitive(stream),
    +
    1734 reduce_type_(reduce_type),
    +
    1735 axis_(axis),
    +
    1736 reverse_(reverse),
    +
    1737 inclusive_(inclusive) {}
    -
    1725
    -
    1726 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1727 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1728
    -
    1729 DEFINE_VMAP()
    -
    1730 DEFINE_GRADS();
    -
    1731
    -
    -
    1732 void print(std::ostream& os) override {
    -
    1733 os << "Cum";
    -
    1734 switch (reduce_type_) {
    -
    1735 case Sum:
    -
    1736 os << "Sum";
    -
    1737 break;
    -
    1738 case Prod:
    -
    1739 os << "Prod";
    -
    1740 break;
    -
    1741 case Min:
    -
    1742 os << "Min";
    -
    1743 break;
    -
    1744 case Max:
    -
    1745 os << "Max";
    -
    1746 break;
    -
    1747 }
    -
    1748 }
    +
    1738
    +
    1739 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1740 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1741
    +
    1742 DEFINE_VMAP()
    +
    1743 DEFINE_GRADS();
    +
    1744
    +
    +
    1745 void print(std::ostream& os) override {
    +
    1746 os << "Cum";
    +
    1747 switch (reduce_type_) {
    +
    1748 case Sum:
    +
    1749 os << "Sum";
    +
    1750 break;
    +
    1751 case Prod:
    +
    1752 os << "Prod";
    +
    1753 break;
    +
    1754 case Min:
    +
    1755 os << "Min";
    +
    1756 break;
    +
    1757 case Max:
    +
    1758 os << "Max";
    +
    1759 break;
    +
    1760 }
    +
    1761 }
    -
    1749 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1750 auto state() const {
    -
    1751 return std::make_tuple(reduce_type_, axis_, reverse_, inclusive_);
    -
    1752 }
    +
    1762 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1763 auto state() const {
    +
    1764 return std::make_tuple(reduce_type_, axis_, reverse_, inclusive_);
    +
    1765 }
    -
    1753
    -
    1754 private:
    -
    1755 ReduceType reduce_type_;
    -
    1756 int axis_;
    -
    1757 bool reverse_;
    -
    1758 bool inclusive_;
    -
    1759};
    +
    1766
    +
    1767 private:
    +
    1768 ReduceType reduce_type_;
    +
    1769 int axis_;
    +
    1770 bool reverse_;
    +
    1771 bool inclusive_;
    +
    1772};
    -
    1760
    -
    -
    1761class Scatter : public UnaryPrimitive {
    -
    1762 public:
    -
    1763 enum ReduceType { Max, Min, Sum, Prod, None };
    -
    1764
    -
    -
    1765 explicit Scatter(
    -
    1766 Stream stream,
    -
    1767 ReduceType reduce_type,
    -
    1768 const std::vector<int>& axes)
    -
    1769 : UnaryPrimitive(stream), reduce_type_(reduce_type), axes_(axes) {}
    -
    -
    1770
    -
    1771 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1772 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    1773
    -
    1774 DEFINE_VMAP();
    -
    1775 DEFINE_GRADS();
    -
    1776
    -
    -
    1777 void print(std::ostream& os) override {
    -
    1778 os << "Scatter";
    -
    1779 switch (reduce_type_) {
    -
    1780 case Sum:
    -
    1781 os << " Sum";
    -
    1782 break;
    -
    1783 case Prod:
    -
    1784 os << " Prod";
    -
    1785 break;
    -
    1786 case Min:
    -
    1787 os << " Min";
    -
    1788 break;
    -
    1789 case Max:
    -
    1790 os << " Max";
    -
    1791 break;
    -
    1792 case None:
    -
    1793 break;
    -
    1794 }
    -
    1795 }
    +
    +
    1774class Scatter : public UnaryPrimitive {
    +
    1775 public:
    +
    1776 enum ReduceType { Max, Min, Sum, Prod, None };
    +
    1777
    +
    +
    1778 explicit Scatter(
    +
    1779 Stream stream,
    +
    1780 ReduceType reduce_type,
    +
    1781 const std::vector<int>& axes)
    +
    1782 : UnaryPrimitive(stream), reduce_type_(reduce_type), axes_(axes) {}
    -
    1796 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1797 std::pair<ReduceType, std::vector<int>> state() const {
    -
    1798 return {reduce_type_, axes_};
    -
    1799 };
    +
    1783
    +
    1784 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1785 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1786
    +
    1787 DEFINE_VMAP();
    +
    1788 DEFINE_GRADS();
    +
    1789
    +
    +
    1790 void print(std::ostream& os) override {
    +
    1791 os << "Scatter";
    +
    1792 switch (reduce_type_) {
    +
    1793 case Sum:
    +
    1794 os << " Sum";
    +
    1795 break;
    +
    1796 case Prod:
    +
    1797 os << " Prod";
    +
    1798 break;
    +
    1799 case Min:
    +
    1800 os << " Min";
    +
    1801 break;
    +
    1802 case Max:
    +
    1803 os << " Max";
    +
    1804 break;
    +
    1805 case None:
    +
    1806 break;
    +
    1807 }
    +
    1808 }
    -
    1800
    -
    1801 private:
    -
    1802 ReduceType reduce_type_;
    -
    1803 std::vector<int> axes_;
    -
    1804};
    -
    -
    1805
    -
    -
    1806class ScatterAxis : public UnaryPrimitive {
    -
    1807 public:
    -
    1808 enum ReduceType { Sum, None };
    -
    1809
    +
    1809 bool is_equivalent(const Primitive& other) const override;
    -
    1810 explicit ScatterAxis(Stream stream, ReduceType reduce_type, int axis)
    -
    1811 : UnaryPrimitive(stream), reduce_type_(reduce_type), axis_(axis) {}
    +
    1810 std::pair<ReduceType, std::vector<int>> state() const {
    +
    1811 return {reduce_type_, axes_};
    +
    1812 };
    +
    +
    1813
    +
    1814 private:
    +
    1815 ReduceType reduce_type_;
    +
    1816 std::vector<int> axes_;
    +
    1817};
    -
    1812
    -
    1813 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1814 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1815
    -
    1816 DEFINE_VMAP()
    -
    1817 DEFINE_GRADS()
    1818
    -
    -
    1819 void print(std::ostream& os) override {
    -
    1820 os << "ScatterAxis";
    -
    1821 switch (reduce_type_) {
    -
    1822 case Sum:
    -
    1823 os << " Sum";
    -
    1824 break;
    -
    1825 case None:
    -
    1826 break;
    -
    1827 }
    -
    1828 }
    +
    +
    1819class ScatterAxis : public UnaryPrimitive {
    +
    1820 public:
    +
    1821 enum ReduceType { Sum, None };
    +
    1822
    +
    +
    1823 explicit ScatterAxis(Stream stream, ReduceType reduce_type, int axis)
    +
    1824 : UnaryPrimitive(stream), reduce_type_(reduce_type), axis_(axis) {}
    -
    1829
    -
    1830 bool is_equivalent(const Primitive& other) const override;
    -
    1831 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    1825
    +
    1826 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1827 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1828
    +
    1829 DEFINE_VMAP()
    +
    1830 DEFINE_GRADS()
    +
    1831
    -
    1832 std::pair<ReduceType, int> state() const {
    -
    1833 return {reduce_type_, axis_};
    -
    1834 }
    +
    1832 void print(std::ostream& os) override {
    +
    1833 os << "ScatterAxis";
    +
    1834 switch (reduce_type_) {
    +
    1835 case Sum:
    +
    1836 os << " Sum";
    +
    1837 break;
    +
    1838 case None:
    +
    1839 break;
    +
    1840 }
    +
    1841 }
    -
    1835
    -
    1836 private:
    -
    1837 ReduceType reduce_type_;
    -
    1838 int axis_;
    -
    1839};
    +
    1842
    +
    1843 bool is_equivalent(const Primitive& other) const override;
    +
    1844 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    1845 std::pair<ReduceType, int> state() const {
    +
    1846 return {reduce_type_, axis_};
    +
    1847 }
    -
    1840
    -
    -
    1841class Sigmoid : public UnaryPrimitive {
    -
    1842 public:
    -
    1843 explicit Sigmoid(Stream stream) : UnaryPrimitive(stream) {}
    -
    1844
    -
    1845 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1846 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1847
    -
    1848 DEFINE_VMAP()
    -
    1849 DEFINE_GRADS()
    -
    1850 DEFINE_PRINT(Sigmoid)
    -
    1851 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1852 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1853};
    +
    1848
    +
    1849 private:
    +
    1850 ReduceType reduce_type_;
    +
    1851 int axis_;
    +
    1852};
    -
    1854
    -
    -
    1855class Sign : public UnaryPrimitive {
    -
    1856 public:
    -
    1857 explicit Sign(Stream stream) : UnaryPrimitive(stream) {}
    -
    1858
    -
    1859 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1860 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1861
    -
    1862 DEFINE_VMAP()
    -
    1863 DEFINE_GRADS()
    -
    1864 DEFINE_PRINT(Sign)
    -
    1865 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1866 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1867};
    +
    1853
    +
    +
    1854class Sigmoid : public UnaryPrimitive {
    +
    1855 public:
    +
    1856 explicit Sigmoid(Stream stream) : UnaryPrimitive(stream) {}
    +
    1857
    +
    1858 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1859 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1860
    +
    1861 DEFINE_VMAP()
    +
    1862 DEFINE_GRADS()
    +
    1863 DEFINE_PRINT(Sigmoid)
    +
    1864 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1865 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1866};
    -
    1868
    -
    -
    1869class Sin : public UnaryPrimitive {
    -
    1870 public:
    -
    1871 explicit Sin(Stream stream) : UnaryPrimitive(stream) {}
    -
    1872
    -
    1873 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1874 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1875
    -
    1876 DEFINE_VMAP()
    -
    1877 DEFINE_GRADS()
    -
    1878 DEFINE_PRINT(Sin)
    -
    1879 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1880 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1881};
    +
    1867
    +
    +
    1868class Sign : public UnaryPrimitive {
    +
    1869 public:
    +
    1870 explicit Sign(Stream stream) : UnaryPrimitive(stream) {}
    +
    1871
    +
    1872 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1873 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1874
    +
    1875 DEFINE_VMAP()
    +
    1876 DEFINE_GRADS()
    +
    1877 DEFINE_PRINT(Sign)
    +
    1878 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1879 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1880};
    -
    1882
    -
    -
    1883class Sinh : public UnaryPrimitive {
    -
    1884 public:
    -
    1885 explicit Sinh(Stream stream) : UnaryPrimitive(stream) {}
    -
    1886
    -
    1887 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1888 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1889
    -
    1890 DEFINE_VMAP()
    -
    1891 DEFINE_GRADS()
    -
    1892 DEFINE_PRINT(Sinh)
    -
    1893 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    1894 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    1895};
    +
    1881
    +
    +
    1882class Sin : public UnaryPrimitive {
    +
    1883 public:
    +
    1884 explicit Sin(Stream stream) : UnaryPrimitive(stream) {}
    +
    1885
    +
    1886 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1887 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1888
    +
    1889 DEFINE_VMAP()
    +
    1890 DEFINE_GRADS()
    +
    1891 DEFINE_PRINT(Sin)
    +
    1892 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1893 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1894};
    -
    1896
    -
    -
    1897class Slice : public UnaryPrimitive {
    -
    1898 public:
    -
    -
    1899 explicit Slice(
    -
    1900 Stream stream,
    -
    1901 const Shape& start_indices,
    -
    1902 const Shape& end_indices,
    -
    1903 const Shape& strides)
    -
    1904 : UnaryPrimitive(stream),
    -
    1905 start_indices_(start_indices),
    -
    1906 end_indices_(end_indices),
    -
    1907 strides_(strides) {}
    +
    1895
    +
    +
    1896class Sinh : public UnaryPrimitive {
    +
    1897 public:
    +
    1898 explicit Sinh(Stream stream) : UnaryPrimitive(stream) {}
    +
    1899
    +
    1900 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1901 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1902
    +
    1903 DEFINE_VMAP()
    +
    1904 DEFINE_GRADS()
    +
    1905 DEFINE_PRINT(Sinh)
    +
    1906 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    1907 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    1908};
    -
    1908
    -
    1909 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1910 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1911
    -
    1912 DEFINE_VMAP()
    -
    1913 DEFINE_GRADS()
    -
    1914 DEFINE_PRINT(Slice)
    -
    1915 bool is_equivalent(const Primitive& other) const override;
    -
    -
    1916 auto state() const {
    -
    1917 return std::make_tuple(start_indices_, end_indices_, strides_);
    -
    1918 }
    +
    1909
    +
    +
    1910class Slice : public UnaryPrimitive {
    +
    1911 public:
    +
    +
    1912 explicit Slice(
    +
    1913 Stream stream,
    +
    1914 const Shape& start_indices,
    +
    1915 const Shape& end_indices,
    +
    1916 const Shape& strides)
    +
    1917 : UnaryPrimitive(stream),
    +
    1918 start_indices_(start_indices),
    +
    1919 end_indices_(end_indices),
    +
    1920 strides_(strides) {}
    -
    1919
    -
    1920 private:
    -
    1921 Shape start_indices_;
    -
    1922 Shape end_indices_;
    -
    1923 Shape strides_;
    -
    1924};
    +
    1921
    +
    1922 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1923 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1924
    +
    1925 DEFINE_VMAP()
    +
    1926 DEFINE_GRADS()
    +
    1927 DEFINE_PRINT(Slice)
    +
    1928 bool is_equivalent(const Primitive& other) const override;
    +
    +
    1929 auto state() const {
    +
    1930 return std::make_tuple(start_indices_, end_indices_, strides_);
    +
    1931 }
    -
    1925
    -
    -
    1926class SliceUpdate : public UnaryPrimitive {
    -
    1927 public:
    -
    -
    1928 explicit SliceUpdate(
    -
    1929 Stream stream,
    -
    1930 const Shape& start_indices,
    -
    1931 const Shape& end_indices,
    -
    1932 const Shape& strides)
    -
    1933 : UnaryPrimitive(stream),
    -
    1934 start_indices_(start_indices),
    -
    1935 end_indices_(end_indices),
    -
    1936 strides_(strides) {}
    +
    1932
    +
    1933 private:
    +
    1934 Shape start_indices_;
    +
    1935 Shape end_indices_;
    +
    1936 Shape strides_;
    +
    1937};
    -
    1937
    -
    1938 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1939 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1940
    -
    1941 DEFINE_VMAP()
    -
    1942 DEFINE_GRADS()
    -
    1943 DEFINE_PRINT(SliceUpdate)
    -
    1944 bool is_equivalent(const Primitive& other) const override;
    -
    1945 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    -
    1946 auto state() const {
    -
    1947 return std::make_tuple(start_indices_, end_indices_, strides_);
    -
    1948 }
    +
    1938
    +
    +
    1939class SliceUpdate : public UnaryPrimitive {
    +
    1940 public:
    +
    +
    1941 explicit SliceUpdate(
    +
    1942 Stream stream,
    +
    1943 const Shape& start_indices,
    +
    1944 const Shape& end_indices,
    +
    1945 const Shape& strides)
    +
    1946 : UnaryPrimitive(stream),
    +
    1947 start_indices_(start_indices),
    +
    1948 end_indices_(end_indices),
    +
    1949 strides_(strides) {}
    -
    1949
    -
    1950 private:
    -
    1951 Shape start_indices_;
    -
    1952 Shape end_indices_;
    -
    1953 Shape strides_;
    -
    1954};
    -
    -
    1955
    -
    -
    1956class DynamicSlice : public UnaryPrimitive {
    -
    1957 public:
    -
    -
    1958 explicit DynamicSlice(Stream stream, std::vector<int> axes, Shape slice_size)
    -
    1959 : UnaryPrimitive(stream),
    -
    1960 axes_(std::move(axes)),
    -
    1961 slice_size_(std::move(slice_size)) {}
    +
    1950
    +
    1951 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1952 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1953
    +
    1954 DEFINE_VMAP()
    +
    1955 DEFINE_GRADS()
    +
    1956 DEFINE_PRINT(SliceUpdate)
    +
    1957 bool is_equivalent(const Primitive& other) const override;
    +
    1958 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    +
    1959 auto state() const {
    +
    1960 return std::make_tuple(start_indices_, end_indices_, strides_);
    +
    1961 }
    1962
    -
    1963 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1964 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    1965
    -
    1966 DEFINE_VMAP()
    -
    1967 DEFINE_GRADS()
    -
    1968 DEFINE_PRINT(DynamicSlice)
    -
    1969 bool is_equivalent(const Primitive& other) const override;
    -
    1970 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    1963 private:
    +
    1964 Shape start_indices_;
    +
    1965 Shape end_indices_;
    +
    1966 Shape strides_;
    +
    1967};
    +
    +
    1968
    +
    +
    1969class DynamicSlice : public UnaryPrimitive {
    +
    1970 public:
    -
    1971 auto state() const {
    -
    1972 return std::make_pair(axes_, slice_size_);
    -
    1973 }
    +
    1971 explicit DynamicSlice(Stream stream, std::vector<int> axes, Shape slice_size)
    +
    1972 : UnaryPrimitive(stream),
    +
    1973 axes_(std::move(axes)),
    +
    1974 slice_size_(std::move(slice_size)) {}
    -
    1974
    -
    1975 private:
    -
    1976 std::vector<int> axes_;
    -
    1977 Shape slice_size_;
    -
    1978};
    +
    1975
    +
    1976 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1977 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    1978
    +
    1979 DEFINE_VMAP()
    +
    1980 DEFINE_GRADS()
    +
    1981 DEFINE_PRINT(DynamicSlice)
    +
    1982 bool is_equivalent(const Primitive& other) const override;
    +
    1983 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    1984 auto state() const {
    +
    1985 return std::make_pair(axes_, slice_size_);
    +
    1986 }
    -
    1979
    -
    -
    1980class DynamicSliceUpdate : public UnaryPrimitive {
    -
    1981 public:
    -
    -
    1982 explicit DynamicSliceUpdate(Stream stream, std::vector<int> axes)
    -
    1983 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
    -
    -
    1984
    -
    1985 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    1986 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    1987
    -
    1988 DEFINE_VMAP()
    -
    1989 DEFINE_GRADS()
    -
    1990 DEFINE_PRINT(DynamicSliceUpdate)
    -
    1991 bool is_equivalent(const Primitive& other) const override;
    -
    1992 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    -
    1993 auto state() const {
    -
    1994 return axes_;
    -
    1995 }
    +
    1988 private:
    +
    1989 std::vector<int> axes_;
    +
    1990 Shape slice_size_;
    +
    1991};
    -
    1996
    -
    1997 private:
    -
    1998 std::vector<int> axes_;
    -
    1999};
    +
    1992
    +
    +
    1993class DynamicSliceUpdate : public UnaryPrimitive {
    +
    1994 public:
    +
    +
    1995 explicit DynamicSliceUpdate(Stream stream, std::vector<int> axes)
    +
    1996 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
    +
    1997
    +
    1998 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    1999 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    2000
    -
    -
    2001class Softmax : public UnaryPrimitive {
    -
    2002 public:
    -
    -
    2003 explicit Softmax(Stream stream, bool precise)
    -
    2004 : UnaryPrimitive(stream), precise_(precise) {}
    +
    2001 DEFINE_VMAP()
    +
    2002 DEFINE_GRADS()
    +
    2003 DEFINE_PRINT(DynamicSliceUpdate)
    +
    2004 bool is_equivalent(const Primitive& other) const override;
    +
    2005 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    +
    2006 auto state() const {
    +
    2007 return axes_;
    +
    2008 }
    +
    +
    2009
    +
    2010 private:
    +
    2011 std::vector<int> axes_;
    +
    2012};
    -
    2005
    -
    2006 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2007 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2008
    -
    2009 DEFINE_VMAP()
    -
    2010 DEFINE_GRADS()
    -
    2011 DEFINE_PRINT(Softmax)
    -
    2012 DEFINE_INPUT_OUTPUT_SHAPE()
    2013
    -
    2014 bool is_equivalent(const Primitive& other) const override;
    -
    -
    2015 auto state() const {
    -
    2016 return precise_;
    -
    2017 };
    +
    +
    2014class Softmax : public UnaryPrimitive {
    +
    2015 public:
    +
    +
    2016 explicit Softmax(Stream stream, bool precise)
    +
    2017 : UnaryPrimitive(stream), precise_(precise) {}
    2018
    -
    2019 private:
    -
    2020 bool precise_;
    -
    2021};
    +
    2019 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2020 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2021
    +
    2022 DEFINE_VMAP()
    +
    2023 DEFINE_GRADS()
    +
    2024 DEFINE_PRINT(Softmax)
    +
    2025 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    2026
    +
    2027 bool is_equivalent(const Primitive& other) const override;
    +
    +
    2028 auto state() const {
    +
    2029 return precise_;
    +
    2030 };
    -
    2022
    -
    -
    2023class Sort : public UnaryPrimitive {
    -
    2024 public:
    -
    -
    2025 explicit Sort(Stream stream, int axis)
    -
    2026 : UnaryPrimitive(stream), axis_(axis) {}
    +
    2031
    +
    2032 private:
    +
    2033 bool precise_;
    +
    2034};
    -
    2027
    -
    2028 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2029 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2030
    -
    2031 DEFINE_VMAP()
    -
    2032 DEFINE_GRADS()
    -
    2033 DEFINE_PRINT(Sort)
    -
    2034 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    2035 bool is_equivalent(const Primitive& other) const override;
    -
    -
    2036 auto state() const {
    -
    2037 return axis_;
    -
    2038 }
    -
    -
    2039
    -
    2040 private:
    -
    2041 int axis_;
    -
    2042};
    +
    2035
    +
    +
    2036class Sort : public UnaryPrimitive {
    +
    2037 public:
    +
    +
    2038 explicit Sort(Stream stream, int axis)
    +
    2039 : UnaryPrimitive(stream), axis_(axis) {}
    +
    2040
    +
    2041 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2042 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    2043
    -
    -
    2044class Split : public Primitive {
    -
    2045 public:
    -
    -
    2046 explicit Split(Stream stream, const Shape& indices, int axis)
    -
    2047 : Primitive(stream), indices_(indices), axis_(axis) {}
    +
    2044 DEFINE_VMAP()
    +
    2045 DEFINE_GRADS()
    +
    2046 DEFINE_PRINT(Sort)
    +
    2047 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    2048 bool is_equivalent(const Primitive& other) const override;
    +
    +
    2049 auto state() const {
    +
    2050 return axis_;
    +
    2051 }
    -
    2048
    -
    2049 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    2050 override;
    -
    2051 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    2052 override;
    -
    2053
    -
    2054 DEFINE_VMAP()
    -
    2055 DEFINE_GRADS()
    -
    2056 DEFINE_PRINT(Split)
    -
    2057 bool is_equivalent(const Primitive& other) const override;
    -
    -
    2058 std::pair<std::vector<int>, int> state() const {
    -
    2059 return {indices_, axis_};
    -
    2060 };
    +
    2052
    +
    2053 private:
    +
    2054 int axis_;
    +
    2055};
    +
    +
    2056
    +
    +
    2057class Split : public Primitive {
    +
    2058 public:
    +
    +
    2059 explicit Split(Stream stream, const Shape& indices, int axis)
    +
    2060 : Primitive(stream), indices_(indices), axis_(axis) {}
    2061
    -
    2062 private:
    -
    2063 void eval(const std::vector<array>& inputs, std::vector<array>& outputs);
    -
    2064
    -
    2065 Shape indices_;
    -
    2066 int axis_;
    -
    2067};
    +
    2062 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2063 override;
    +
    2064 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2065 override;
    +
    2066
    +
    2067 DEFINE_VMAP()
    +
    2068 DEFINE_GRADS()
    +
    2069 DEFINE_PRINT(Split)
    +
    2070 bool is_equivalent(const Primitive& other) const override;
    +
    +
    2071 std::pair<std::vector<int>, int> state() const {
    +
    2072 return {indices_, axis_};
    +
    2073 };
    -
    2068
    -
    -
    2069class Square : public UnaryPrimitive {
    -
    2070 public:
    -
    2071 explicit Square(Stream stream) : UnaryPrimitive(stream) {}
    -
    2072
    -
    2073 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2074 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2075
    -
    2076 DEFINE_VMAP()
    -
    2077 DEFINE_GRADS()
    -
    2078 DEFINE_PRINT(Square)
    -
    2079 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    2080 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    2081};
    +
    2074
    +
    2075 private:
    +
    2076 void eval(const std::vector<array>& inputs, std::vector<array>& outputs);
    +
    2077
    +
    2078 Shape indices_;
    +
    2079 int axis_;
    +
    2080};
    -
    2082
    -
    -
    2083class Sqrt : public UnaryPrimitive {
    -
    2084 public:
    -
    -
    2085 explicit Sqrt(Stream stream, bool recip = false)
    -
    2086 : UnaryPrimitive(stream), recip_(recip) {}
    +
    2081
    +
    +
    2082class Square : public UnaryPrimitive {
    +
    2083 public:
    +
    2084 explicit Square(Stream stream) : UnaryPrimitive(stream) {}
    +
    2085
    +
    2086 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2087 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2088
    +
    2089 DEFINE_VMAP()
    +
    2090 DEFINE_GRADS()
    +
    2091 DEFINE_PRINT(Square)
    +
    2092 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    2093 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    2094};
    -
    2087
    -
    2088 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2089 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2090
    -
    2091 DEFINE_VMAP()
    -
    2092 DEFINE_GRADS()
    -
    2093 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    2094 bool is_equivalent(const Primitive& other) const override;
    -
    -
    2095 auto state() const {
    -
    2096 return recip_;
    -
    2097 }
    +
    2095
    +
    +
    2096class Sqrt : public UnaryPrimitive {
    +
    2097 public:
    +
    +
    2098 explicit Sqrt(Stream stream, bool recip = false)
    +
    2099 : UnaryPrimitive(stream), recip_(recip) {}
    -
    2098
    -
    -
    2099 void print(std::ostream& os) override {
    -
    2100 if (recip_) {
    -
    2101 os << "Rsqrt";
    -
    2102 } else {
    -
    2103 os << "Sqrt";
    -
    2104 }
    -
    2105 }
    +
    2100
    +
    2101 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2102 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2103
    +
    2104 DEFINE_VMAP()
    +
    2105 DEFINE_GRADS()
    +
    2106 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    2107 bool is_equivalent(const Primitive& other) const override;
    +
    +
    2108 auto state() const {
    +
    2109 return recip_;
    +
    2110 }
    -
    2106
    -
    2107 private:
    -
    2108 bool recip_;
    -
    2109};
    +
    2111
    +
    +
    2112 void print(std::ostream& os) override {
    +
    2113 if (recip_) {
    +
    2114 os << "Rsqrt";
    +
    2115 } else {
    +
    2116 os << "Sqrt";
    +
    2117 }
    +
    2118 }
    -
    2110
    -
    -
    2111class StopGradient : public UnaryPrimitive {
    -
    2112 public:
    -
    2113 explicit StopGradient(Stream stream) : UnaryPrimitive(stream) {}
    -
    2114
    -
    2115 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2116 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2117
    -
    2118 DEFINE_VMAP()
    -
    2119 DEFINE_PRINT(StopGradient)
    -
    2120 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    2121 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    2122
    -
    2123 private:
    -
    2124 void eval(const std::vector<array>& inputs, array& out);
    -
    2125};
    +
    2119
    +
    2120 private:
    +
    2121 bool recip_;
    +
    2122};
    -
    2126
    -
    -
    2127class Subtract : public UnaryPrimitive {
    -
    2128 public:
    -
    2129 explicit Subtract(Stream stream) : UnaryPrimitive(stream) {}
    +
    2123
    +
    +
    2124class StopGradient : public UnaryPrimitive {
    +
    2125 public:
    +
    2126 explicit StopGradient(Stream stream) : UnaryPrimitive(stream) {}
    +
    2127
    +
    2128 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2129 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    2130
    -
    2131 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2132 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2133
    -
    2134 DEFINE_VMAP()
    -
    2135 DEFINE_GRADS()
    -
    2136 DEFINE_PRINT(Subtract)
    -
    2137 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    2138 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    2139};
    +
    2131 DEFINE_VMAP()
    +
    2132 DEFINE_PRINT(StopGradient)
    +
    2133 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    2134 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    2135
    +
    2136 private:
    +
    2137 void eval(const std::vector<array>& inputs, array& out);
    +
    2138};
    -
    2140
    -
    -
    2141class Squeeze : public UnaryPrimitive {
    -
    2142 public:
    -
    -
    2143 explicit Squeeze(Stream stream, std::vector<int> axes)
    -
    2144 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
    +
    2139
    +
    +
    2140class Subtract : public UnaryPrimitive {
    +
    2141 public:
    +
    2142 explicit Subtract(Stream stream) : UnaryPrimitive(stream) {}
    +
    2143
    +
    2144 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2145 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2146
    +
    2147 DEFINE_VMAP()
    +
    2148 DEFINE_GRADS()
    +
    2149 DEFINE_PRINT(Subtract)
    +
    2150 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    2151 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    2152};
    -
    2145
    -
    2146 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2147 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2148
    -
    2149 DEFINE_VMAP()
    -
    2150 DEFINE_GRADS()
    -
    2151 DEFINE_PRINT(Squeeze)
    -
    2152
    -
    2153 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    2154 bool is_equivalent(const Primitive& other) const override;
    -
    2155
    -
    2156 static Shape output_shape(const array& input, const std::vector<int>& axes);
    -
    -
    2157 auto state() const {
    -
    2158 return axes_;
    -
    2159 };
    -
    -
    2160
    -
    2161 private:
    -
    2162 void eval(const std::vector<array>& inputs, array& out);
    -
    2163 std::vector<int> axes_;
    -
    2164};
    +
    2153
    +
    +
    2154class Squeeze : public UnaryPrimitive {
    +
    2155 public:
    +
    +
    2156 explicit Squeeze(Stream stream, std::vector<int> axes)
    +
    2157 : UnaryPrimitive(stream), axes_(std::move(axes)) {}
    +
    2158
    +
    2159 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2160 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2161
    +
    2162 DEFINE_VMAP()
    +
    2163 DEFINE_GRADS()
    +
    2164 DEFINE_PRINT(Squeeze)
    2165
    -
    -
    2166class Tan : public UnaryPrimitive {
    -
    2167 public:
    -
    2168 explicit Tan(Stream stream) : UnaryPrimitive(stream) {}
    -
    2169
    -
    2170 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2171 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2172
    -
    2173 DEFINE_VMAP()
    -
    2174 DEFINE_GRADS()
    -
    2175 DEFINE_PRINT(Tan)
    -
    2176 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    2177 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    2178};
    +
    2166 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    2167 bool is_equivalent(const Primitive& other) const override;
    +
    2168
    +
    2169 static Shape output_shape(const array& input, const std::vector<int>& axes);
    +
    +
    2170 auto state() const {
    +
    2171 return axes_;
    +
    2172 };
    -
    2179
    -
    -
    2180class Tanh : public UnaryPrimitive {
    -
    2181 public:
    -
    2182 explicit Tanh(Stream stream) : UnaryPrimitive(stream) {}
    -
    2183
    -
    2184 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2185 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2186
    -
    2187 DEFINE_VMAP()
    -
    2188 DEFINE_GRADS()
    -
    2189 DEFINE_PRINT(Tanh)
    -
    2190 DEFINE_DEFAULT_IS_EQUIVALENT()
    -
    2191 DEFINE_INPUT_OUTPUT_SHAPE()
    -
    2192};
    +
    2173
    +
    2174 private:
    +
    2175 void eval(const std::vector<array>& inputs, array& out);
    +
    2176 std::vector<int> axes_;
    +
    2177};
    -
    2193
    -
    -
    2194class Unflatten : public UnaryPrimitive {
    -
    2195 public:
    -
    -
    2196 explicit Unflatten(Stream stream, int axis, Shape shape)
    -
    2197 : UnaryPrimitive(stream), axis_(axis), shape_(std::move(shape)) {}
    +
    2178
    +
    +
    2179class Tan : public UnaryPrimitive {
    +
    2180 public:
    +
    2181 explicit Tan(Stream stream) : UnaryPrimitive(stream) {}
    +
    2182
    +
    2183 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2184 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2185
    +
    2186 DEFINE_VMAP()
    +
    2187 DEFINE_GRADS()
    +
    2188 DEFINE_PRINT(Tan)
    +
    2189 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    2190 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    2191};
    -
    2198
    -
    2199 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2200 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2201
    -
    2202 DEFINE_VMAP()
    -
    2203 DEFINE_GRADS()
    -
    2204 DEFINE_PRINT(Unflatten)
    -
    2205 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    2206 bool is_equivalent(const Primitive& other) const override;
    -
    2207
    -
    2208 static Shape output_shape(const array& input, int axis, const Shape& shape);
    +
    2192
    +
    +
    2193class Tanh : public UnaryPrimitive {
    +
    2194 public:
    +
    2195 explicit Tanh(Stream stream) : UnaryPrimitive(stream) {}
    +
    2196
    +
    2197 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2198 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2199
    +
    2200 DEFINE_VMAP()
    +
    2201 DEFINE_GRADS()
    +
    2202 DEFINE_PRINT(Tanh)
    +
    2203 DEFINE_DEFAULT_IS_EQUIVALENT()
    +
    2204 DEFINE_INPUT_OUTPUT_SHAPE()
    +
    2205};
    +
    +
    2206
    +
    +
    2207class Unflatten : public UnaryPrimitive {
    +
    2208 public:
    -
    2209 auto state() const {
    -
    2210 return std::make_pair(axis_, shape_);
    -
    2211 }
    +
    2209 explicit Unflatten(Stream stream, int axis, Shape shape)
    +
    2210 : UnaryPrimitive(stream), axis_(axis), shape_(std::move(shape)) {}
    -
    2212
    -
    2213 private:
    -
    2214 int axis_;
    -
    2215 Shape shape_;
    -
    2216 void eval(const std::vector<array>& inputs, array& out);
    -
    2217};
    +
    2211
    +
    2212 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2213 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2214
    +
    2215 DEFINE_VMAP()
    +
    2216 DEFINE_GRADS()
    +
    2217 DEFINE_PRINT(Unflatten)
    +
    2218 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    2219 bool is_equivalent(const Primitive& other) const override;
    +
    2220
    +
    2221 static Shape output_shape(const array& input, int axis, const Shape& shape);
    +
    +
    2222 auto state() const {
    +
    2223 return std::make_pair(axis_, shape_);
    +
    2224 }
    -
    2218
    -
    -
    2219class View : public UnaryPrimitive {
    -
    2220 public:
    -
    -
    2221 explicit View(Stream stream, Dtype dtype)
    -
    2222 : UnaryPrimitive(stream), dtype_(dtype) {}
    +
    2225
    +
    2226 private:
    +
    2227 int axis_;
    +
    2228 Shape shape_;
    +
    2229 void eval(const std::vector<array>& inputs, array& out);
    +
    2230};
    -
    2223
    -
    2224 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2225 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2226
    -
    2227 DEFINE_VMAP()
    -
    2228 void print(std::ostream& os) override;
    -
    2229 bool is_equivalent(const Primitive& other) const override;
    -
    -
    2230 auto state() const {
    -
    2231 return dtype_;
    -
    2232 }
    +
    2231
    +
    +
    2232class View : public UnaryPrimitive {
    +
    2233 public:
    +
    +
    2234 explicit View(Stream stream, Dtype dtype)
    +
    2235 : UnaryPrimitive(stream), dtype_(dtype) {}
    -
    2233
    -
    2234 private:
    -
    2235 Dtype dtype_;
    -
    2236};
    +
    2236
    +
    2237 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2238 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2239
    +
    2240 DEFINE_VMAP()
    +
    2241 void print(std::ostream& os) override;
    +
    2242 bool is_equivalent(const Primitive& other) const override;
    +
    +
    2243 auto state() const {
    +
    2244 return dtype_;
    +
    2245 }
    -
    2237
    -
    -
    2238class Transpose : public UnaryPrimitive {
    -
    2239 public:
    -
    -
    2240 explicit Transpose(Stream stream, const std::vector<int>& axes)
    -
    2241 : UnaryPrimitive(stream), axes_(axes) {}
    +
    2246
    +
    2247 private:
    +
    2248 Dtype dtype_;
    +
    2249};
    -
    2242
    -
    2243 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2244 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2245
    -
    2246 DEFINE_VMAP()
    -
    2247 DEFINE_GRADS()
    -
    2248 DEFINE_PRINT(Transpose)
    -
    2249 bool is_equivalent(const Primitive& other) const override;
    -
    2250 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    -
    2251 std::vector<int> state() const {
    -
    2252 return axes_;
    -
    2253 };
    +
    2250
    +
    +
    2251class Transpose : public UnaryPrimitive {
    +
    2252 public:
    +
    +
    2253 explicit Transpose(Stream stream, const std::vector<int>& axes)
    +
    2254 : UnaryPrimitive(stream), axes_(axes) {}
    -
    2254
    -
    2255 private:
    -
    2256 std::vector<int> axes_;
    -
    2257
    -
    2258 void eval(const std::vector<array>& inputs, array& out);
    -
    2259};
    +
    2255
    +
    2256 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2257 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    +
    2258
    +
    2259 DEFINE_VMAP()
    +
    2260 DEFINE_GRADS()
    +
    2261 DEFINE_PRINT(Transpose)
    +
    2262 bool is_equivalent(const Primitive& other) const override;
    +
    2263 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    +
    2264 std::vector<int> state() const {
    +
    2265 return axes_;
    +
    2266 };
    -
    2260
    -
    2261/* QR Factorization primitive. */
    -
    -
    2262class QRF : public Primitive {
    -
    2263 public:
    -
    2264 explicit QRF(Stream stream) : Primitive(stream) {}
    -
    2265
    -
    2266 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    2267 override;
    -
    2268 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    2269 override;
    +
    2267
    +
    2268 private:
    +
    2269 std::vector<int> axes_;
    2270
    -
    2271 DEFINE_PRINT(QRF)
    +
    2271 void eval(const std::vector<array>& inputs, array& out);
    2272};
    2273
    -
    2274/* SVD primitive. */
    +
    2274/* QR Factorization primitive. */
    -
    2275class SVD : public Primitive {
    +
    2275class QRF : public Primitive {
    2276 public:
    -
    2277 explicit SVD(Stream stream) : Primitive(stream) {}
    +
    2277 explicit QRF(Stream stream) : Primitive(stream) {}
    2278
    -
    2279 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2279 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    2280 override;
    -
    2281 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2281 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    2282 override;
    2283
    -
    2284 DEFINE_VMAP()
    -
    2285 DEFINE_PRINT(SVD)
    -
    2286};
    +
    2284 DEFINE_PRINT(QRF)
    +
    2285};
    -
    2287
    -
    2288/* Matrix inversion primitive. */
    -
    -
    2289class Inverse : public UnaryPrimitive {
    -
    2290 public:
    -
    -
    2291 explicit Inverse(Stream stream, bool tri, bool upper)
    -
    2292 : UnaryPrimitive(stream), tri_(tri), upper_(upper) {}
    -
    -
    2293
    -
    2294 void eval_cpu(const std::vector<array>& inputs, array& output) override;
    -
    2295 void eval_gpu(const std::vector<array>& inputs, array& output) override;
    +
    2286
    +
    2287/* SVD primitive. */
    +
    +
    2288class SVD : public Primitive {
    +
    2289 public:
    +
    2290 explicit SVD(Stream stream) : Primitive(stream) {}
    +
    2291
    +
    2292 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2293 override;
    +
    2294 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2295 override;
    2296
    -
    2297 DEFINE_VMAP()
    -
    2298 DEFINE_PRINT(Inverse)
    -
    -
    2299 auto state() const {
    -
    2300 return std::make_pair(tri_, upper_);
    -
    2301 }
    +
    2297 DEFINE_VMAP()
    +
    2298 DEFINE_PRINT(SVD)
    +
    2299};
    -
    2302
    -
    2303 private:
    -
    2304 bool tri_;
    -
    2305 bool upper_;
    -
    2306};
    +
    2300
    +
    2301/* Matrix inversion primitive. */
    +
    +
    2302class Inverse : public UnaryPrimitive {
    +
    2303 public:
    +
    +
    2304 explicit Inverse(Stream stream, bool tri, bool upper)
    +
    2305 : UnaryPrimitive(stream), tri_(tri), upper_(upper) {}
    -
    2307
    -
    -
    2308class Cholesky : public UnaryPrimitive {
    -
    2309 public:
    -
    -
    2310 explicit Cholesky(Stream stream, bool upper)
    -
    2311 : UnaryPrimitive(stream), upper_(upper) {}
    +
    2306
    +
    2307 void eval_cpu(const std::vector<array>& inputs, array& output) override;
    +
    2308 void eval_gpu(const std::vector<array>& inputs, array& output) override;
    +
    2309
    +
    2310 DEFINE_VMAP()
    +
    2311 DEFINE_PRINT(Inverse)
    +
    +
    2312 auto state() const {
    +
    2313 return std::make_pair(tri_, upper_);
    +
    2314 }
    -
    2312
    -
    2313 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    -
    2314 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    -
    2315 auto state() const {
    -
    2316 return upper_;
    -
    2317 }
    +
    2315
    +
    2316 private:
    +
    2317 bool tri_;
    +
    2318 bool upper_;
    +
    2319};
    -
    2318
    -
    2319 DEFINE_VMAP()
    -
    2320 DEFINE_PRINT(Cholesky)
    -
    2321
    -
    2322 private:
    -
    2323 bool upper_;
    -
    2324};
    +
    2320
    +
    +
    2321class Cholesky : public UnaryPrimitive {
    +
    2322 public:
    +
    +
    2323 explicit Cholesky(Stream stream, bool upper)
    +
    2324 : UnaryPrimitive(stream), upper_(upper) {}
    2325
    -
    -
    2326class Eigh : public Primitive {
    -
    2327 public:
    +
    2326 void eval_cpu(const std::vector<array>& inputs, array& out) override;
    +
    2327 void eval_gpu(const std::vector<array>& inputs, array& out) override;
    -
    2328 explicit Eigh(Stream stream, std::string uplo, bool compute_eigenvectors)
    -
    2329 : Primitive(stream),
    -
    2330 uplo_(std::move(uplo)),
    -
    2331 compute_eigenvectors_(compute_eigenvectors) {}
    +
    2328 auto state() const {
    +
    2329 return upper_;
    +
    2330 }
    -
    2332
    -
    2333 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    2334 override;
    -
    2335 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    -
    2336 override;
    -
    2337
    -
    2338 DEFINE_VMAP()
    -
    2339 DEFINE_PRINT(Eigh)
    -
    2340
    -
    2341 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    -
    2342
    -
    2343 bool is_equivalent(const Primitive& other) const override;
    -
    -
    2344 auto state() const {
    -
    2345 return std::make_pair(uplo_, compute_eigenvectors_);
    -
    2346 }
    +
    2331
    +
    2332 DEFINE_VMAP()
    +
    2333 DEFINE_PRINT(Cholesky)
    +
    2334
    +
    2335 private:
    +
    2336 bool upper_;
    +
    2337};
    -
    2347
    -
    2348 private:
    -
    2349 std::string uplo_;
    -
    2350 bool compute_eigenvectors_;
    -
    2351};
    +
    2338
    +
    +
    2339class Eigh : public Primitive {
    +
    2340 public:
    +
    +
    2341 explicit Eigh(Stream stream, std::string uplo, bool compute_eigenvectors)
    +
    2342 : Primitive(stream),
    +
    2343 uplo_(std::move(uplo)),
    +
    2344 compute_eigenvectors_(compute_eigenvectors) {}
    +
    2345 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2346 override;
    +
    2347 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2348 override;
    +
    2349
    +
    2350 DEFINE_VMAP()
    +
    2351 DEFINE_PRINT(Eigh)
    2352
    -
    2353} // namespace mlx::core
    +
    2353 std::vector<Shape> output_shapes(const std::vector<array>& inputs) override;
    +
    2354
    +
    2355 bool is_equivalent(const Primitive& other) const override;
    +
    +
    2356 auto state() const {
    +
    2357 return std::make_pair(uplo_, compute_eigenvectors_);
    +
    2358 }
    +
    +
    2359
    +
    2360 private:
    +
    2361 std::string uplo_;
    +
    2362 bool compute_eigenvectors_;
    +
    2363};
    +
    +
    2364
    +
    2365/* LU Factorization primitive. */
    +
    +
    2366class LUF : public Primitive {
    +
    2367 public:
    +
    2368 explicit LUF(Stream stream) : Primitive(stream) {}
    +
    2369 void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2370 override;
    +
    2371 void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
    +
    2372 override;
    +
    2373
    +
    2374 DEFINE_PRINT(LUF)
    +
    2375};
    +
    +
    2376
    +
    2377} // namespace mlx::core
    mlx::core::Abs::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Abs::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    @@ -2964,32 +2992,35 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
    mlx::core::BitwiseBinary::state
    auto state() const
    Definition primitives.h:454
    mlx::core::BitwiseBinary::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::BitwiseBinary::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    +
    mlx::core::BitwiseInvert::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    +
    mlx::core::BitwiseInvert::BitwiseInvert
    BitwiseInvert(Stream stream)
    Definition primitives.h:464
    +
    mlx::core::BitwiseInvert::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::BlockMaskedMM::vjp
    std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
    The vector-Jacobian product.
    -
    mlx::core::BlockMaskedMM::state
    auto state() const
    Definition primitives.h:478
    +
    mlx::core::BlockMaskedMM::state
    auto state() const
    Definition primitives.h:491
    mlx::core::BlockMaskedMM::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::BlockMaskedMM::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::BlockMaskedMM::BlockMaskedMM
    BlockMaskedMM(Stream stream, int block_size)
    Definition primitives.h:464
    +
    mlx::core::BlockMaskedMM::BlockMaskedMM
    BlockMaskedMM(Stream stream, int block_size)
    Definition primitives.h:477
    mlx::core::BlockMaskedMM::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::BroadcastAxes::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::BroadcastAxes::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::BroadcastAxes::BroadcastAxes
    BroadcastAxes(Stream stream, std::vector< int > ignore_axes={})
    Definition primitives.h:505
    +
    mlx::core::BroadcastAxes::BroadcastAxes
    BroadcastAxes(Stream stream, std::vector< int > ignore_axes={})
    Definition primitives.h:518
    mlx::core::BroadcastAxes::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::BroadcastAxes::state
    auto state() const
    Definition primitives.h:519
    +
    mlx::core::BroadcastAxes::state
    auto state() const
    Definition primitives.h:532
    mlx::core::BroadcastAxes::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::BroadcastAxes::output_shape
    static Shape output_shape(const std::vector< array > &inputs, const std::vector< int > &ignore_axes)
    -
    mlx::core::Broadcast::Broadcast
    Broadcast(Stream stream, const Shape &shape)
    Definition primitives.h:530
    +
    mlx::core::Broadcast::Broadcast
    Broadcast(Stream stream, const Shape &shape)
    Definition primitives.h:543
    mlx::core::Broadcast::output_shape
    static Shape output_shape(const std::vector< array > &inputs)
    mlx::core::Broadcast::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::Broadcast::state
    std::vector< int > state() const
    Definition primitives.h:542
    +
    mlx::core::Broadcast::state
    std::vector< int > state() const
    Definition primitives.h:555
    mlx::core::Broadcast::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Broadcast::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Broadcast::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::Ceil::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Ceil::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Ceil::Ceil
    Ceil(Stream stream)
    Definition primitives.h:554
    +
    mlx::core::Ceil::Ceil
    Ceil(Stream stream)
    Definition primitives.h:567
    mlx::core::Cholesky::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Cholesky::state
    auto state() const
    Definition primitives.h:2315
    -
    mlx::core::Cholesky::Cholesky
    Cholesky(Stream stream, bool upper)
    Definition primitives.h:2310
    +
    mlx::core::Cholesky::state
    auto state() const
    Definition primitives.h:2328
    +
    mlx::core::Cholesky::Cholesky
    Cholesky(Stream stream, bool upper)
    Definition primitives.h:2323
    mlx::core::Cholesky::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Compiled::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::Compiled::print
    void print(std::ostream &os) override
    Print the primitive.
    @@ -2997,60 +3028,60 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
    mlx::core::Compiled::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Compiled::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    mlx::core::Compiled::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    -
    mlx::core::Compiled::lib_name
    std::string lib_name() const
    Definition primitives.h:595
    +
    mlx::core::Compiled::lib_name
    std::string lib_name() const
    Definition primitives.h:608
    mlx::core::Concatenate::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Concatenate::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Concatenate::state
    auto state() const
    Definition primitives.h:621
    +
    mlx::core::Concatenate::state
    auto state() const
    Definition primitives.h:634
    mlx::core::Concatenate::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::Concatenate::Concatenate
    Concatenate(Stream stream, int axis)
    Definition primitives.h:610
    +
    mlx::core::Concatenate::Concatenate
    Concatenate(Stream stream, int axis)
    Definition primitives.h:623
    mlx::core::Concatenate::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    -
    mlx::core::Conjugate::Conjugate
    Conjugate(Stream stream)
    Definition primitives.h:631
    +
    mlx::core::Conjugate::Conjugate
    Conjugate(Stream stream)
    Definition primitives.h:644
    mlx::core::Conjugate::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Conjugate::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Contiguous::Contiguous
    Contiguous(Stream stream, bool allow_col_major)
    Definition primitives.h:644
    +
    mlx::core::Contiguous::Contiguous
    Contiguous(Stream stream, bool allow_col_major)
    Definition primitives.h:657
    mlx::core::Contiguous::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Contiguous::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Contiguous::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Convolution::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Convolution::Convolution
    Convolution(Stream stream, const std::vector< int > &kernel_strides, const std::vector< int > &padding, const std::vector< int > &kernel_dilation, const std::vector< int > &input_dilation, const int groups=1, const bool flip=false)
    Definition primitives.h:663
    -
    mlx::core::Convolution::state
    auto state() const
    Definition primitives.h:690
    +
    mlx::core::Convolution::Convolution
    Convolution(Stream stream, const std::vector< int > &kernel_strides, const std::vector< int > &padding, const std::vector< int > &kernel_dilation, const std::vector< int > &input_dilation, const int groups=1, const bool flip=false)
    Definition primitives.h:676
    +
    mlx::core::Convolution::state
    auto state() const
    Definition primitives.h:703
    mlx::core::Convolution::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Convolution::vjp
    std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
    The vector-Jacobian product.
    mlx::core::Convolution::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Copy::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Copy::Copy
    Copy(Stream stream)
    Definition primitives.h:711
    +
    mlx::core::Copy::Copy
    Copy(Stream stream)
    Definition primitives.h:724
    mlx::core::Copy::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Cos::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Cos::Cos
    Cos(Stream stream)
    Definition primitives.h:728
    +
    mlx::core::Cos::Cos
    Cos(Stream stream)
    Definition primitives.h:741
    mlx::core::Cos::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Cosh::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Cosh::Cosh
    Cosh(Stream stream)
    Definition primitives.h:742
    +
    mlx::core::Cosh::Cosh
    Cosh(Stream stream)
    Definition primitives.h:755
    mlx::core::Cosh::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::CustomTransforms::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    mlx::core::CustomTransforms::vmap
    virtual std::pair< std::vector< array >, std::vector< int > > vmap(const std::vector< array > &inputs, const std::vector< int > &axes) override
    The primitive must know how to vectorize itself across the given axes.
    mlx::core::CustomTransforms::vjp
    std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
    The vector-Jacobian product.
    mlx::core::CustomTransforms::jvp
    std::vector< array > jvp(const std::vector< array > &primals, const std::vector< array > &tangents, const std::vector< int > &argnums) override
    The Jacobian-vector product.
    -
    mlx::core::CustomTransforms::CustomTransforms
    CustomTransforms(Stream stream, int num_outputs, std::function< std::vector< array >(const std::vector< array > &, const std::vector< array > &, const std::vector< array > &)> vjp, std::function< std::vector< array >(const std::vector< array > &, const std::vector< array > &, const std::vector< int > &)> jvp, std::function< std::pair< std::vector< array >, std::vector< int > >(const std::vector< array > &, const std::vector< int > &)> vmap)
    Definition primitives.h:756
    +
    mlx::core::CustomTransforms::CustomTransforms
    CustomTransforms(Stream stream, int num_outputs, std::function< std::vector< array >(const std::vector< array > &, const std::vector< array > &, const std::vector< array > &)> vjp, std::function< std::vector< array >(const std::vector< array > &, const std::vector< array > &, const std::vector< int > &)> jvp, std::function< std::pair< std::vector< array >, std::vector< int > >(const std::vector< array > &, const std::vector< int > &)> vmap)
    Definition primitives.h:769
    mlx::core::CustomTransforms::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    mlx::core::Depends::vjp
    std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotan, const std::vector< int > &argnums, const std::vector< array > &outputs) override
    The vector-Jacobian product.
    mlx::core::Depends::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    -
    mlx::core::Depends::Depends
    Depends(Stream stream)
    Definition primitives.h:808
    +
    mlx::core::Depends::Depends
    Depends(Stream stream)
    Definition primitives.h:821
    mlx::core::Depends::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    mlx::core::DivMod::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    -
    mlx::core::DivMod::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    Definition primitives.h:854
    -
    mlx::core::DivMod::DivMod
    DivMod(Stream stream)
    Definition primitives.h:843
    +
    mlx::core::DivMod::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    Definition primitives.h:867
    +
    mlx::core::DivMod::DivMod
    DivMod(Stream stream)
    Definition primitives.h:856
    mlx::core::DivMod::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    -
    mlx::core::Divide::Divide
    Divide(Stream stream)
    Definition primitives.h:829
    +
    mlx::core::Divide::Divide
    Divide(Stream stream)
    Definition primitives.h:842
    mlx::core::Divide::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Divide::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::DynamicSlice::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::DynamicSlice::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::DynamicSlice::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    -
    mlx::core::DynamicSlice::DynamicSlice
    DynamicSlice(Stream stream, std::vector< int > axes, Shape slice_size)
    Definition primitives.h:1958
    +
    mlx::core::DynamicSlice::DynamicSlice
    DynamicSlice(Stream stream, std::vector< int > axes, Shape slice_size)
    Definition primitives.h:1971
    mlx::core::DynamicSlice::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::DynamicSlice::state
    auto state() const
    Definition primitives.h:1971
    -
    mlx::core::DynamicSliceUpdate::state
    auto state() const
    Definition primitives.h:1993
    -
    mlx::core::DynamicSliceUpdate::DynamicSliceUpdate
    DynamicSliceUpdate(Stream stream, std::vector< int > axes)
    Definition primitives.h:1982
    +
    mlx::core::DynamicSlice::state
    auto state() const
    Definition primitives.h:1984
    +
    mlx::core::DynamicSliceUpdate::state
    auto state() const
    Definition primitives.h:2006
    +
    mlx::core::DynamicSliceUpdate::DynamicSliceUpdate
    DynamicSliceUpdate(Stream stream, std::vector< int > axes)
    Definition primitives.h:1995
    mlx::core::DynamicSliceUpdate::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::DynamicSliceUpdate::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::DynamicSliceUpdate::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    @@ -3058,159 +3089,162 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
    mlx::core::Eigh::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    mlx::core::Eigh::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    mlx::core::Eigh::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    -
    mlx::core::Eigh::state
    auto state() const
    Definition primitives.h:2344
    -
    mlx::core::Eigh::Eigh
    Eigh(Stream stream, std::string uplo, bool compute_eigenvectors)
    Definition primitives.h:2328
    -
    mlx::core::Equal::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:900
    -
    mlx::core::Equal::Equal
    Equal(Stream stream, bool equal_nan=false)
    Definition primitives.h:889
    -
    mlx::core::Equal::state
    auto state() const
    Definition primitives.h:907
    +
    mlx::core::Eigh::state
    auto state() const
    Definition primitives.h:2356
    +
    mlx::core::Eigh::Eigh
    Eigh(Stream stream, std::string uplo, bool compute_eigenvectors)
    Definition primitives.h:2341
    +
    mlx::core::Equal::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:913
    +
    mlx::core::Equal::Equal
    Equal(Stream stream, bool equal_nan=false)
    Definition primitives.h:902
    +
    mlx::core::Equal::state
    auto state() const
    Definition primitives.h:920
    mlx::core::Equal::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Equal::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Erf::Erf
    Erf(Stream stream)
    Definition primitives.h:917
    +
    mlx::core::Erf::Erf
    Erf(Stream stream)
    Definition primitives.h:930
    mlx::core::Erf::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Erf::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::ErfInv::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::ErfInv::ErfInv
    ErfInv(Stream stream)
    Definition primitives.h:931
    +
    mlx::core::ErfInv::ErfInv
    ErfInv(Stream stream)
    Definition primitives.h:944
    mlx::core::ErfInv::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Exp::Exp
    Exp(Stream stream)
    Definition primitives.h:945
    +
    mlx::core::Exp::Exp
    Exp(Stream stream)
    Definition primitives.h:958
    mlx::core::Exp::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Exp::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::ExpandDims::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::ExpandDims::output_shape
    static Shape output_shape(const array &input, const std::vector< int > &axes)
    -
    mlx::core::ExpandDims::state
    auto state() const
    Definition primitives.h:986
    +
    mlx::core::ExpandDims::state
    auto state() const
    Definition primitives.h:999
    mlx::core::ExpandDims::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::ExpandDims::ExpandDims
    ExpandDims(Stream stream, std::vector< int > axes)
    Definition primitives.h:972
    +
    mlx::core::ExpandDims::ExpandDims
    ExpandDims(Stream stream, std::vector< int > axes)
    Definition primitives.h:985
    mlx::core::ExpandDims::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::ExpandDims::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    -
    mlx::core::Expm1::Expm1
    Expm1(Stream stream)
    Definition primitives.h:959
    +
    mlx::core::Expm1::Expm1
    Expm1(Stream stream)
    Definition primitives.h:972
    mlx::core::Expm1::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Expm1::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::FFT::FFT
    FFT(Stream stream, const std::vector< size_t > &axes, bool inverse, bool real)
    Definition primitives.h:997
    +
    mlx::core::FFT::FFT
    FFT(Stream stream, const std::vector< size_t > &axes, bool inverse, bool real)
    Definition primitives.h:1010
    mlx::core::FFT::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::FFT::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::FFT::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::FFT::state
    auto state() const
    Definition primitives.h:1012
    +
    mlx::core::FFT::state
    auto state() const
    Definition primitives.h:1025
    mlx::core::Flatten::output_shape
    static Shape output_shape(const array &input, int start_axis, int end_axis)
    mlx::core::Flatten::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Flatten::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::Flatten::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Flatten::Flatten
    Flatten(Stream stream, int start_axis, int end_axis)
    Definition primitives.h:1024
    +
    mlx::core::Flatten::Flatten
    Flatten(Stream stream, int start_axis, int end_axis)
    Definition primitives.h:1037
    mlx::core::Flatten::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Flatten::state
    auto state() const
    Definition primitives.h:1037
    +
    mlx::core::Flatten::state
    auto state() const
    Definition primitives.h:1050
    mlx::core::Floor::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Floor::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Floor::Floor
    Floor(Stream stream)
    Definition primitives.h:1049
    +
    mlx::core::Floor::Floor
    Floor(Stream stream)
    Definition primitives.h:1062
    mlx::core::Full::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Full::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Full::Full
    Full(Stream stream)
    Definition primitives.h:1063
    +
    mlx::core::Full::Full
    Full(Stream stream)
    Definition primitives.h:1076
    mlx::core::GatherAxis::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::GatherAxis::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::GatherAxis::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::GatherAxis::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    -
    mlx::core::GatherAxis::GatherAxis
    GatherAxis(Stream stream, int axis)
    Definition primitives.h:1100
    -
    mlx::core::GatherAxis::state
    auto state() const
    Definition primitives.h:1111
    +
    mlx::core::GatherAxis::GatherAxis
    GatherAxis(Stream stream, int axis)
    Definition primitives.h:1113
    +
    mlx::core::GatherAxis::state
    auto state() const
    Definition primitives.h:1124
    mlx::core::Gather::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Gather::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::Gather::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Gather::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Gather::state
    std::pair< std::vector< int >, std::vector< int > > state() const
    Definition primitives.h:1089
    -
    mlx::core::Gather::Gather
    Gather(Stream stream, std::vector< int > axes, Shape slice_sizes)
    Definition primitives.h:1076
    +
    mlx::core::Gather::state
    std::pair< std::vector< int >, std::vector< int > > state() const
    Definition primitives.h:1102
    +
    mlx::core::Gather::Gather
    Gather(Stream stream, std::vector< int > axes, Shape slice_sizes)
    Definition primitives.h:1089
    mlx::core::GatherMM::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::GatherMM::vjp
    std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
    The vector-Jacobian product.
    mlx::core::GatherMM::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::GatherMM::GatherMM
    GatherMM(Stream stream)
    Definition primitives.h:488
    -
    mlx::core::GatherQMM::state
    auto state() const
    Definition primitives.h:1575
    -
    mlx::core::GatherQMM::GatherQMM
    GatherQMM(Stream stream, int group_size, int bits, bool transpose)
    Definition primitives.h:1562
    +
    mlx::core::GatherMM::GatherMM
    GatherMM(Stream stream)
    Definition primitives.h:501
    +
    mlx::core::GatherQMM::state
    auto state() const
    Definition primitives.h:1588
    +
    mlx::core::GatherQMM::GatherQMM
    GatherQMM(Stream stream, int group_size, int bits, bool transpose)
    Definition primitives.h:1575
    mlx::core::GatherQMM::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::GatherQMM::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::GatherQMM::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::GreaterEqual::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::GreaterEqual::GreaterEqual
    GreaterEqual(Stream stream)
    Definition primitives.h:1135
    +
    mlx::core::GreaterEqual::GreaterEqual
    GreaterEqual(Stream stream)
    Definition primitives.h:1148
    mlx::core::GreaterEqual::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Greater::Greater
    Greater(Stream stream)
    Definition primitives.h:1121
    +
    mlx::core::Greater::Greater
    Greater(Stream stream)
    Definition primitives.h:1134
    mlx::core::Greater::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Greater::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Hadamard::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Hadamard::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Hadamard::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Hadamard::Hadamard
    Hadamard(Stream stream, float scale)
    Definition primitives.h:1149
    -
    mlx::core::Hadamard::state
    auto state() const
    Definition primitives.h:1161
    +
    mlx::core::Hadamard::Hadamard
    Hadamard(Stream stream, float scale)
    Definition primitives.h:1162
    +
    mlx::core::Hadamard::state
    auto state() const
    Definition primitives.h:1174
    mlx::core::Imag::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Imag::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Imag::Imag
    Imag(Stream stream)
    Definition primitives.h:1171
    +
    mlx::core::Imag::Imag
    Imag(Stream stream)
    Definition primitives.h:1184
    mlx::core::Inverse::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &output) override
    -
    mlx::core::Inverse::Inverse
    Inverse(Stream stream, bool tri, bool upper)
    Definition primitives.h:2291
    -
    mlx::core::Inverse::state
    auto state() const
    Definition primitives.h:2299
    +
    mlx::core::Inverse::Inverse
    Inverse(Stream stream, bool tri, bool upper)
    Definition primitives.h:2304
    +
    mlx::core::Inverse::state
    auto state() const
    Definition primitives.h:2312
    mlx::core::Inverse::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &output) override
    -
    mlx::core::LessEqual::LessEqual
    LessEqual(Stream stream)
    Definition primitives.h:1199
    +
    mlx::core::LUF::LUF
    LUF(Stream stream)
    Definition primitives.h:2368
    +
    mlx::core::LUF::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    +
    mlx::core::LUF::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    +
    mlx::core::LessEqual::LessEqual
    LessEqual(Stream stream)
    Definition primitives.h:1212
    mlx::core::LessEqual::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::LessEqual::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Less::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Less::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Less::Less
    Less(Stream stream)
    Definition primitives.h:1185
    +
    mlx::core::Less::Less
    Less(Stream stream)
    Definition primitives.h:1198
    mlx::core::Load::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Load::Load
    Load(Stream stream, std::shared_ptr< io::Reader > reader, size_t offset, bool swap_endianness=false)
    Definition primitives.h:1213
    +
    mlx::core::Load::Load
    Load(Stream stream, std::shared_ptr< io::Reader > reader, size_t offset, bool swap_endianness=false)
    Definition primitives.h:1226
    mlx::core::Load::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Log1p::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Log1p::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Log1p::Log1p
    Log1p(Stream stream)
    Definition primitives.h:1281
    +
    mlx::core::Log1p::Log1p
    Log1p(Stream stream)
    Definition primitives.h:1294
    mlx::core::LogAddExp::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::LogAddExp::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::LogAddExp::LogAddExp
    LogAddExp(Stream stream)
    Definition primitives.h:1336
    -
    mlx::core::Log::Base
    Base
    Definition primitives.h:1244
    -
    mlx::core::Log::ten
    @ ten
    Definition primitives.h:1244
    -
    mlx::core::Log::two
    @ two
    Definition primitives.h:1244
    -
    mlx::core::Log::e
    @ e
    Definition primitives.h:1244
    -
    mlx::core::Log::Log
    Log(Stream stream, Base base)
    Definition primitives.h:1246
    -
    mlx::core::Log::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1261
    -
    mlx::core::Log::state
    Base state() const
    Definition primitives.h:1257
    +
    mlx::core::LogAddExp::LogAddExp
    LogAddExp(Stream stream)
    Definition primitives.h:1349
    +
    mlx::core::Log::Base
    Base
    Definition primitives.h:1257
    +
    mlx::core::Log::ten
    @ ten
    Definition primitives.h:1257
    +
    mlx::core::Log::two
    @ two
    Definition primitives.h:1257
    +
    mlx::core::Log::e
    @ e
    Definition primitives.h:1257
    +
    mlx::core::Log::Log
    Log(Stream stream, Base base)
    Definition primitives.h:1259
    +
    mlx::core::Log::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1274
    +
    mlx::core::Log::state
    Base state() const
    Definition primitives.h:1270
    mlx::core::Log::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Log::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::LogicalAnd::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::LogicalAnd::LogicalAnd
    LogicalAnd(Stream stream)
    Definition primitives.h:1308
    +
    mlx::core::LogicalAnd::LogicalAnd
    LogicalAnd(Stream stream)
    Definition primitives.h:1321
    mlx::core::LogicalAnd::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::LogicalNot::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::LogicalNot::LogicalNot
    LogicalNot(Stream stream)
    Definition primitives.h:1294
    +
    mlx::core::LogicalNot::LogicalNot
    LogicalNot(Stream stream)
    Definition primitives.h:1307
    mlx::core::LogicalNot::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::LogicalOr::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::LogicalOr::LogicalOr
    LogicalOr(Stream stream)
    Definition primitives.h:1322
    +
    mlx::core::LogicalOr::LogicalOr
    LogicalOr(Stream stream)
    Definition primitives.h:1335
    mlx::core::LogicalOr::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Matmul::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Matmul::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Matmul::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    -
    mlx::core::Matmul::Matmul
    Matmul(Stream stream)
    Definition primitives.h:1350
    -
    mlx::core::Maximum::Maximum
    Maximum(Stream stream)
    Definition primitives.h:1364
    +
    mlx::core::Matmul::Matmul
    Matmul(Stream stream)
    Definition primitives.h:1363
    +
    mlx::core::Maximum::Maximum
    Maximum(Stream stream)
    Definition primitives.h:1377
    mlx::core::Maximum::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Maximum::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Minimum::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Minimum::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Minimum::Minimum
    Minimum(Stream stream)
    Definition primitives.h:1378
    +
    mlx::core::Minimum::Minimum
    Minimum(Stream stream)
    Definition primitives.h:1391
    mlx::core::Multiply::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Multiply::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Multiply::Multiply
    Multiply(Stream stream)
    Definition primitives.h:1392
    +
    mlx::core::Multiply::Multiply
    Multiply(Stream stream)
    Definition primitives.h:1405
    mlx::core::Negative::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Negative::Negative
    Negative(Stream stream)
    Definition primitives.h:1406
    +
    mlx::core::Negative::Negative
    Negative(Stream stream)
    Definition primitives.h:1419
    mlx::core::Negative::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::NotEqual::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::NotEqual::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::NotEqual::NotEqual
    NotEqual(Stream stream)
    Definition primitives.h:1420
    +
    mlx::core::NotEqual::NotEqual
    NotEqual(Stream stream)
    Definition primitives.h:1433
    mlx::core::NumberOfElements::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::NumberOfElements::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    Definition primitives.h:1450
    -
    mlx::core::NumberOfElements::NumberOfElements
    NumberOfElements(Stream stream, std::vector< int > axes, bool inverted, Dtype dtype)
    Definition primitives.h:1434
    +
    mlx::core::NumberOfElements::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    Definition primitives.h:1463
    +
    mlx::core::NumberOfElements::NumberOfElements
    NumberOfElements(Stream stream, std::vector< int > axes, bool inverted, Dtype dtype)
    Definition primitives.h:1447
    mlx::core::NumberOfElements::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::NumberOfElements::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::NumberOfElements::state
    std::tuple< std::vector< int >, bool, Dtype > state() const
    Definition primitives.h:1453
    -
    mlx::core::Pad::state
    auto state() const
    Definition primitives.h:1484
    -
    mlx::core::Pad::Pad
    Pad(Stream stream, const std::vector< int > &axes, const Shape &low_pad_size, const Shape &high_pad_size)
    Definition primitives.h:1467
    +
    mlx::core::NumberOfElements::state
    std::tuple< std::vector< int >, bool, Dtype > state() const
    Definition primitives.h:1466
    +
    mlx::core::Pad::state
    auto state() const
    Definition primitives.h:1497
    +
    mlx::core::Pad::Pad
    Pad(Stream stream, const std::vector< int > &axes, const Shape &low_pad_size, const Shape &high_pad_size)
    Definition primitives.h:1480
    mlx::core::Pad::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Pad::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Pad::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Partition::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Partition::Partition
    Partition(Stream stream, int kth, int axis)
    Definition primitives.h:1496
    +
    mlx::core::Partition::Partition
    Partition(Stream stream, int kth, int axis)
    Definition primitives.h:1509
    mlx::core::Partition::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Partition::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::Partition::state
    auto state() const
    Definition primitives.h:1507
    +
    mlx::core::Partition::state
    auto state() const
    Definition primitives.h:1520
    mlx::core::Power::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Power::Power
    Power(Stream stream)
    Definition primitives.h:1518
    +
    mlx::core::Power::Power
    Power(Stream stream)
    Definition primitives.h:1531
    mlx::core::Power::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Primitive
    Definition primitives.h:48
    mlx::core::Primitive::eval_cpu
    virtual void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs)=0
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    @@ -3229,138 +3263,138 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
    mlx::core::Primitive::eval_gpu
    virtual void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs)=0
    mlx::core::Primitive::print
    virtual void print(std::ostream &os)=0
    Print the primitive.
    mlx::core::Primitive::Primitive
    Primitive(Stream stream)
    Definition primitives.h:50
    -
    mlx::core::QRF::QRF
    QRF(Stream stream)
    Definition primitives.h:2264
    +
    mlx::core::QRF::QRF
    QRF(Stream stream)
    Definition primitives.h:2277
    mlx::core::QRF::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    mlx::core::QRF::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    mlx::core::QuantizedMatmul::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::QuantizedMatmul::QuantizedMatmul
    QuantizedMatmul(Stream stream, int group_size, int bits, bool transpose)
    Definition primitives.h:1532
    +
    mlx::core::QuantizedMatmul::QuantizedMatmul
    QuantizedMatmul(Stream stream, int group_size, int bits, bool transpose)
    Definition primitives.h:1545
    mlx::core::QuantizedMatmul::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::QuantizedMatmul::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::QuantizedMatmul::state
    auto state() const
    Definition primitives.h:1550
    +
    mlx::core::QuantizedMatmul::state
    auto state() const
    Definition primitives.h:1563
    mlx::core::QuantizedMatmul::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::RandomBits::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::RandomBits::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::RandomBits::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::RandomBits::state
    std::pair< std::vector< int >, int > state() const
    Definition primitives.h:1596
    -
    mlx::core::RandomBits::RandomBits
    RandomBits(Stream stream, const Shape &shape, int width)
    Definition primitives.h:1587
    +
    mlx::core::RandomBits::state
    std::pair< std::vector< int >, int > state() const
    Definition primitives.h:1609
    +
    mlx::core::RandomBits::RandomBits
    RandomBits(Stream stream, const Shape &shape, int width)
    Definition primitives.h:1600
    mlx::core::Real::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Real::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Real::Real
    Real(Stream stream)
    Definition primitives.h:1607
    -
    mlx::core::Reduce::Reduce
    Reduce(Stream stream, ReduceType reduce_type, const std::vector< int > &axes)
    Definition primitives.h:1645
    -
    mlx::core::Reduce::ReduceType
    ReduceType
    Definition primitives.h:1643
    -
    mlx::core::Reduce::Min
    @ Min
    Definition primitives.h:1643
    -
    mlx::core::Reduce::Or
    @ Or
    Definition primitives.h:1643
    -
    mlx::core::Reduce::Max
    @ Max
    Definition primitives.h:1643
    -
    mlx::core::Reduce::And
    @ And
    Definition primitives.h:1643
    -
    mlx::core::Reduce::Sum
    @ Sum
    Definition primitives.h:1643
    -
    mlx::core::Reduce::Prod
    @ Prod
    Definition primitives.h:1643
    -
    mlx::core::Reduce::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1664
    +
    mlx::core::Real::Real
    Real(Stream stream)
    Definition primitives.h:1620
    +
    mlx::core::Reduce::Reduce
    Reduce(Stream stream, ReduceType reduce_type, const std::vector< int > &axes)
    Definition primitives.h:1658
    +
    mlx::core::Reduce::ReduceType
    ReduceType
    Definition primitives.h:1656
    +
    mlx::core::Reduce::Min
    @ Min
    Definition primitives.h:1656
    +
    mlx::core::Reduce::Or
    @ Or
    Definition primitives.h:1656
    +
    mlx::core::Reduce::Max
    @ Max
    Definition primitives.h:1656
    +
    mlx::core::Reduce::And
    @ And
    Definition primitives.h:1656
    +
    mlx::core::Reduce::Sum
    @ Sum
    Definition primitives.h:1656
    +
    mlx::core::Reduce::Prod
    @ Prod
    Definition primitives.h:1656
    +
    mlx::core::Reduce::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1677
    mlx::core::Reduce::vjp
    std::vector< array > vjp(const std::vector< array > &primals, const std::vector< array > &cotangents, const std::vector< int > &argnums, const std::vector< array > &outputs) override
    The vector-Jacobian product.
    mlx::core::Reduce::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::Reduce::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Reduce::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Reduce::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Reduce::state
    std::pair< ReduceType, std::vector< int > > state() const
    Definition primitives.h:1687
    -
    mlx::core::Remainder::Remainder
    Remainder(Stream stream)
    Definition primitives.h:875
    +
    mlx::core::Reduce::state
    std::pair< ReduceType, std::vector< int > > state() const
    Definition primitives.h:1700
    +
    mlx::core::Remainder::Remainder
    Remainder(Stream stream)
    Definition primitives.h:888
    mlx::core::Remainder::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Remainder::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Reshape::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Reshape::output_shape
    static Shape output_shape(const array &input, Shape shape)
    mlx::core::Reshape::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Reshape::Reshape
    Reshape(Stream stream, const Shape &shape)
    Definition primitives.h:1621
    -
    mlx::core::Reshape::state
    std::vector< int > state() const
    Definition primitives.h:1631
    +
    mlx::core::Reshape::Reshape
    Reshape(Stream stream, const Shape &shape)
    Definition primitives.h:1634
    +
    mlx::core::Reshape::state
    std::vector< int > state() const
    Definition primitives.h:1644
    mlx::core::Reshape::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Reshape::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    -
    mlx::core::Round::Round
    Round(Stream stream)
    Definition primitives.h:1698
    +
    mlx::core::Round::Round
    Round(Stream stream)
    Definition primitives.h:1711
    mlx::core::Round::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Round::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::SVD::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    mlx::core::SVD::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    -
    mlx::core::SVD::SVD
    SVD(Stream stream)
    Definition primitives.h:2277
    +
    mlx::core::SVD::SVD
    SVD(Stream stream)
    Definition primitives.h:2290
    mlx::core::Scan::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Scan::ReduceType
    ReduceType
    Definition primitives.h:1712
    -
    mlx::core::Scan::Prod
    @ Prod
    Definition primitives.h:1712
    -
    mlx::core::Scan::Min
    @ Min
    Definition primitives.h:1712
    -
    mlx::core::Scan::Max
    @ Max
    Definition primitives.h:1712
    -
    mlx::core::Scan::Sum
    @ Sum
    Definition primitives.h:1712
    +
    mlx::core::Scan::ReduceType
    ReduceType
    Definition primitives.h:1725
    +
    mlx::core::Scan::Prod
    @ Prod
    Definition primitives.h:1725
    +
    mlx::core::Scan::Min
    @ Min
    Definition primitives.h:1725
    +
    mlx::core::Scan::Max
    @ Max
    Definition primitives.h:1725
    +
    mlx::core::Scan::Sum
    @ Sum
    Definition primitives.h:1725
    mlx::core::Scan::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::Scan::state
    auto state() const
    Definition primitives.h:1750
    -
    mlx::core::Scan::Scan
    Scan(Stream stream, ReduceType reduce_type, int axis, bool reverse, bool inclusive)
    Definition primitives.h:1714
    -
    mlx::core::Scan::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1732
    +
    mlx::core::Scan::state
    auto state() const
    Definition primitives.h:1763
    +
    mlx::core::Scan::Scan
    Scan(Stream stream, ReduceType reduce_type, int axis, bool reverse, bool inclusive)
    Definition primitives.h:1727
    +
    mlx::core::Scan::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1745
    mlx::core::Scan::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::ScatterAxis::state
    std::pair< ReduceType, int > state() const
    Definition primitives.h:1832
    -
    mlx::core::ScatterAxis::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1819
    +
    mlx::core::ScatterAxis::state
    std::pair< ReduceType, int > state() const
    Definition primitives.h:1845
    +
    mlx::core::ScatterAxis::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1832
    mlx::core::ScatterAxis::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::ScatterAxis::ScatterAxis
    ScatterAxis(Stream stream, ReduceType reduce_type, int axis)
    Definition primitives.h:1810
    -
    mlx::core::ScatterAxis::ReduceType
    ReduceType
    Definition primitives.h:1808
    -
    mlx::core::ScatterAxis::Sum
    @ Sum
    Definition primitives.h:1808
    -
    mlx::core::ScatterAxis::None
    @ None
    Definition primitives.h:1808
    +
    mlx::core::ScatterAxis::ScatterAxis
    ScatterAxis(Stream stream, ReduceType reduce_type, int axis)
    Definition primitives.h:1823
    +
    mlx::core::ScatterAxis::ReduceType
    ReduceType
    Definition primitives.h:1821
    +
    mlx::core::ScatterAxis::Sum
    @ Sum
    Definition primitives.h:1821
    +
    mlx::core::ScatterAxis::None
    @ None
    Definition primitives.h:1821
    mlx::core::ScatterAxis::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::ScatterAxis::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::ScatterAxis::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    mlx::core::Scatter::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::Scatter::state
    std::pair< ReduceType, std::vector< int > > state() const
    Definition primitives.h:1797
    -
    mlx::core::Scatter::ReduceType
    ReduceType
    Definition primitives.h:1763
    -
    mlx::core::Scatter::Sum
    @ Sum
    Definition primitives.h:1763
    -
    mlx::core::Scatter::Max
    @ Max
    Definition primitives.h:1763
    -
    mlx::core::Scatter::Prod
    @ Prod
    Definition primitives.h:1763
    -
    mlx::core::Scatter::None
    @ None
    Definition primitives.h:1763
    -
    mlx::core::Scatter::Min
    @ Min
    Definition primitives.h:1763
    +
    mlx::core::Scatter::state
    std::pair< ReduceType, std::vector< int > > state() const
    Definition primitives.h:1810
    +
    mlx::core::Scatter::ReduceType
    ReduceType
    Definition primitives.h:1776
    +
    mlx::core::Scatter::Sum
    @ Sum
    Definition primitives.h:1776
    +
    mlx::core::Scatter::Max
    @ Max
    Definition primitives.h:1776
    +
    mlx::core::Scatter::Prod
    @ Prod
    Definition primitives.h:1776
    +
    mlx::core::Scatter::None
    @ None
    Definition primitives.h:1776
    +
    mlx::core::Scatter::Min
    @ Min
    Definition primitives.h:1776
    mlx::core::Scatter::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Scatter::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1777
    +
    mlx::core::Scatter::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:1790
    mlx::core::Scatter::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Scatter::Scatter
    Scatter(Stream stream, ReduceType reduce_type, const std::vector< int > &axes)
    Definition primitives.h:1765
    +
    mlx::core::Scatter::Scatter
    Scatter(Stream stream, ReduceType reduce_type, const std::vector< int > &axes)
    Definition primitives.h:1778
    mlx::core::Select::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Select::Select
    Select(Stream stream)
    Definition primitives.h:861
    +
    mlx::core::Select::Select
    Select(Stream stream)
    Definition primitives.h:874
    mlx::core::Select::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Sigmoid::Sigmoid
    Sigmoid(Stream stream)
    Definition primitives.h:1843
    +
    mlx::core::Sigmoid::Sigmoid
    Sigmoid(Stream stream)
    Definition primitives.h:1856
    mlx::core::Sigmoid::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Sigmoid::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Sign::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Sign::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Sign::Sign
    Sign(Stream stream)
    Definition primitives.h:1857
    -
    mlx::core::Sin::Sin
    Sin(Stream stream)
    Definition primitives.h:1871
    +
    mlx::core::Sign::Sign
    Sign(Stream stream)
    Definition primitives.h:1870
    +
    mlx::core::Sin::Sin
    Sin(Stream stream)
    Definition primitives.h:1884
    mlx::core::Sin::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Sin::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Sinh::Sinh
    Sinh(Stream stream)
    Definition primitives.h:1885
    +
    mlx::core::Sinh::Sinh
    Sinh(Stream stream)
    Definition primitives.h:1898
    mlx::core::Sinh::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Sinh::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Slice::state
    auto state() const
    Definition primitives.h:1916
    -
    mlx::core::Slice::Slice
    Slice(Stream stream, const Shape &start_indices, const Shape &end_indices, const Shape &strides)
    Definition primitives.h:1899
    +
    mlx::core::Slice::state
    auto state() const
    Definition primitives.h:1929
    +
    mlx::core::Slice::Slice
    Slice(Stream stream, const Shape &start_indices, const Shape &end_indices, const Shape &strides)
    Definition primitives.h:1912
    mlx::core::Slice::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Slice::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Slice::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::SliceUpdate::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::SliceUpdate::SliceUpdate
    SliceUpdate(Stream stream, const Shape &start_indices, const Shape &end_indices, const Shape &strides)
    Definition primitives.h:1928
    +
    mlx::core::SliceUpdate::SliceUpdate
    SliceUpdate(Stream stream, const Shape &start_indices, const Shape &end_indices, const Shape &strides)
    Definition primitives.h:1941
    mlx::core::SliceUpdate::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::SliceUpdate::state
    auto state() const
    Definition primitives.h:1946
    +
    mlx::core::SliceUpdate::state
    auto state() const
    Definition primitives.h:1959
    mlx::core::SliceUpdate::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Softmax::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Softmax::Softmax
    Softmax(Stream stream, bool precise)
    Definition primitives.h:2003
    +
    mlx::core::Softmax::Softmax
    Softmax(Stream stream, bool precise)
    Definition primitives.h:2016
    mlx::core::Softmax::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Softmax::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Softmax::state
    auto state() const
    Definition primitives.h:2015
    +
    mlx::core::Softmax::state
    auto state() const
    Definition primitives.h:2028
    mlx::core::Sort::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Sort::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Sort::state
    auto state() const
    Definition primitives.h:2036
    -
    mlx::core::Sort::Sort
    Sort(Stream stream, int axis)
    Definition primitives.h:2025
    +
    mlx::core::Sort::state
    auto state() const
    Definition primitives.h:2049
    +
    mlx::core::Sort::Sort
    Sort(Stream stream, int axis)
    Definition primitives.h:2038
    mlx::core::Sort::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Split::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    -
    mlx::core::Split::state
    std::pair< std::vector< int >, int > state() const
    Definition primitives.h:2058
    -
    mlx::core::Split::Split
    Split(Stream stream, const Shape &indices, int axis)
    Definition primitives.h:2046
    +
    mlx::core::Split::state
    std::pair< std::vector< int >, int > state() const
    Definition primitives.h:2071
    +
    mlx::core::Split::Split
    Split(Stream stream, const Shape &indices, int axis)
    Definition primitives.h:2059
    mlx::core::Split::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Split::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, std::vector< array > &outputs) override
    A primitive must know how to evaluate itself on the CPU/GPU for the given inputs and populate the out...
    -
    mlx::core::Sqrt::state
    auto state() const
    Definition primitives.h:2095
    +
    mlx::core::Sqrt::state
    auto state() const
    Definition primitives.h:2108
    mlx::core::Sqrt::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Sqrt::Sqrt
    Sqrt(Stream stream, bool recip=false)
    Definition primitives.h:2085
    +
    mlx::core::Sqrt::Sqrt
    Sqrt(Stream stream, bool recip=false)
    Definition primitives.h:2098
    mlx::core::Sqrt::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Sqrt::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:2099
    +
    mlx::core::Sqrt::print
    void print(std::ostream &os) override
    Print the primitive.
    Definition primitives.h:2112
    mlx::core::Sqrt::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Square::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Square::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Square::Square
    Square(Stream stream)
    Definition primitives.h:2071
    -
    mlx::core::Squeeze::Squeeze
    Squeeze(Stream stream, std::vector< int > axes)
    Definition primitives.h:2143
    -
    mlx::core::Squeeze::state
    auto state() const
    Definition primitives.h:2157
    +
    mlx::core::Square::Square
    Square(Stream stream)
    Definition primitives.h:2084
    +
    mlx::core::Squeeze::Squeeze
    Squeeze(Stream stream, std::vector< int > axes)
    Definition primitives.h:2156
    +
    mlx::core::Squeeze::state
    auto state() const
    Definition primitives.h:2170
    mlx::core::Squeeze::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Squeeze::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Squeeze::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    @@ -3368,19 +3402,19 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
    mlx::core::Squeeze::output_shape
    static Shape output_shape(const array &input, const std::vector< int > &axes)
    mlx::core::StopGradient::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::StopGradient::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::StopGradient::StopGradient
    StopGradient(Stream stream)
    Definition primitives.h:2113
    +
    mlx::core::StopGradient::StopGradient
    StopGradient(Stream stream)
    Definition primitives.h:2126
    mlx::core::Subtract::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Subtract::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Subtract::Subtract
    Subtract(Stream stream)
    Definition primitives.h:2129
    -
    mlx::core::Tan::Tan
    Tan(Stream stream)
    Definition primitives.h:2168
    +
    mlx::core::Subtract::Subtract
    Subtract(Stream stream)
    Definition primitives.h:2142
    +
    mlx::core::Tan::Tan
    Tan(Stream stream)
    Definition primitives.h:2181
    mlx::core::Tan::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Tan::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Tanh::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Tanh::Tanh
    Tanh(Stream stream)
    Definition primitives.h:2182
    +
    mlx::core::Tanh::Tanh
    Tanh(Stream stream)
    Definition primitives.h:2195
    mlx::core::Tanh::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Transpose::Transpose
    Transpose(Stream stream, const std::vector< int > &axes)
    Definition primitives.h:2240
    +
    mlx::core::Transpose::Transpose
    Transpose(Stream stream, const std::vector< int > &axes)
    Definition primitives.h:2253
    mlx::core::Transpose::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Transpose::state
    std::vector< int > state() const
    Definition primitives.h:2251
    +
    mlx::core::Transpose::state
    std::vector< int > state() const
    Definition primitives.h:2264
    mlx::core::Transpose::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Transpose::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Transpose::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    @@ -3396,17 +3430,17 @@ $(function(){initNavTree('primitives_8h_source.html',''); initResizable(true); }
    mlx::core::UnaryPrimitive::operator=
    UnaryPrimitive & operator=(UnaryPrimitive &&other)=delete
    mlx::core::UnaryPrimitive::~UnaryPrimitive
    virtual ~UnaryPrimitive()=default
    mlx::core::Unflatten::output_shapes
    std::vector< Shape > output_shapes(const std::vector< array > &inputs) override
    Get the output shapes of the primitive.
    -
    mlx::core::Unflatten::Unflatten
    Unflatten(Stream stream, int axis, Shape shape)
    Definition primitives.h:2196
    +
    mlx::core::Unflatten::Unflatten
    Unflatten(Stream stream, int axis, Shape shape)
    Definition primitives.h:2209
    mlx::core::Unflatten::output_shape
    static Shape output_shape(const array &input, int axis, const Shape &shape)
    mlx::core::Unflatten::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    mlx::core::Unflatten::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    mlx::core::Unflatten::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::Unflatten::state
    auto state() const
    Definition primitives.h:2209
    +
    mlx::core::Unflatten::state
    auto state() const
    Definition primitives.h:2222
    mlx::core::View::eval_cpu
    void eval_cpu(const std::vector< array > &inputs, array &out) override
    -
    mlx::core::View::state
    auto state() const
    Definition primitives.h:2230
    +
    mlx::core::View::state
    auto state() const
    Definition primitives.h:2243
    mlx::core::View::print
    void print(std::ostream &os) override
    Print the primitive.
    mlx::core::View::is_equivalent
    bool is_equivalent(const Primitive &other) const override
    Equivalence check defaults to false unless overridden by the primitive.
    -
    mlx::core::View::View
    View(Stream stream, Dtype dtype)
    Definition primitives.h:2221
    +
    mlx::core::View::View
    View(Stream stream, Dtype dtype)
    Definition primitives.h:2234
    mlx::core::View::eval_gpu
    void eval_gpu(const std::vector< array > &inputs, array &out) override
    mlx::core::array
    Definition array.h:24
    diff --git a/docs/build/html/python/_autosummary/mlx.core.Device.html b/docs/build/html/python/_autosummary/mlx.core.Device.html index 9deb72a17..e10bea9db 100644 --- a/docs/build/html/python/_autosummary/mlx.core.Device.html +++ b/docs/build/html/python/_autosummary/mlx.core.Device.html @@ -8,7 +8,7 @@ - mlx.core.Device — MLX 0.22.1 documentation + mlx.core.Device — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.Dtype.html b/docs/build/html/python/_autosummary/mlx.core.Dtype.html index a1a56ef2b..a79ba312b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.Dtype.html +++ b/docs/build/html/python/_autosummary/mlx.core.Dtype.html @@ -8,7 +8,7 @@ - mlx.core.Dtype — MLX 0.22.1 documentation + mlx.core.Dtype — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html b/docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html index 5662b7582..ec646d14c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html +++ b/docs/build/html/python/_autosummary/mlx.core.DtypeCategory.html @@ -8,7 +8,7 @@ - mlx.core.DtypeCategory — MLX 0.22.1 documentation + mlx.core.DtypeCategory — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal

  • complexfloating

    diff --git a/docs/build/html/python/_autosummary/mlx.core.abs.html b/docs/build/html/python/_autosummary/mlx.core.abs.html index e2641c424..c4b940bc6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.abs.html +++ b/docs/build/html/python/_autosummary/mlx.core.abs.html @@ -8,7 +8,7 @@ - mlx.core.abs — MLX 0.22.1 documentation + mlx.core.abs — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.add.html b/docs/build/html/python/_autosummary/mlx.core.add.html index fcb997785..452c5df70 100644 --- a/docs/build/html/python/_autosummary/mlx.core.add.html +++ b/docs/build/html/python/_autosummary/mlx.core.add.html @@ -8,7 +8,7 @@ - mlx.core.add — MLX 0.22.1 documentation + mlx.core.add — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.addmm.html b/docs/build/html/python/_autosummary/mlx.core.addmm.html index 0ad5cdeca..6ee2a5710 100644 --- a/docs/build/html/python/_autosummary/mlx.core.addmm.html +++ b/docs/build/html/python/_autosummary/mlx.core.addmm.html @@ -8,7 +8,7 @@ - mlx.core.addmm — MLX 0.22.1 documentation + mlx.core.addmm — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.all.html b/docs/build/html/python/_autosummary/mlx.core.all.html index a70fd9349..ecaf83198 100644 --- a/docs/build/html/python/_autosummary/mlx.core.all.html +++ b/docs/build/html/python/_autosummary/mlx.core.all.html @@ -8,7 +8,7 @@ - mlx.core.all — MLX 0.22.1 documentation + mlx.core.all — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.allclose.html b/docs/build/html/python/_autosummary/mlx.core.allclose.html index 133584dc5..cc274edd9 100644 --- a/docs/build/html/python/_autosummary/mlx.core.allclose.html +++ b/docs/build/html/python/_autosummary/mlx.core.allclose.html @@ -8,7 +8,7 @@ - mlx.core.allclose — MLX 0.22.1 documentation + mlx.core.allclose — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.any.html b/docs/build/html/python/_autosummary/mlx.core.any.html index 4e943dcde..a239ef950 100644 --- a/docs/build/html/python/_autosummary/mlx.core.any.html +++ b/docs/build/html/python/_autosummary/mlx.core.any.html @@ -8,7 +8,7 @@ - mlx.core.any — MLX 0.22.1 documentation + mlx.core.any — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.arange.html b/docs/build/html/python/_autosummary/mlx.core.arange.html index a094ac61e..b02c7111e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arange.html +++ b/docs/build/html/python/_autosummary/mlx.core.arange.html @@ -8,7 +8,7 @@ - mlx.core.arange — MLX 0.22.1 documentation + mlx.core.arange — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.arccos.html b/docs/build/html/python/_autosummary/mlx.core.arccos.html index 414348d61..48c1d3c67 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arccos.html +++ b/docs/build/html/python/_autosummary/mlx.core.arccos.html @@ -8,7 +8,7 @@ - mlx.core.arccos — MLX 0.22.1 documentation + mlx.core.arccos — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.arccosh.html b/docs/build/html/python/_autosummary/mlx.core.arccosh.html index 24cce2804..1b8f2ed61 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arccosh.html +++ b/docs/build/html/python/_autosummary/mlx.core.arccosh.html @@ -8,7 +8,7 @@ - mlx.core.arccosh — MLX 0.22.1 documentation + mlx.core.arccosh — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.arcsin.html b/docs/build/html/python/_autosummary/mlx.core.arcsin.html index 8ba841ff2..ff1404488 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arcsin.html +++ b/docs/build/html/python/_autosummary/mlx.core.arcsin.html @@ -8,7 +8,7 @@ - mlx.core.arcsin — MLX 0.22.1 documentation + mlx.core.arcsin — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.arcsinh.html b/docs/build/html/python/_autosummary/mlx.core.arcsinh.html index fdaeb243e..48d1e7ff7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arcsinh.html +++ b/docs/build/html/python/_autosummary/mlx.core.arcsinh.html @@ -8,7 +8,7 @@ - mlx.core.arcsinh — MLX 0.22.1 documentation + mlx.core.arcsinh — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.arctan.html b/docs/build/html/python/_autosummary/mlx.core.arctan.html index a2eebd025..483ae745f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arctan.html +++ b/docs/build/html/python/_autosummary/mlx.core.arctan.html @@ -8,7 +8,7 @@ - mlx.core.arctan — MLX 0.22.1 documentation + mlx.core.arctan — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.arctan2.html b/docs/build/html/python/_autosummary/mlx.core.arctan2.html index 9e478f74e..b1a4d9004 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arctan2.html +++ b/docs/build/html/python/_autosummary/mlx.core.arctan2.html @@ -8,7 +8,7 @@ - mlx.core.arctan2 — MLX 0.22.1 documentation + mlx.core.arctan2 — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.arctanh.html b/docs/build/html/python/_autosummary/mlx.core.arctanh.html index b10d1d032..b9d057051 100644 --- a/docs/build/html/python/_autosummary/mlx.core.arctanh.html +++ b/docs/build/html/python/_autosummary/mlx.core.arctanh.html @@ -8,7 +8,7 @@ - mlx.core.arctanh — MLX 0.22.1 documentation + mlx.core.arctanh — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.argmax.html b/docs/build/html/python/_autosummary/mlx.core.argmax.html index ecec4742d..01296d8e5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.argmax.html +++ b/docs/build/html/python/_autosummary/mlx.core.argmax.html @@ -8,7 +8,7 @@ - mlx.core.argmax — MLX 0.22.1 documentation + mlx.core.argmax — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.argmin.html b/docs/build/html/python/_autosummary/mlx.core.argmin.html index 425f537b5..00e85ea91 100644 --- a/docs/build/html/python/_autosummary/mlx.core.argmin.html +++ b/docs/build/html/python/_autosummary/mlx.core.argmin.html @@ -8,7 +8,7 @@ - mlx.core.argmin — MLX 0.22.1 documentation + mlx.core.argmin — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.argpartition.html b/docs/build/html/python/_autosummary/mlx.core.argpartition.html index 4105bd9b5..60ba6535f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.argpartition.html +++ b/docs/build/html/python/_autosummary/mlx.core.argpartition.html @@ -8,7 +8,7 @@ - mlx.core.argpartition — MLX 0.22.1 documentation + mlx.core.argpartition — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.argsort.html b/docs/build/html/python/_autosummary/mlx.core.argsort.html index 0fb6c744a..817664d3d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.argsort.html +++ b/docs/build/html/python/_autosummary/mlx.core.argsort.html @@ -8,7 +8,7 @@ - mlx.core.argsort — MLX 0.22.1 documentation + mlx.core.argsort — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.T.html b/docs/build/html/python/_autosummary/mlx.core.array.T.html index ee75eb4ee..900cf5a63 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.T.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.T.html @@ -8,7 +8,7 @@ - mlx.core.array.T — MLX 0.22.1 documentation + mlx.core.array.T — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.abs.html b/docs/build/html/python/_autosummary/mlx.core.array.abs.html index e3ebaac14..d0280c38f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.abs.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.abs.html @@ -8,7 +8,7 @@ - mlx.core.array.abs — MLX 0.22.1 documentation + mlx.core.array.abs — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.all.html b/docs/build/html/python/_autosummary/mlx.core.array.all.html index 9f40384d6..ea2d762a1 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.all.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.all.html @@ -8,7 +8,7 @@ - mlx.core.array.all — MLX 0.22.1 documentation + mlx.core.array.all — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.any.html b/docs/build/html/python/_autosummary/mlx.core.array.any.html index a817833c3..6ba8da595 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.any.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.any.html @@ -8,7 +8,7 @@ - mlx.core.array.any — MLX 0.22.1 documentation + mlx.core.array.any — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.argmax.html b/docs/build/html/python/_autosummary/mlx.core.array.argmax.html index 3d25fbd07..6e8754d60 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.argmax.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.argmax.html @@ -8,7 +8,7 @@ - mlx.core.array.argmax — MLX 0.22.1 documentation + mlx.core.array.argmax — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.argmin.html b/docs/build/html/python/_autosummary/mlx.core.array.argmin.html index 3e0f52aa4..0efb6eb79 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.argmin.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.argmin.html @@ -8,7 +8,7 @@ - mlx.core.array.argmin — MLX 0.22.1 documentation + mlx.core.array.argmin — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.astype.html b/docs/build/html/python/_autosummary/mlx.core.array.astype.html index 6e34bd4b0..6076da914 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.astype.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.astype.html @@ -8,7 +8,7 @@ - mlx.core.array.astype — MLX 0.22.1 documentation + mlx.core.array.astype — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.at.html b/docs/build/html/python/_autosummary/mlx.core.array.at.html index dd49bd56e..4db6e7fb4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.at.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.at.html @@ -8,7 +8,7 @@ - mlx.core.array.at — MLX 0.22.1 documentation + mlx.core.array.at — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.conj.html b/docs/build/html/python/_autosummary/mlx.core.array.conj.html index 2f48f9183..ba1bda8e6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.conj.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.conj.html @@ -8,7 +8,7 @@ - mlx.core.array.conj — MLX 0.22.1 documentation + mlx.core.array.conj — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.cos.html b/docs/build/html/python/_autosummary/mlx.core.array.cos.html index 73212c58e..ee84a0183 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.cos.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.cos.html @@ -8,7 +8,7 @@ - mlx.core.array.cos — MLX 0.22.1 documentation + mlx.core.array.cos — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.cummax.html b/docs/build/html/python/_autosummary/mlx.core.array.cummax.html index 96089efc2..6d5542dc4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.cummax.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.cummax.html @@ -8,7 +8,7 @@ - mlx.core.array.cummax — MLX 0.22.1 documentation + mlx.core.array.cummax — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.cummin.html b/docs/build/html/python/_autosummary/mlx.core.array.cummin.html index c5d9e28d6..9134e9383 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.cummin.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.cummin.html @@ -8,7 +8,7 @@ - mlx.core.array.cummin — MLX 0.22.1 documentation + mlx.core.array.cummin — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.cumprod.html b/docs/build/html/python/_autosummary/mlx.core.array.cumprod.html index 5ca24905a..0547a41e7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.cumprod.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.cumprod.html @@ -8,7 +8,7 @@ - mlx.core.array.cumprod — MLX 0.22.1 documentation + mlx.core.array.cumprod — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.cumsum.html b/docs/build/html/python/_autosummary/mlx.core.array.cumsum.html index 3db5a695b..5b86fb30f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.cumsum.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.cumsum.html @@ -8,7 +8,7 @@ - mlx.core.array.cumsum — MLX 0.22.1 documentation + mlx.core.array.cumsum — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.diag.html b/docs/build/html/python/_autosummary/mlx.core.array.diag.html index d5092ad4e..4bf1aa615 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.diag.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.diag.html @@ -8,7 +8,7 @@ - mlx.core.array.diag — MLX 0.22.1 documentation + mlx.core.array.diag — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.diagonal.html b/docs/build/html/python/_autosummary/mlx.core.array.diagonal.html index 6bc55578f..918352a7d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.diagonal.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.diagonal.html @@ -8,7 +8,7 @@ - mlx.core.array.diagonal — MLX 0.22.1 documentation + mlx.core.array.diagonal — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.dtype.html b/docs/build/html/python/_autosummary/mlx.core.array.dtype.html index 371a9d20f..803d1e3be 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.dtype.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.dtype.html @@ -8,7 +8,7 @@ - mlx.core.array.dtype — MLX 0.22.1 documentation + mlx.core.array.dtype — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.exp.html b/docs/build/html/python/_autosummary/mlx.core.array.exp.html index 0d505aa53..9635eba29 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.exp.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.exp.html @@ -8,7 +8,7 @@ - mlx.core.array.exp — MLX 0.22.1 documentation + mlx.core.array.exp — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.flatten.html b/docs/build/html/python/_autosummary/mlx.core.array.flatten.html index 133fa5132..cbbcdae10 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.flatten.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.flatten.html @@ -8,7 +8,7 @@ - mlx.core.array.flatten — MLX 0.22.1 documentation + mlx.core.array.flatten — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.html b/docs/build/html/python/_autosummary/mlx.core.array.html index 65945696c..0ea8e27be 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.html @@ -8,7 +8,7 @@ - mlx.core.array — MLX 0.22.1 documentation + mlx.core.array — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.item.html b/docs/build/html/python/_autosummary/mlx.core.array.item.html index 6e0ab14ff..77e2fe908 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.item.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.item.html @@ -8,7 +8,7 @@ - mlx.core.array.item — MLX 0.22.1 documentation + mlx.core.array.item — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.itemsize.html b/docs/build/html/python/_autosummary/mlx.core.array.itemsize.html index 8bf65647f..9a613f962 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.itemsize.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.itemsize.html @@ -8,7 +8,7 @@ - mlx.core.array.itemsize — MLX 0.22.1 documentation + mlx.core.array.itemsize — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.log.html b/docs/build/html/python/_autosummary/mlx.core.array.log.html index d6454d4a1..cd13a43fe 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.log.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.log.html @@ -8,7 +8,7 @@ - mlx.core.array.log — MLX 0.22.1 documentation + mlx.core.array.log — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.log10.html b/docs/build/html/python/_autosummary/mlx.core.array.log10.html index ed0805d41..8cb022ed7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.log10.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.log10.html @@ -8,7 +8,7 @@ - mlx.core.array.log10 — MLX 0.22.1 documentation + mlx.core.array.log10 — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.log1p.html b/docs/build/html/python/_autosummary/mlx.core.array.log1p.html index a15131341..a0261a30d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.log1p.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.log1p.html @@ -8,7 +8,7 @@ - mlx.core.array.log1p — MLX 0.22.1 documentation + mlx.core.array.log1p — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.log2.html b/docs/build/html/python/_autosummary/mlx.core.array.log2.html index 95df4db6f..bde275a18 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.log2.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.log2.html @@ -8,7 +8,7 @@ - mlx.core.array.log2 — MLX 0.22.1 documentation + mlx.core.array.log2 — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.logsumexp.html b/docs/build/html/python/_autosummary/mlx.core.array.logsumexp.html index 0b307a028..7233b11b3 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.logsumexp.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.logsumexp.html @@ -8,7 +8,7 @@ - mlx.core.array.logsumexp — MLX 0.22.1 documentation + mlx.core.array.logsumexp — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.max.html b/docs/build/html/python/_autosummary/mlx.core.array.max.html index f29cd61fc..62274c391 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.max.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.max.html @@ -8,7 +8,7 @@ - mlx.core.array.max — MLX 0.22.1 documentation + mlx.core.array.max — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.mean.html b/docs/build/html/python/_autosummary/mlx.core.array.mean.html index 9b3458c01..d332b365f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.mean.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.mean.html @@ -8,7 +8,7 @@ - mlx.core.array.mean — MLX 0.22.1 documentation + mlx.core.array.mean — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.min.html b/docs/build/html/python/_autosummary/mlx.core.array.min.html index 0139f111e..64df7d2ca 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.min.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.min.html @@ -8,7 +8,7 @@ - mlx.core.array.min — MLX 0.22.1 documentation + mlx.core.array.min — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.moveaxis.html b/docs/build/html/python/_autosummary/mlx.core.array.moveaxis.html index 62c40df06..2a649e2b3 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.moveaxis.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.moveaxis.html @@ -8,7 +8,7 @@ - mlx.core.array.moveaxis — MLX 0.22.1 documentation + mlx.core.array.moveaxis — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.nbytes.html b/docs/build/html/python/_autosummary/mlx.core.array.nbytes.html index d8d35b141..227696e4f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.nbytes.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.nbytes.html @@ -8,7 +8,7 @@ - mlx.core.array.nbytes — MLX 0.22.1 documentation + mlx.core.array.nbytes — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.ndim.html b/docs/build/html/python/_autosummary/mlx.core.array.ndim.html index 2c408742b..63f77d7d4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.ndim.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.ndim.html @@ -8,7 +8,7 @@ - mlx.core.array.ndim — MLX 0.22.1 documentation + mlx.core.array.ndim — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.prod.html b/docs/build/html/python/_autosummary/mlx.core.array.prod.html index 1cd8a5535..5fb6da0df 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.prod.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.prod.html @@ -8,7 +8,7 @@ - mlx.core.array.prod — MLX 0.22.1 documentation + mlx.core.array.prod — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.reciprocal.html b/docs/build/html/python/_autosummary/mlx.core.array.reciprocal.html index b68f5a592..d6f6f61e1 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.reciprocal.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.reciprocal.html @@ -8,7 +8,7 @@ - mlx.core.array.reciprocal — MLX 0.22.1 documentation + mlx.core.array.reciprocal — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.reshape.html b/docs/build/html/python/_autosummary/mlx.core.array.reshape.html index 97e428055..5229682f4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.reshape.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.reshape.html @@ -8,7 +8,7 @@ - mlx.core.array.reshape — MLX 0.22.1 documentation + mlx.core.array.reshape — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.round.html b/docs/build/html/python/_autosummary/mlx.core.array.round.html index 176b5ee1c..16cb70c64 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.round.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.round.html @@ -8,7 +8,7 @@ - mlx.core.array.round — MLX 0.22.1 documentation + mlx.core.array.round — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.rsqrt.html b/docs/build/html/python/_autosummary/mlx.core.array.rsqrt.html index 6637dcb1c..fa689f951 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.rsqrt.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.rsqrt.html @@ -8,7 +8,7 @@ - mlx.core.array.rsqrt — MLX 0.22.1 documentation + mlx.core.array.rsqrt — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.shape.html b/docs/build/html/python/_autosummary/mlx.core.array.shape.html index b912f07da..5fc4aa6eb 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.shape.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.shape.html @@ -8,7 +8,7 @@ - mlx.core.array.shape — MLX 0.22.1 documentation + mlx.core.array.shape — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.sin.html b/docs/build/html/python/_autosummary/mlx.core.array.sin.html index 4ebaa5878..6d3921a5e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.sin.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.sin.html @@ -8,7 +8,7 @@ - mlx.core.array.sin — MLX 0.22.1 documentation + mlx.core.array.sin — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.size.html b/docs/build/html/python/_autosummary/mlx.core.array.size.html index 06a230c20..aa3d0f96b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.size.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.size.html @@ -8,7 +8,7 @@ - mlx.core.array.size — MLX 0.22.1 documentation + mlx.core.array.size — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.split.html b/docs/build/html/python/_autosummary/mlx.core.array.split.html index d909cbd91..39ebdf745 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.split.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.split.html @@ -8,7 +8,7 @@ - mlx.core.array.split — MLX 0.22.1 documentation + mlx.core.array.split — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.sqrt.html b/docs/build/html/python/_autosummary/mlx.core.array.sqrt.html index e1346b512..ce31455bf 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.sqrt.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.sqrt.html @@ -8,7 +8,7 @@ - mlx.core.array.sqrt — MLX 0.22.1 documentation + mlx.core.array.sqrt — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.square.html b/docs/build/html/python/_autosummary/mlx.core.array.square.html index d8ac62e1f..eb7f7494d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.square.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.square.html @@ -8,7 +8,7 @@ - mlx.core.array.square — MLX 0.22.1 documentation + mlx.core.array.square — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.squeeze.html b/docs/build/html/python/_autosummary/mlx.core.array.squeeze.html index 85f6513dc..be976efef 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.squeeze.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.squeeze.html @@ -8,7 +8,7 @@ - mlx.core.array.squeeze — MLX 0.22.1 documentation + mlx.core.array.squeeze — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.std.html b/docs/build/html/python/_autosummary/mlx.core.array.std.html index 953ba45af..9b320a8d3 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.std.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.std.html @@ -8,7 +8,7 @@ - mlx.core.array.std — MLX 0.22.1 documentation + mlx.core.array.std — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.sum.html b/docs/build/html/python/_autosummary/mlx.core.array.sum.html index c951c06a2..e3cd9cb54 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.sum.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.sum.html @@ -8,7 +8,7 @@ - mlx.core.array.sum — MLX 0.22.1 documentation + mlx.core.array.sum — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.swapaxes.html b/docs/build/html/python/_autosummary/mlx.core.array.swapaxes.html index f10963659..d3c343523 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.swapaxes.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.swapaxes.html @@ -8,7 +8,7 @@ - mlx.core.array.swapaxes — MLX 0.22.1 documentation + mlx.core.array.swapaxes — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.tolist.html b/docs/build/html/python/_autosummary/mlx.core.array.tolist.html index 6655e4e9e..7c29df900 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.tolist.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.tolist.html @@ -8,7 +8,7 @@ - mlx.core.array.tolist — MLX 0.22.1 documentation + mlx.core.array.tolist — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.transpose.html b/docs/build/html/python/_autosummary/mlx.core.array.transpose.html index 03712270b..aa8851259 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.transpose.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.transpose.html @@ -8,7 +8,7 @@ - mlx.core.array.transpose — MLX 0.22.1 documentation + mlx.core.array.transpose — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.var.html b/docs/build/html/python/_autosummary/mlx.core.array.var.html index eb87eeea6..93ed61dd5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.var.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.var.html @@ -8,7 +8,7 @@ - mlx.core.array.var — MLX 0.22.1 documentation + mlx.core.array.var — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array.view.html b/docs/build/html/python/_autosummary/mlx.core.array.view.html index b05b16746..65540965d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array.view.html +++ b/docs/build/html/python/_autosummary/mlx.core.array.view.html @@ -8,7 +8,7 @@ - mlx.core.array.view — MLX 0.22.1 documentation + mlx.core.array.view — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.array_equal.html b/docs/build/html/python/_autosummary/mlx.core.array_equal.html index 13879f304..48c1ca23a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.array_equal.html +++ b/docs/build/html/python/_autosummary/mlx.core.array_equal.html @@ -8,7 +8,7 @@ - mlx.core.array_equal — MLX 0.22.1 documentation + mlx.core.array_equal — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.as_strided.html b/docs/build/html/python/_autosummary/mlx.core.as_strided.html index 8bfe199fb..de356db86 100644 --- a/docs/build/html/python/_autosummary/mlx.core.as_strided.html +++ b/docs/build/html/python/_autosummary/mlx.core.as_strided.html @@ -8,7 +8,7 @@ - mlx.core.as_strided — MLX 0.22.1 documentation + mlx.core.as_strided — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.atleast_1d.html b/docs/build/html/python/_autosummary/mlx.core.atleast_1d.html index 30874acd3..f13b10bba 100644 --- a/docs/build/html/python/_autosummary/mlx.core.atleast_1d.html +++ b/docs/build/html/python/_autosummary/mlx.core.atleast_1d.html @@ -8,7 +8,7 @@ - mlx.core.atleast_1d — MLX 0.22.1 documentation + mlx.core.atleast_1d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.atleast_2d.html b/docs/build/html/python/_autosummary/mlx.core.atleast_2d.html index c20dca552..9377359db 100644 --- a/docs/build/html/python/_autosummary/mlx.core.atleast_2d.html +++ b/docs/build/html/python/_autosummary/mlx.core.atleast_2d.html @@ -8,7 +8,7 @@ - mlx.core.atleast_2d — MLX 0.22.1 documentation + mlx.core.atleast_2d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.atleast_3d.html b/docs/build/html/python/_autosummary/mlx.core.atleast_3d.html index 6ec9315ab..9ceeedc19 100644 --- a/docs/build/html/python/_autosummary/mlx.core.atleast_3d.html +++ b/docs/build/html/python/_autosummary/mlx.core.atleast_3d.html @@ -8,7 +8,7 @@ - mlx.core.atleast_3d — MLX 0.22.1 documentation + mlx.core.atleast_3d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.bitwise_and.html b/docs/build/html/python/_autosummary/mlx.core.bitwise_and.html index fbbd2e941..a9e4aef5a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.bitwise_and.html +++ b/docs/build/html/python/_autosummary/mlx.core.bitwise_and.html @@ -8,7 +8,7 @@ - mlx.core.bitwise_and — MLX 0.22.1 documentation + mlx.core.bitwise_and — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -47,11 +47,11 @@ - + - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      @@ -928,11 +933,11 @@ semantics. Either or both input arrays can also be scalars.

    • next

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    mlx.core.bitwise_or

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    mlx.core.bitwise_invert

     diff --git a/docs/build/html/python/_autosummary/mlx.core.bitwise_invert.html b/docs/build/html/python/_autosummary/mlx.core.bitwise_invert.html new file mode 100644 index 000000000..eae9ce7f0 --- /dev/null +++ b/docs/build/html/python/_autosummary/mlx.core.bitwise_invert.html @@ -0,0 +1,1012 @@ + + + + + + + + + + + mlx.core.bitwise_invert — MLX 0.23.0 documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    mlx.core.bitwise_invert

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    Contents

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    mlx.core.bitwise_invert#

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    +bitwise_invert(a: scalar | array, stream: None | Stream | Device = None) → array#
    +

    Element-wise bitwise inverse.

    +

    Take the bitwise complement of the input.

    +
    +
    Parameters:
    +

    a (array) – Input array or scalar.

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    Returns:
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    The bitwise inverse ~a.

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    Return type:
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    array

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    +By MLX Contributors +

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    + + © Copyright 2023, MLX Contributors. +
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    + + \ No newline at end of file diff --git a/docs/build/html/python/_autosummary/mlx.core.bitwise_or.html b/docs/build/html/python/_autosummary/mlx.core.bitwise_or.html index 8ec32a62b..04a2eeb2c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.bitwise_or.html +++ b/docs/build/html/python/_autosummary/mlx.core.bitwise_or.html @@ -8,7 +8,7 @@ - mlx.core.bitwise_or — MLX 0.22.1 documentation + mlx.core.bitwise_or — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -48,10 +48,10 @@ - + - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.block_masked_mm.html b/docs/build/html/python/_autosummary/mlx.core.block_masked_mm.html index 1e67353c5..2f547aaa8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.block_masked_mm.html +++ b/docs/build/html/python/_autosummary/mlx.core.block_masked_mm.html @@ -8,7 +8,7 @@ - mlx.core.block_masked_mm — MLX 0.22.1 documentation + mlx.core.block_masked_mm — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -52,7 +52,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -277,6 +277,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -487,6 +488,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.broadcast_to.html b/docs/build/html/python/_autosummary/mlx.core.broadcast_to.html index b3648d352..53c6b4c23 100644 --- a/docs/build/html/python/_autosummary/mlx.core.broadcast_to.html +++ b/docs/build/html/python/_autosummary/mlx.core.broadcast_to.html @@ -8,7 +8,7 @@ - mlx.core.broadcast_to — MLX 0.22.1 documentation + mlx.core.broadcast_to — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.ceil.html b/docs/build/html/python/_autosummary/mlx.core.ceil.html index b3529fb48..fe134858a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.ceil.html +++ b/docs/build/html/python/_autosummary/mlx.core.ceil.html @@ -8,7 +8,7 @@ - mlx.core.ceil — MLX 0.22.1 documentation + mlx.core.ceil — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.clip.html b/docs/build/html/python/_autosummary/mlx.core.clip.html index 2bc6be17e..8d29105d6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.clip.html +++ b/docs/build/html/python/_autosummary/mlx.core.clip.html @@ -8,7 +8,7 @@ - mlx.core.clip — MLX 0.22.1 documentation + mlx.core.clip — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
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    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.compile.html b/docs/build/html/python/_autosummary/mlx.core.compile.html index f52dd46ce..1401474b1 100644 --- a/docs/build/html/python/_autosummary/mlx.core.compile.html +++ b/docs/build/html/python/_autosummary/mlx.core.compile.html @@ -8,7 +8,7 @@ - mlx.core.compile — MLX 0.22.1 documentation + mlx.core.compile — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
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  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
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    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
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    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.concatenate.html b/docs/build/html/python/_autosummary/mlx.core.concatenate.html index d9e74ea9b..b98eb57a6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.concatenate.html +++ b/docs/build/html/python/_autosummary/mlx.core.concatenate.html @@ -8,7 +8,7 @@ - mlx.core.concatenate — MLX 0.22.1 documentation + mlx.core.concatenate — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
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    • +
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    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
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  • mlx.core.linalg.eigh
    • +
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    • +
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    • +
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    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conj.html b/docs/build/html/python/_autosummary/mlx.core.conj.html index 6e66269bb..01818bcf9 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conj.html +++ b/docs/build/html/python/_autosummary/mlx.core.conj.html @@ -8,7 +8,7 @@ - mlx.core.conj — MLX 0.22.1 documentation + mlx.core.conj — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
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    • +
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    • @@ -486,6 +487,10 @@
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    • +
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    • +
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    • +
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    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conjugate.html b/docs/build/html/python/_autosummary/mlx.core.conjugate.html index b69a47fae..475efd836 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conjugate.html +++ b/docs/build/html/python/_autosummary/mlx.core.conjugate.html @@ -8,7 +8,7 @@ - mlx.core.conjugate — MLX 0.22.1 documentation + mlx.core.conjugate — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
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    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conv1d.html b/docs/build/html/python/_autosummary/mlx.core.conv1d.html index 00683ad5a..6f02aa9fd 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conv1d.html +++ b/docs/build/html/python/_autosummary/mlx.core.conv1d.html @@ -8,7 +8,7 @@ - mlx.core.conv1d — MLX 0.22.1 documentation + mlx.core.conv1d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conv2d.html b/docs/build/html/python/_autosummary/mlx.core.conv2d.html index 40f183d42..f5f488a44 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conv2d.html +++ b/docs/build/html/python/_autosummary/mlx.core.conv2d.html @@ -8,7 +8,7 @@ - mlx.core.conv2d — MLX 0.22.1 documentation + mlx.core.conv2d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conv3d.html b/docs/build/html/python/_autosummary/mlx.core.conv3d.html index 514f8f182..a31533758 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conv3d.html +++ b/docs/build/html/python/_autosummary/mlx.core.conv3d.html @@ -8,7 +8,7 @@ - mlx.core.conv3d — MLX 0.22.1 documentation + mlx.core.conv3d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
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    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conv_general.html b/docs/build/html/python/_autosummary/mlx.core.conv_general.html index fe3686b94..b461c66f3 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conv_general.html +++ b/docs/build/html/python/_autosummary/mlx.core.conv_general.html @@ -8,7 +8,7 @@ - mlx.core.conv_general — MLX 0.22.1 documentation + mlx.core.conv_general — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
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    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
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    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conv_transpose1d.html b/docs/build/html/python/_autosummary/mlx.core.conv_transpose1d.html index 0d34306a7..9d7702c97 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conv_transpose1d.html +++ b/docs/build/html/python/_autosummary/mlx.core.conv_transpose1d.html @@ -8,7 +8,7 @@ - mlx.core.conv_transpose1d — MLX 0.22.1 documentation + mlx.core.conv_transpose1d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conv_transpose2d.html b/docs/build/html/python/_autosummary/mlx.core.conv_transpose2d.html index 0d8de88d1..eece265a5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conv_transpose2d.html +++ b/docs/build/html/python/_autosummary/mlx.core.conv_transpose2d.html @@ -8,7 +8,7 @@ - mlx.core.conv_transpose2d — MLX 0.22.1 documentation + mlx.core.conv_transpose2d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.conv_transpose3d.html b/docs/build/html/python/_autosummary/mlx.core.conv_transpose3d.html index 6901a3cbe..fefc7ac6c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.conv_transpose3d.html +++ b/docs/build/html/python/_autosummary/mlx.core.conv_transpose3d.html @@ -8,7 +8,7 @@ - mlx.core.conv_transpose3d — MLX 0.22.1 documentation + mlx.core.conv_transpose3d — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.convolve.html b/docs/build/html/python/_autosummary/mlx.core.convolve.html index f6c1d112b..e2607c04b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.convolve.html +++ b/docs/build/html/python/_autosummary/mlx.core.convolve.html @@ -8,7 +8,7 @@ - mlx.core.convolve — MLX 0.22.1 documentation + mlx.core.convolve — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
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  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
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    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.cos.html b/docs/build/html/python/_autosummary/mlx.core.cos.html index 5323e5371..7ff8c6958 100644 --- a/docs/build/html/python/_autosummary/mlx.core.cos.html +++ b/docs/build/html/python/_autosummary/mlx.core.cos.html @@ -8,7 +8,7 @@ - mlx.core.cos — MLX 0.22.1 documentation + mlx.core.cos — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
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  • mlx.core.atleast_3d
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    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
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    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.cosh.html b/docs/build/html/python/_autosummary/mlx.core.cosh.html index 1417ff90a..3acf1bb73 100644 --- a/docs/build/html/python/_autosummary/mlx.core.cosh.html +++ b/docs/build/html/python/_autosummary/mlx.core.cosh.html @@ -8,7 +8,7 @@ - mlx.core.cosh — MLX 0.22.1 documentation + mlx.core.cosh — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
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    • +
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  • mlx.core.bitwise_or
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  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
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  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
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    • +
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    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.cummax.html b/docs/build/html/python/_autosummary/mlx.core.cummax.html index 80aacb288..4232b9d9b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.cummax.html +++ b/docs/build/html/python/_autosummary/mlx.core.cummax.html @@ -8,7 +8,7 @@ - mlx.core.cummax — MLX 0.22.1 documentation + mlx.core.cummax — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
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  • mlx.core.atleast_3d
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    • +
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  • mlx.core.bitwise_or
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  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
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    • +
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    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.cummin.html b/docs/build/html/python/_autosummary/mlx.core.cummin.html index 8e517ce07..6d7bff961 100644 --- a/docs/build/html/python/_autosummary/mlx.core.cummin.html +++ b/docs/build/html/python/_autosummary/mlx.core.cummin.html @@ -8,7 +8,7 @@ - mlx.core.cummin — MLX 0.22.1 documentation + mlx.core.cummin — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
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    • +
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  • mlx.core.bitwise_or
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  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
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  • mlx.core.linalg.eigh
    • +
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    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.cumprod.html b/docs/build/html/python/_autosummary/mlx.core.cumprod.html index 552dd00b0..2b28491af 100644 --- a/docs/build/html/python/_autosummary/mlx.core.cumprod.html +++ b/docs/build/html/python/_autosummary/mlx.core.cumprod.html @@ -8,7 +8,7 @@ - mlx.core.cumprod — MLX 0.22.1 documentation + mlx.core.cumprod — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.cumsum.html b/docs/build/html/python/_autosummary/mlx.core.cumsum.html index 8ffa25b9a..113d853cf 100644 --- a/docs/build/html/python/_autosummary/mlx.core.cumsum.html +++ b/docs/build/html/python/_autosummary/mlx.core.cumsum.html @@ -8,7 +8,7 @@ - mlx.core.cumsum — MLX 0.22.1 documentation + mlx.core.cumsum — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.custom_function.html b/docs/build/html/python/_autosummary/mlx.core.custom_function.html index 63e4aa38f..7102f7f17 100644 --- a/docs/build/html/python/_autosummary/mlx.core.custom_function.html +++ b/docs/build/html/python/_autosummary/mlx.core.custom_function.html @@ -8,7 +8,7 @@ - mlx.core.custom_function — MLX 0.22.1 documentation + mlx.core.custom_function — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.default_device.html b/docs/build/html/python/_autosummary/mlx.core.default_device.html index 8539028c8..557069a19 100644 --- a/docs/build/html/python/_autosummary/mlx.core.default_device.html +++ b/docs/build/html/python/_autosummary/mlx.core.default_device.html @@ -8,7 +8,7 @@ - mlx.core.default_device — MLX 0.22.1 documentation + mlx.core.default_device — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.default_stream.html b/docs/build/html/python/_autosummary/mlx.core.default_stream.html index b841779ff..38b27ad27 100644 --- a/docs/build/html/python/_autosummary/mlx.core.default_stream.html +++ b/docs/build/html/python/_autosummary/mlx.core.default_stream.html @@ -8,7 +8,7 @@ - mlx.core.default_stream — MLX 0.22.1 documentation + mlx.core.default_stream — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.degrees.html b/docs/build/html/python/_autosummary/mlx.core.degrees.html index d6defe383..564f66acc 100644 --- a/docs/build/html/python/_autosummary/mlx.core.degrees.html +++ b/docs/build/html/python/_autosummary/mlx.core.degrees.html @@ -8,7 +8,7 @@ - mlx.core.degrees — MLX 0.22.1 documentation + mlx.core.degrees — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
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  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.dequantize.html b/docs/build/html/python/_autosummary/mlx.core.dequantize.html index 28704d31b..5f153e6b9 100644 --- a/docs/build/html/python/_autosummary/mlx.core.dequantize.html +++ b/docs/build/html/python/_autosummary/mlx.core.dequantize.html @@ -8,7 +8,7 @@ - mlx.core.dequantize — MLX 0.22.1 documentation + mlx.core.dequantize — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -52,7 +52,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -277,6 +277,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -487,6 +488,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.diag.html b/docs/build/html/python/_autosummary/mlx.core.diag.html index 079c3a304..2a8f314f2 100644 --- a/docs/build/html/python/_autosummary/mlx.core.diag.html +++ b/docs/build/html/python/_autosummary/mlx.core.diag.html @@ -8,7 +8,7 @@ - mlx.core.diag — MLX 0.22.1 documentation + mlx.core.diag — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -52,7 +52,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -277,6 +277,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -487,6 +488,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.diagonal.html b/docs/build/html/python/_autosummary/mlx.core.diagonal.html index a28d57529..9cb5dcae3 100644 --- a/docs/build/html/python/_autosummary/mlx.core.diagonal.html +++ b/docs/build/html/python/_autosummary/mlx.core.diagonal.html @@ -8,7 +8,7 @@ - mlx.core.diagonal — MLX 0.22.1 documentation + mlx.core.diagonal — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.disable_compile.html b/docs/build/html/python/_autosummary/mlx.core.disable_compile.html index 6d0b43c64..3a060bcbc 100644 --- a/docs/build/html/python/_autosummary/mlx.core.disable_compile.html +++ b/docs/build/html/python/_autosummary/mlx.core.disable_compile.html @@ -8,7 +8,7 @@ - mlx.core.disable_compile — MLX 0.22.1 documentation + mlx.core.disable_compile — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.Group.html b/docs/build/html/python/_autosummary/mlx.core.distributed.Group.html index 993d53e41..123773636 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.Group.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.Group.html @@ -8,7 +8,7 @@ - mlx.core.distributed.Group — MLX 0.22.1 documentation + mlx.core.distributed.Group — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.all_gather.html b/docs/build/html/python/_autosummary/mlx.core.distributed.all_gather.html index db717762c..07f016e50 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.all_gather.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.all_gather.html @@ -8,7 +8,7 @@ - mlx.core.distributed.all_gather — MLX 0.22.1 documentation + mlx.core.distributed.all_gather — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.all_sum.html b/docs/build/html/python/_autosummary/mlx.core.distributed.all_sum.html index f89d9b3d2..b51aa5ea0 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.all_sum.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.all_sum.html @@ -8,7 +8,7 @@ - mlx.core.distributed.all_sum — MLX 0.22.1 documentation + mlx.core.distributed.all_sum — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.init.html b/docs/build/html/python/_autosummary/mlx.core.distributed.init.html index d88b7fe24..e0f34cede 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.init.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.init.html @@ -8,7 +8,7 @@ - mlx.core.distributed.init — MLX 0.22.1 documentation + mlx.core.distributed.init — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.is_available.html b/docs/build/html/python/_autosummary/mlx.core.distributed.is_available.html index ec5da1158..3079eb8dd 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.is_available.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.is_available.html @@ -8,7 +8,7 @@ - mlx.core.distributed.is_available — MLX 0.22.1 documentation + mlx.core.distributed.is_available — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.recv.html b/docs/build/html/python/_autosummary/mlx.core.distributed.recv.html index a0e7f4725..8da8255a5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.recv.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.recv.html @@ -8,7 +8,7 @@ - mlx.core.distributed.recv — MLX 0.22.1 documentation + mlx.core.distributed.recv — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.recv_like.html b/docs/build/html/python/_autosummary/mlx.core.distributed.recv_like.html index c35d32ba2..2992c4727 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.recv_like.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.recv_like.html @@ -8,7 +8,7 @@ - mlx.core.distributed.recv_like — MLX 0.22.1 documentation + mlx.core.distributed.recv_like — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.distributed.send.html b/docs/build/html/python/_autosummary/mlx.core.distributed.send.html index 83bbd7c2b..cf19b504b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.distributed.send.html +++ b/docs/build/html/python/_autosummary/mlx.core.distributed.send.html @@ -8,7 +8,7 @@ - mlx.core.distributed.send — MLX 0.22.1 documentation + mlx.core.distributed.send — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.divide.html b/docs/build/html/python/_autosummary/mlx.core.divide.html index f5d13f056..4bc9a4138 100644 --- a/docs/build/html/python/_autosummary/mlx.core.divide.html +++ b/docs/build/html/python/_autosummary/mlx.core.divide.html @@ -8,7 +8,7 @@ - mlx.core.divide — MLX 0.22.1 documentation + mlx.core.divide — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.divmod.html b/docs/build/html/python/_autosummary/mlx.core.divmod.html index af07df1a6..8440e17ca 100644 --- a/docs/build/html/python/_autosummary/mlx.core.divmod.html +++ b/docs/build/html/python/_autosummary/mlx.core.divmod.html @@ -8,7 +8,7 @@ - mlx.core.divmod — MLX 0.22.1 documentation + mlx.core.divmod — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.einsum.html b/docs/build/html/python/_autosummary/mlx.core.einsum.html index 06ec78bde..75c46f345 100644 --- a/docs/build/html/python/_autosummary/mlx.core.einsum.html +++ b/docs/build/html/python/_autosummary/mlx.core.einsum.html @@ -8,7 +8,7 @@ - mlx.core.einsum — MLX 0.22.1 documentation + mlx.core.einsum — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.einsum_path.html b/docs/build/html/python/_autosummary/mlx.core.einsum_path.html index ced9529f2..cd309f353 100644 --- a/docs/build/html/python/_autosummary/mlx.core.einsum_path.html +++ b/docs/build/html/python/_autosummary/mlx.core.einsum_path.html @@ -8,7 +8,7 @@ - mlx.core.einsum_path — MLX 0.22.1 documentation + mlx.core.einsum_path — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.enable_compile.html b/docs/build/html/python/_autosummary/mlx.core.enable_compile.html index 0478e72cf..fe0ba77d7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.enable_compile.html +++ b/docs/build/html/python/_autosummary/mlx.core.enable_compile.html @@ -8,7 +8,7 @@ - mlx.core.enable_compile — MLX 0.22.1 documentation + mlx.core.enable_compile — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.equal.html b/docs/build/html/python/_autosummary/mlx.core.equal.html index e93573c46..436dc8822 100644 --- a/docs/build/html/python/_autosummary/mlx.core.equal.html +++ b/docs/build/html/python/_autosummary/mlx.core.equal.html @@ -8,7 +8,7 @@ - mlx.core.equal — MLX 0.22.1 documentation + mlx.core.equal — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.erf.html b/docs/build/html/python/_autosummary/mlx.core.erf.html index 58d03df1b..50798bc0b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.erf.html +++ b/docs/build/html/python/_autosummary/mlx.core.erf.html @@ -8,7 +8,7 @@ - mlx.core.erf — MLX 0.22.1 documentation + mlx.core.erf — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -52,7 +52,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -277,6 +277,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -487,6 +488,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.erfinv.html b/docs/build/html/python/_autosummary/mlx.core.erfinv.html index 677f091b7..999c2c159 100644 --- a/docs/build/html/python/_autosummary/mlx.core.erfinv.html +++ b/docs/build/html/python/_autosummary/mlx.core.erfinv.html @@ -8,7 +8,7 @@ - mlx.core.erfinv — MLX 0.22.1 documentation + mlx.core.erfinv — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
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  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.eval.html b/docs/build/html/python/_autosummary/mlx.core.eval.html index c13d97337..d4a1b4412 100644 --- a/docs/build/html/python/_autosummary/mlx.core.eval.html +++ b/docs/build/html/python/_autosummary/mlx.core.eval.html @@ -8,7 +8,7 @@ - mlx.core.eval — MLX 0.22.1 documentation + mlx.core.eval — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.exp.html b/docs/build/html/python/_autosummary/mlx.core.exp.html index 967c93580..9319a134d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.exp.html +++ b/docs/build/html/python/_autosummary/mlx.core.exp.html @@ -8,7 +8,7 @@ - mlx.core.exp — MLX 0.22.1 documentation + mlx.core.exp — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.expand_dims.html b/docs/build/html/python/_autosummary/mlx.core.expand_dims.html index bc924acac..ed836a8e1 100644 --- a/docs/build/html/python/_autosummary/mlx.core.expand_dims.html +++ b/docs/build/html/python/_autosummary/mlx.core.expand_dims.html @@ -8,7 +8,7 @@ - mlx.core.expand_dims — MLX 0.22.1 documentation + mlx.core.expand_dims — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.expm1.html b/docs/build/html/python/_autosummary/mlx.core.expm1.html index 7e462a405..440b20382 100644 --- a/docs/build/html/python/_autosummary/mlx.core.expm1.html +++ b/docs/build/html/python/_autosummary/mlx.core.expm1.html @@ -8,7 +8,7 @@ - mlx.core.expm1 — MLX 0.22.1 documentation + mlx.core.expm1 — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.export_function.html b/docs/build/html/python/_autosummary/mlx.core.export_function.html index 83e392ef7..b6a275a8e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.export_function.html +++ b/docs/build/html/python/_autosummary/mlx.core.export_function.html @@ -8,7 +8,7 @@ - mlx.core.export_function — MLX 0.22.1 documentation + mlx.core.export_function — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.export_to_dot.html b/docs/build/html/python/_autosummary/mlx.core.export_to_dot.html index b5b7a2a9c..573dee36c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.export_to_dot.html +++ b/docs/build/html/python/_autosummary/mlx.core.export_to_dot.html @@ -8,7 +8,7 @@ - mlx.core.export_to_dot — MLX 0.22.1 documentation + mlx.core.export_to_dot — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.exporter.html b/docs/build/html/python/_autosummary/mlx.core.exporter.html index 52dc7efec..cfe785485 100644 --- a/docs/build/html/python/_autosummary/mlx.core.exporter.html +++ b/docs/build/html/python/_autosummary/mlx.core.exporter.html @@ -8,7 +8,7 @@ - mlx.core.exporter — MLX 0.22.1 documentation + mlx.core.exporter — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.eye.html b/docs/build/html/python/_autosummary/mlx.core.eye.html index 24c124b59..88bdb8733 100644 --- a/docs/build/html/python/_autosummary/mlx.core.eye.html +++ b/docs/build/html/python/_autosummary/mlx.core.eye.html @@ -8,7 +8,7 @@ - mlx.core.eye — MLX 0.22.1 documentation + mlx.core.eye — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.layer_norm.html b/docs/build/html/python/_autosummary/mlx.core.fast.layer_norm.html index 33b393318..e3ff5ad9a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.layer_norm.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.layer_norm.html @@ -8,7 +8,7 @@ - mlx.core.fast.layer_norm — MLX 0.22.1 documentation + mlx.core.fast.layer_norm — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.metal_kernel.html b/docs/build/html/python/_autosummary/mlx.core.fast.metal_kernel.html index 2632979e5..cbd367858 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.metal_kernel.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.metal_kernel.html @@ -8,7 +8,7 @@ - mlx.core.fast.metal_kernel — MLX 0.22.1 documentation + mlx.core.fast.metal_kernel — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.rms_norm.html b/docs/build/html/python/_autosummary/mlx.core.fast.rms_norm.html index 8506b4a96..0e9b10be9 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.rms_norm.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.rms_norm.html @@ -8,7 +8,7 @@ - mlx.core.fast.rms_norm — MLX 0.22.1 documentation + mlx.core.fast.rms_norm — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.rope.html b/docs/build/html/python/_autosummary/mlx.core.fast.rope.html index 2a6436517..2459f322b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.rope.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.rope.html @@ -8,7 +8,7 @@ - mlx.core.fast.rope — MLX 0.22.1 documentation + mlx.core.fast.rope — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.scaled_dot_product_attention.html b/docs/build/html/python/_autosummary/mlx.core.fast.scaled_dot_product_attention.html index 25bd353e4..84537c382 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.scaled_dot_product_attention.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.scaled_dot_product_attention.html @@ -8,7 +8,7 @@ - mlx.core.fast.scaled_dot_product_attention — MLX 0.22.1 documentation + mlx.core.fast.scaled_dot_product_attention — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.fft.html b/docs/build/html/python/_autosummary/mlx.core.fft.fft.html index e516ebe71..c0ef6513d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.fft.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.fft.html @@ -8,7 +8,7 @@ - mlx.core.fft.fft — MLX 0.22.1 documentation + mlx.core.fft.fft — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.fft2.html b/docs/build/html/python/_autosummary/mlx.core.fft.fft2.html index 59f690ba5..9402ba579 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.fft2.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.fft2.html @@ -8,7 +8,7 @@ - mlx.core.fft.fft2 — MLX 0.22.1 documentation + mlx.core.fft.fft2 — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.fftn.html b/docs/build/html/python/_autosummary/mlx.core.fft.fftn.html index 4fc19c31f..b4ae14d70 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.fftn.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.fftn.html @@ -8,7 +8,7 @@ - mlx.core.fft.fftn — MLX 0.22.1 documentation + mlx.core.fft.fftn — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.ifft.html b/docs/build/html/python/_autosummary/mlx.core.fft.ifft.html index f850f2703..8b8566a91 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.ifft.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.ifft.html @@ -8,7 +8,7 @@ - mlx.core.fft.ifft — MLX 0.22.1 documentation + mlx.core.fft.ifft — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.ifft2.html b/docs/build/html/python/_autosummary/mlx.core.fft.ifft2.html index 6e20f3aa2..2dfeba5e1 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.ifft2.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.ifft2.html @@ -8,7 +8,7 @@ - mlx.core.fft.ifft2 — MLX 0.22.1 documentation + mlx.core.fft.ifft2 — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.ifftn.html b/docs/build/html/python/_autosummary/mlx.core.fft.ifftn.html index c2fb5356e..7950ddc87 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.ifftn.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.ifftn.html @@ -8,7 +8,7 @@ - mlx.core.fft.ifftn — MLX 0.22.1 documentation + mlx.core.fft.ifftn — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.irfft.html b/docs/build/html/python/_autosummary/mlx.core.fft.irfft.html index 71f0013f7..3d577d4e4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.irfft.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.irfft.html @@ -8,7 +8,7 @@ - mlx.core.fft.irfft — MLX 0.22.1 documentation + mlx.core.fft.irfft — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.irfft2.html b/docs/build/html/python/_autosummary/mlx.core.fft.irfft2.html index 0003c739d..8edb4354e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.irfft2.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.irfft2.html @@ -8,7 +8,7 @@ - mlx.core.fft.irfft2 — MLX 0.22.1 documentation + mlx.core.fft.irfft2 — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home
    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
  • Metal
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    • @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
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  • mlx.core.linalg.svd
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    • +
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      @@ -937,13 +942,22 @@
    • - + + + + +

    Namespaces

    4

    32-bit float

    complex64

    float64

    4

    64-bit double

    complex64

    8

    64-bit complex float
    +
    +

    Note

    +

    Arrays with type float64 only work with CPU operations. Using +float64 arrays on the GPU will result in an exception.

    +

    Data type are aranged in a hierarchy. See the DtypeCategory object documentation for more information. Use issubdtype() to determine if one dtype (or category) is a subtype of another category.

    diff --git a/docs/build/html/python/devices_and_streams.html b/docs/build/html/python/devices_and_streams.html index 3e56cd0d0..31ffbc88a 100644 --- a/docs/build/html/python/devices_and_streams.html +++ b/docs/build/html/python/devices_and_streams.html @@ -8,7 +8,7 @@ - Devices and Streams — MLX 0.22.1 documentation + Devices and Streams — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home @@ -276,6 +276,7 @@
  • mlx.core.atleast_2d
  • mlx.core.atleast_3d
  • mlx.core.bitwise_and
    • +
  • mlx.core.bitwise_invert
  • mlx.core.bitwise_or
  • mlx.core.bitwise_xor
  • mlx.core.block_masked_mm
    • @@ -486,6 +487,10 @@
  • mlx.core.linalg.svd
  • mlx.core.linalg.eigvalsh
  • mlx.core.linalg.eigh
    • +
  • mlx.core.linalg.lu
    • +
  • mlx.core.linalg.lu_factor
    • +
  • mlx.core.linalg.solve
    • +
  • mlx.core.linalg.solve_triangular
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      @@ -885,7 +890,7 @@

      mlx.nn.Transformer#

      -class Transformer(dims: int = 512, num_heads: int = 8, num_encoder_layers: int = 6, num_decoder_layers: int = 6, mlp_dims: int | None = None, dropout: float = 0.0, activation: ~typing.Callable[[~typing.Any], ~typing.Any] = <nanobind.nb_func object>, custom_encoder: ~typing.Any | None = None, custom_decoder: ~typing.Any | None = None, norm_first: bool = True, checkpoint: bool = False)#
      +class Transformer(dims: int = 512, num_heads: int = 8, num_encoder_layers: int = 6, num_decoder_layers: int = 6, mlp_dims: int | None = None, dropout: float = 0.0, activation: ~typing.Callable[[~typing.Any], ~typing.Any] = <mlx.gc_func object>, custom_encoder: ~typing.Any | None = None, custom_decoder: ~typing.Any | None = None, norm_first: bool = True, checkpoint: bool = False)#

      Implements a standard Transformer model.

      The implementation is based on Attention Is All You Need.

      The Transformer model contains an encoder and a decoder. The encoder diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Upsample.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Upsample.html index 14d432a88..4b901f5dd 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Upsample.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Upsample.html @@ -8,7 +8,7 @@ - mlx.nn.Upsample — MLX 0.22.1 documentation + mlx.nn.Upsample — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home @@ -276,6 +276,7 @@

    • mlx.core.atleast_2d
    • mlx.core.atleast_3d
    • mlx.core.bitwise_and
      • +
    • mlx.core.bitwise_invert
    • mlx.core.bitwise_or
    • mlx.core.bitwise_xor
    • mlx.core.block_masked_mm
      • @@ -486,6 +487,10 @@
    • mlx.core.linalg.svd
    • mlx.core.linalg.eigvalsh
    • mlx.core.linalg.eigh
      • +
    • mlx.core.linalg.lu
      • +
    • mlx.core.linalg.lu_factor
      • +
    • mlx.core.linalg.solve
      • +
    • mlx.core.linalg.solve_triangular
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      @@ -878,77 +883,77 @@ simple functions.

      - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + - - + + diff --git a/docs/build/html/python/nn/init.html b/docs/build/html/python/nn/init.html index 6e2bc3571..512cc44b4 100644 --- a/docs/build/html/python/nn/init.html +++ b/docs/build/html/python/nn/init.html @@ -8,7 +8,7 @@ - Initializers — MLX 0.22.1 documentation + Initializers — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -52,7 +52,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home @@ -277,6 +277,7 @@
    • mlx.core.atleast_2d
    • mlx.core.atleast_3d
    • mlx.core.bitwise_and
      • +
    • mlx.core.bitwise_invert
    • mlx.core.bitwise_or
    • mlx.core.bitwise_xor
    • mlx.core.block_masked_mm
      • @@ -487,6 +488,10 @@
    • mlx.core.linalg.svd
    • mlx.core.linalg.eigvalsh
    • mlx.core.linalg.eigh
      • +
    • mlx.core.linalg.lu
      • +
    • mlx.core.linalg.lu_factor
      • +
    • mlx.core.linalg.solve
      • +
    • mlx.core.linalg.solve_triangular
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        @@ -948,439 +953,442 @@
      • - + + + + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + diff --git a/docs/build/html/python/optimizers.html b/docs/build/html/python/optimizers.html index db48d236f..ac56eb962 100644 --- a/docs/build/html/python/optimizers.html +++ b/docs/build/html/python/optimizers.html @@ -8,7 +8,7 @@ - Optimizers — MLX 0.22.1 documentation + Optimizers — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -52,7 +52,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home @@ -277,6 +277,7 @@
    • mlx.core.atleast_2d
    • mlx.core.atleast_3d
    • mlx.core.bitwise_and
      • +
    • mlx.core.bitwise_invert
    • mlx.core.bitwise_or
    • mlx.core.bitwise_xor
    • mlx.core.block_masked_mm
      • @@ -487,6 +488,10 @@
    • mlx.core.linalg.svd
    • mlx.core.linalg.eigvalsh
    • mlx.core.linalg.eigh
      • +
    • mlx.core.linalg.lu
      • +
    • mlx.core.linalg.lu_factor
      • +
    • mlx.core.linalg.solve
      • +
    • mlx.core.linalg.solve_triangular
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        diff --git a/docs/build/html/quantized_8h_source.html b/docs/build/html/quantized_8h_source.html index 45011ee0e..bdf2d0962 100644 --- a/docs/build/html/quantized_8h_source.html +++ b/docs/build/html/quantized_8h_source.html @@ -780,14 +780,14 @@ $(function(){initNavTree('quantized_8h_source.html',''); initResizable(true); })
        648 // Adjust positions
        649 const int in_vec_size_w = in_vec_size * bytes_per_pack / pack_factor;
        650 const int in_vec_size_g = in_vec_size / group_size;
        -
        651 const int out_row = tid.x * (num_simdgroups * results_per_simdgroup) +
        +
        651 const int out_row = tid.y * (num_simdgroups * results_per_simdgroup) +
        652 simd_gid * results_per_simdgroup;
        653
        654 ws += out_row * in_vec_size_w + simd_lid * packs_per_thread * bytes_per_pack;
        655 scales += out_row * in_vec_size_g + simd_lid / scale_step_per_thread;
        656 biases += out_row * in_vec_size_g + simd_lid / scale_step_per_thread;
        -
        657 x += tid.y * in_vec_size + simd_lid * values_per_thread;
        -
        658 y += tid.y * out_vec_size + out_row;
        +
        657 x += tid.x * in_vec_size + simd_lid * values_per_thread;
        +
        658 y += tid.x * out_vec_size + out_row;
        659
        660 for (int k = 0; k < in_vec_size; k += block_size) {
        661 U sum = load_vector<T, U, values_per_thread, bits>(x, x_thread);
        @@ -850,7 +850,7 @@ $(function(){initNavTree('quantized_8h_source.html',''); initResizable(true); })
        716 // Adjust positions
        717 const int in_vec_size_w = in_vec_size * bytes_per_pack / pack_factor;
        718 const int in_vec_size_g = in_vec_size / group_size;
        -
        719 const int out_row = tid.x * (num_simdgroups * results_per_simdgroup) +
        +
        719 const int out_row = tid.y * (num_simdgroups * results_per_simdgroup) +
        720 simd_gid * results_per_simdgroup;
        721 const int used_out_row = min(out_vec_size - results_per_simdgroup, out_row);
        722
        @@ -865,8 +865,8 @@ $(function(){initNavTree('quantized_8h_source.html',''); initResizable(true); })
        731 out_row * in_vec_size_w + simd_lid * packs_per_thread * bytes_per_pack;
        732 scales += out_row * in_vec_size_g + simd_lid / scale_step_per_thread;
        733 biases += out_row * in_vec_size_g + simd_lid / scale_step_per_thread;
        -
        734 x += tid.y * in_vec_size + simd_lid * values_per_thread;
        -
        735 y += tid.y * out_vec_size + out_row;
        +
        734 x += tid.x * in_vec_size + simd_lid * values_per_thread;
        +
        735 y += tid.x * out_vec_size + out_row;
        736
        737 int k = 0;
        738 for (; k < in_vec_size - block_size; k += block_size) {
        @@ -922,8 +922,8 @@ $(function(){initNavTree('quantized_8h_source.html',''); initResizable(true); })
        788 simd_lid * packs_per_thread * bytes_per_pack;
        789 scales += used_out_row * in_vec_size_g + simd_lid / scale_step_per_thread;
        790 biases += used_out_row * in_vec_size_g + simd_lid / scale_step_per_thread;
        -
        791 x += tid.y * in_vec_size + simd_lid * values_per_thread;
        -
        792 y += tid.y * out_vec_size + used_out_row;
        +
        791 x += tid.x * in_vec_size + simd_lid * values_per_thread;
        +
        792 y += tid.x * out_vec_size + used_out_row;
        793
        794 int k = 0;
        795 for (; k < in_vec_size - block_size; k += block_size) {
        @@ -1012,12 +1012,12 @@ $(function(){initNavTree('quantized_8h_source.html',''); initResizable(true); })
        876 // Adjust positions
        877 const int out_vec_size_w = out_vec_size * bytes_per_pack / pack_factor;
        878 const int out_vec_size_g = out_vec_size / group_size;
        -
        879 int out_col = pack_factor * tn * (tid.x * num_simdgroups + simd_gid);
        +
        879 int out_col = pack_factor * tn * (tid.y * num_simdgroups + simd_gid);
        880 ws += out_col * bytes_per_pack / pack_factor + simd_lid * out_vec_size_w;
        881 scales += out_col / group_size + simd_lid * out_vec_size_g;
        882 biases += out_col / group_size + simd_lid * out_vec_size_g;
        -
        883 x += tid.y * in_vec_size + simd_lid;
        -
        884 y += tid.y * out_vec_size + out_col;
        +
        883 x += tid.x * in_vec_size + simd_lid;
        +
        884 y += tid.x * out_vec_size + out_col;
        885
        886 if (out_col >= out_vec_size) {
        887 return;
        diff --git a/docs/build/html/random_8h_source.html b/docs/build/html/random_8h_source.html index 0c60e3edc..77c81427d 100644 --- a/docs/build/html/random_8h_source.html +++ b/docs/build/html/random_8h_source.html @@ -414,8 +414,8 @@ $(function(){initNavTree('random_8h_source.html',''); initResizable(true); });
        mlx::core::random::multivariate_normal
        array multivariate_normal(const array &mean, const array &cov, const Shape &shape, Dtype dtype, const std::optional< array > &key=std::nullopt, StreamOrDevice s={})
        Generate samples from a multivariate normal distribution.
        mlx::core::random::truncated_normal
        array truncated_normal(const array &lower, const array &upper, const Shape &shape, Dtype dtype=float32, const std::optional< array > &key=std::nullopt, StreamOrDevice s={})
        mlx::core::to_stream
        Stream to_stream(StreamOrDevice s)
        -
        mlx::core::int32
        constexpr Dtype int32
        Definition dtype.h:76
        -
        mlx::core::float32
        constexpr Dtype float32
        Definition dtype.h:80
        +
        mlx::core::int32
        constexpr Dtype int32
        Definition dtype.h:77
        +
        mlx::core::float32
        constexpr Dtype float32
        Definition dtype.h:81
        mlx::core::Shape
        std::vector< ShapeElem > Shape
        Definition array.h:21
        mlx::core::StreamOrDevice
        std::variant< std::monostate, Stream, Device > StreamOrDevice
        Definition utils.h:15
        diff --git a/docs/build/html/search.html b/docs/build/html/search.html index d2c1463d9..2d739df69 100644 --- a/docs/build/html/search.html +++ b/docs/build/html/search.html @@ -6,7 +6,7 @@ - Search - MLX 0.22.1 documentation + Search - MLX 0.23.0 documentation @@ -37,7 +37,7 @@ - + @@ -50,7 +50,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home @@ -277,6 +277,7 @@
      • mlx.core.atleast_2d
      • mlx.core.atleast_3d
      • mlx.core.bitwise_and
        • +
      • mlx.core.bitwise_invert
      • mlx.core.bitwise_or
      • mlx.core.bitwise_xor
      • mlx.core.block_masked_mm
        • @@ -487,6 +488,10 @@
      • mlx.core.linalg.svd
      • mlx.core.linalg.eigvalsh
      • mlx.core.linalg.eigh
        • +
      • mlx.core.linalg.lu
        • +
      • mlx.core.linalg.lu_factor
        • +
      • mlx.core.linalg.solve
        • +
      • mlx.core.linalg.solve_triangular
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+ + + + + + + + + + + + + + + +
        +
        +

      • elu(x[, alpha])

      Applies the Exponential Linear Unit.

      elu

      elu(x, alpha=1.0)

      celu(x[, alpha])

      Applies the Continuously Differentiable Exponential Linear Unit.

      celu

      celu(x, alpha=1.0)

      gelu(x)

      Applies the Gaussian Error Linear Units function.

      gelu

      gelu(x) -> mlx.core.array

      gelu_approx(x)

      An approximation to Gaussian Error Linear Unit.

      gelu_approx

      gelu_approx(x)

      gelu_fast_approx(x)

      A fast approximation to Gaussian Error Linear Unit.

      gelu_fast_approx

      gelu_fast_approx(x)

      glu(x[, axis])

      Applies the gated linear unit function.

      hard_shrink(x[, lambd])

      Applies the HardShrink activation function.

      hard_shrink

      hard_shrink(x, lambd=0.5)

      hard_tanh(x[, min_val, max_val])

      Applies the HardTanh function.

      hard_tanh

      hard_tanh(x, min_val=-1.0, max_val=1.0)

      hardswish(x)

      Applies the hardswish function, element-wise.

      hardswish

      hardswish(x)

      leaky_relu(x[, negative_slope])

      Applies the Leaky Rectified Linear Unit.

      leaky_relu

      leaky_relu(x, negative_slope=0.01)

      log_sigmoid(x)

      Applies the Log Sigmoid function.

      log_sigmoid

      log_sigmoid(x)

      log_softmax(x[, axis])

      Applies the Log Softmax function.

      log_softmax

      log_softmax(x, axis=-1)

      mish(x)

      Applies the Mish function, element-wise.

      mish

      mlx.core.array) -> mlx.core.array

      prelu(x, alpha)

      Applies the element-wise parametric ReLU.

      prelu

      mlx.core.array) -> mlx.core.array

      relu(x)

      Applies the Rectified Linear Unit.

      relu

      relu(x)

      relu6(x)

      Applies the Rectified Linear Unit 6.

      relu6

      relu6(x)

      selu(x)

      Applies the Scaled Exponential Linear Unit.

      selu

      selu(x)

      sigmoid(x)

      Applies the sigmoid function.

      sigmoid

      sigmoid(x)

      silu(x)

      Applies the Sigmoid Linear Unit.

      silu

      silu(x)

      softmax(x[, axis])

      Applies the Softmax function.

      softmax

      softmax(x, axis=-1)

      softmin(x[, axis])

      Applies the Softmin function.

      softmin

      softmin(x, axis=-1)

      softplus(x)

      Applies the Softplus function.

      softplus

      softplus(x)

      softshrink(x[, lambd])

      Applies the Softshrink activation function.

      softshrink

      float = 0.5)

      step(x[, threshold])

      Applies the Step Activation Function.

      step

      float = 0.0)

      tanh(x)

      Applies the hyperbolic tangent function.

      bitwise_and(a, b[, stream])

      Element-wise bitwise and.

      bitwise_or(a, b[, stream])

      bitwise_invert(a[, stream])

      Element-wise bitwise inverse.

      bitwise_or(a, b[, stream])

      Element-wise bitwise or.

      bitwise_xor(a, b[, stream])

      bitwise_xor(a, b[, stream])

      Element-wise bitwise xor.

      block_masked_mm(a, b, /[, block_size, ...])

      block_masked_mm(a, b, /[, block_size, ...])

      Matrix multiplication with block masking.

      broadcast_to(a, /, shape, *[, stream])

      broadcast_to(a, /, shape, *[, stream])

      Broadcast an array to the given shape.

      ceil(a, /, *[, stream])

      ceil(a, /, *[, stream])

      Element-wise ceil.

      clip(a, /, a_min, a_max, *[, stream])

      clip(a, /, a_min, a_max, *[, stream])

      Clip the values of the array between the given minimum and maximum.

      concatenate(arrays[, axis, stream])

      concatenate(arrays[, axis, stream])

      Concatenate the arrays along the given axis.

      conj(a, *[, stream])

      conj(a, *[, stream])

      Return the elementwise complex conjugate of the input.

      conjugate(a, *[, stream])

      conjugate(a, *[, stream])

      Return the elementwise complex conjugate of the input.

      convolve(a, v, /[, mode, stream])

      convolve(a, v, /[, mode, stream])

      The discrete convolution of 1D arrays.

      conv1d(input, weight, /[, stride, padding, ...])

      conv1d(input, weight, /[, stride, padding, ...])

      1D convolution over an input with several channels

      conv2d(input, weight, /[, stride, padding, ...])

      conv2d(input, weight, /[, stride, padding, ...])

      2D convolution over an input with several channels

      conv3d(input, weight, /[, stride, padding, ...])

      conv3d(input, weight, /[, stride, padding, ...])

      3D convolution over an input with several channels

      conv_transpose1d(input, weight, /[, stride, ...])

      conv_transpose1d(input, weight, /[, stride, ...])

      1D transposed convolution over an input with several channels

      conv_transpose2d(input, weight, /[, stride, ...])

      conv_transpose2d(input, weight, /[, stride, ...])

      2D transposed convolution over an input with several channels

      conv_transpose3d(input, weight, /[, stride, ...])

      conv_transpose3d(input, weight, /[, stride, ...])

      3D transposed convolution over an input with several channels

      conv_general(input, weight, /[, stride, ...])

      conv_general(input, weight, /[, stride, ...])

      General convolution over an input with several channels

      cos(a, /, *[, stream])

      cos(a, /, *[, stream])

      Element-wise cosine.

      cosh(a, /, *[, stream])

      cosh(a, /, *[, stream])

      Element-wise hyperbolic cosine.

      cummax(a, /[, axis, reverse, inclusive, stream])

      cummax(a, /[, axis, reverse, inclusive, stream])

      Return the cumulative maximum of the elements along the given axis.

      cummin(a, /[, axis, reverse, inclusive, stream])

      cummin(a, /[, axis, reverse, inclusive, stream])

      Return the cumulative minimum of the elements along the given axis.

      cumprod(a, /[, axis, reverse, inclusive, stream])

      cumprod(a, /[, axis, reverse, inclusive, stream])

      Return the cumulative product of the elements along the given axis.

      cumsum(a, /[, axis, reverse, inclusive, stream])

      cumsum(a, /[, axis, reverse, inclusive, stream])

      Return the cumulative sum of the elements along the given axis.

      degrees(a, /, *[, stream])

      degrees(a, /, *[, stream])

      Convert angles from radians to degrees.

      dequantize(w, /, scales, biases[, ...])

      dequantize(w, /, scales, biases[, ...])

      Dequantize the matrix w using the provided scales and biases and the group_size and bits configuration.

      diag(a, /[, k, stream])

      diag(a, /[, k, stream])

      Extract a diagonal or construct a diagonal matrix.

      diagonal(a[, offset, axis1, axis2, stream])

      diagonal(a[, offset, axis1, axis2, stream])

      Return specified diagonals.

      divide(a, b[, stream])

      divide(a, b[, stream])

      Element-wise division.

      divmod(a, b[, stream])

      divmod(a, b[, stream])

      Element-wise quotient and remainder.

      einsum(subscripts, *operands[, stream])

      einsum(subscripts, *operands[, stream])

      Perform the Einstein summation convention on the operands.

      einsum_path(subscripts, *operands)

      einsum_path(subscripts, *operands)

      Compute the contraction order for the given Einstein summation.

      equal(a, b[, stream])

      equal(a, b[, stream])

      Element-wise equality.

      erf(a, /, *[, stream])

      erf(a, /, *[, stream])

      Element-wise error function.

      erfinv(a, /, *[, stream])

      erfinv(a, /, *[, stream])

      Element-wise inverse of erf().

      exp(a, /, *[, stream])

      exp(a, /, *[, stream])

      Element-wise exponential.

      expm1(a, /, *[, stream])

      expm1(a, /, *[, stream])

      Element-wise exponential minus 1.

      expand_dims(a, /, axis, *[, stream])

      expand_dims(a, /, axis, *[, stream])

      Add a size one dimension at the given axis.

      eye(n[, m, k, dtype, stream])

      eye(n[, m, k, dtype, stream])

      Create an identity matrix or a general diagonal matrix.

      flatten(a, /[, start_axis, end_axis, stream])

      flatten(a, /[, start_axis, end_axis, stream])

      Flatten an array.

      floor(a, /, *[, stream])

      floor(a, /, *[, stream])

      Element-wise floor.

      floor_divide(a, b[, stream])

      floor_divide(a, b[, stream])

      Element-wise integer division.

      full(shape, vals[, dtype, stream])

      full(shape, vals[, dtype, stream])

      Construct an array with the given value.

      gather_mm(a, b, /, lhs_indices, rhs_indices, *)

      gather_mm(a, b, /, lhs_indices, rhs_indices, *)

      Matrix multiplication with matrix-level gather.

      gather_qmm(x, w, /, scales, biases[, ...])

      gather_qmm(x, w, /, scales, biases[, ...])

      Perform quantized matrix multiplication with matrix-level gather.

      greater(a, b[, stream])

      greater(a, b[, stream])

      Element-wise greater than.

      greater_equal(a, b[, stream])

      greater_equal(a, b[, stream])

      Element-wise greater or equal.

      hadamard_transform(a[, scale, stream])

      hadamard_transform(a[, scale, stream])

      Perform the Walsh-Hadamard transform along the final axis.

      identity(n[, dtype, stream])

      identity(n[, dtype, stream])

      Create a square identity matrix.

      imag(a, /, *[, stream])

      imag(a, /, *[, stream])

      Returns the imaginary part of a complex array.

      inner(a, b, /, *[, stream])

      inner(a, b, /, *[, stream])

      Ordinary inner product of vectors for 1-D arrays, in higher dimensions a sum product over the last axes.

      isfinite(a[, stream])

      isfinite(a[, stream])

      Return a boolean array indicating which elements are finite.

      isclose(a, b, /[, rtol, atol, equal_nan, stream])

      isclose(a, b, /[, rtol, atol, equal_nan, stream])

      Returns a boolean array where two arrays are element-wise equal within a tolerance.

      isinf(a[, stream])

      isinf(a[, stream])

      Return a boolean array indicating which elements are +/- inifnity.

      isnan(a[, stream])

      isnan(a[, stream])

      Return a boolean array indicating which elements are NaN.

      isneginf(a[, stream])

      isneginf(a[, stream])

      Return a boolean array indicating which elements are negative infinity.

      isposinf(a[, stream])

      isposinf(a[, stream])

      Return a boolean array indicating which elements are positive infinity.

      issubdtype(arg1, arg2)

      issubdtype(arg1, arg2)

      Check if a Dtype or DtypeCategory is a subtype of another.

      kron(a, b, *[, stream])

      kron(a, b, *[, stream])

      Compute the Kronecker product of two arrays a and b.

      left_shift(a, b[, stream])

      left_shift(a, b[, stream])

      Element-wise left shift.

      less(a, b[, stream])

      less(a, b[, stream])

      Element-wise less than.

      less_equal(a, b[, stream])

      less_equal(a, b[, stream])

      Element-wise less than or equal.

      linspace(start, stop[, num, dtype, stream])

      linspace(start, stop[, num, dtype, stream])

      Generate num evenly spaced numbers over interval [start, stop].

      load(file, /[, format, return_metadata, stream])

      load(file, /[, format, return_metadata, stream])

      Load array(s) from a binary file.

      log(a, /, *[, stream])

      log(a, /, *[, stream])

      Element-wise natural logarithm.

      log2(a, /, *[, stream])

      log2(a, /, *[, stream])

      Element-wise base-2 logarithm.

      log10(a, /, *[, stream])

      log10(a, /, *[, stream])

      Element-wise base-10 logarithm.

      log1p(a, /, *[, stream])

      log1p(a, /, *[, stream])

      Element-wise natural log of one plus the array.

      logaddexp(a, b, /, *[, stream])

      logaddexp(a, b, /, *[, stream])

      Element-wise log-add-exp.

      logical_not(a, /, *[, stream])

      logical_not(a, /, *[, stream])

      Element-wise logical not.

      logical_and(a, b, /, *[, stream])

      logical_and(a, b, /, *[, stream])

      Element-wise logical and.

      logical_or(a, b, /, *[, stream])

      logical_or(a, b, /, *[, stream])

      Element-wise logical or.

      logsumexp(a, /[, axis, keepdims, stream])

      logsumexp(a, /[, axis, keepdims, stream])

      A log-sum-exp reduction over the given axes.

      matmul(a, b, /, *[, stream])

      matmul(a, b, /, *[, stream])

      Matrix multiplication.

      max(a, /[, axis, keepdims, stream])

      max(a, /[, axis, keepdims, stream])

      A max reduction over the given axes.

      maximum(a, b, /, *[, stream])

      maximum(a, b, /, *[, stream])

      Element-wise maximum.

      mean(a, /[, axis, keepdims, stream])

      mean(a, /[, axis, keepdims, stream])

      Compute the mean(s) over the given axes.

      meshgrid(*arrays[, sparse, indexing, stream])

      meshgrid(*arrays[, sparse, indexing, stream])

      Generate multidimensional coordinate grids from 1-D coordinate arrays

      min(a, /[, axis, keepdims, stream])

      min(a, /[, axis, keepdims, stream])

      A min reduction over the given axes.

      minimum(a, b, /, *[, stream])

      minimum(a, b, /, *[, stream])

      Element-wise minimum.

      moveaxis(a, /, source, destination, *[, stream])

      moveaxis(a, /, source, destination, *[, stream])

      Move an axis to a new position.

      multiply(a, b[, stream])

      multiply(a, b[, stream])

      Element-wise multiplication.

      nan_to_num(a[, nan, posinf, neginf, stream])

      nan_to_num(a[, nan, posinf, neginf, stream])

      Replace NaN and Inf values with finite numbers.

      negative(a, /, *[, stream])

      negative(a, /, *[, stream])

      Element-wise negation.

      not_equal(a, b[, stream])

      not_equal(a, b[, stream])

      Element-wise not equal.

      ones(shape[, dtype, stream])

      ones(shape[, dtype, stream])

      Construct an array of ones.

      ones_like(a, /, *[, stream])

      ones_like(a, /, *[, stream])

      An array of ones like the input.

      outer(a, b, /, *[, stream])

      outer(a, b, /, *[, stream])

      Compute the outer product of two 1-D arrays, if the array's passed are not 1-D a flatten op will be run beforehand.

      partition(a, /, kth[, axis, stream])

      partition(a, /, kth[, axis, stream])

      Returns a partitioned copy of the array such that the smaller kth elements are first.

      pad(a, pad_width[, mode, constant_values, ...])

      pad(a, pad_width[, mode, constant_values, ...])

      Pad an array with a constant value

      power(a, b, /, *[, stream])

      power(a, b, /, *[, stream])

      Element-wise power operation.

      prod(a, /[, axis, keepdims, stream])

      prod(a, /[, axis, keepdims, stream])

      An product reduction over the given axes.

      put_along_axis(a, /, indices, values[, ...])

      put_along_axis(a, /, indices, values[, ...])

      Put values along an axis at the specified indices.

      quantize(w, /[, group_size, bits, stream])

      quantize(w, /[, group_size, bits, stream])

      Quantize the matrix w using bits bits per element.

      quantized_matmul(x, w, /, scales, biases[, ...])

      quantized_matmul(x, w, /, scales, biases[, ...])

      Perform the matrix multiplication with the quantized matrix w.

      radians(a, /, *[, stream])

      radians(a, /, *[, stream])

      Convert angles from degrees to radians.

      real(a, /, *[, stream])

      real(a, /, *[, stream])

      Returns the real part of a complex array.

      reciprocal(a, /, *[, stream])

      reciprocal(a, /, *[, stream])

      Element-wise reciprocal.

      remainder(a, b[, stream])

      remainder(a, b[, stream])

      Element-wise remainder of division.

      repeat(array, repeats[, axis, stream])

      repeat(array, repeats[, axis, stream])

      Repeat an array along a specified axis.

      reshape(a, /, shape, *[, stream])

      reshape(a, /, shape, *[, stream])

      Reshape an array while preserving the size.

      right_shift(a, b[, stream])

      right_shift(a, b[, stream])

      Element-wise right shift.

      roll(a, shift[, axis, stream])

      roll(a, shift[, axis, stream])

      Roll array elements along a given axis.

      round(a, /[, decimals, stream])

      round(a, /[, decimals, stream])

      Round to the given number of decimals.

      rsqrt(a, /, *[, stream])

      rsqrt(a, /, *[, stream])

      Element-wise reciprocal and square root.

      save(file, arr)

      save(file, arr)

      Save the array to a binary file in .npy format.

      savez(file, *args, **kwargs)

      savez(file, *args, **kwargs)

      Save several arrays to a binary file in uncompressed .npz format.

      savez_compressed(file, *args, **kwargs)

      savez_compressed(file, *args, **kwargs)

      Save several arrays to a binary file in compressed .npz format.

      save_gguf(file, arrays, metadata)

      save_gguf(file, arrays, metadata)

      Save array(s) to a binary file in .gguf format.

      save_safetensors(file, arrays[, metadata])

      save_safetensors(file, arrays[, metadata])

      Save array(s) to a binary file in .safetensors format.

      sigmoid(a, /, *[, stream])

      sigmoid(a, /, *[, stream])

      Element-wise logistic sigmoid.

      sign(a, /, *[, stream])

      sign(a, /, *[, stream])

      Element-wise sign.

      sin(a, /, *[, stream])

      sin(a, /, *[, stream])

      Element-wise sine.

      sinh(a, /, *[, stream])

      sinh(a, /, *[, stream])

      Element-wise hyperbolic sine.

      slice(a, start_indices, axes, slice_size, *)

      slice(a, start_indices, axes, slice_size, *)

      Extract a sub-array from the input array.

      slice_update(a, update, start_indices, axes, *)

      slice_update(a, update, start_indices, axes, *)

      Update a sub-array of the input array.

      softmax(a, /[, axis, stream])

      softmax(a, /[, axis, stream])

      Perform the softmax along the given axis.

      sort(a, /[, axis, stream])

      sort(a, /[, axis, stream])

      Returns a sorted copy of the array.

      split(a, /, indices_or_sections[, axis, stream])

      split(a, /, indices_or_sections[, axis, stream])

      Split an array along a given axis.

      sqrt(a, /, *[, stream])

      sqrt(a, /, *[, stream])

      Element-wise square root.

      square(a, /, *[, stream])

      square(a, /, *[, stream])

      Element-wise square.

      squeeze(a, /[, axis, stream])

      squeeze(a, /[, axis, stream])

      Remove length one axes from an array.

      stack(arrays[, axis, stream])

      stack(arrays[, axis, stream])

      Stacks the arrays along a new axis.

      std(a, /[, axis, keepdims, ddof, stream])

      std(a, /[, axis, keepdims, ddof, stream])

      Compute the standard deviation(s) over the given axes.

      stop_gradient(a, /, *[, stream])

      stop_gradient(a, /, *[, stream])

      Stop gradients from being computed.

      subtract(a, b[, stream])

      subtract(a, b[, stream])

      Element-wise subtraction.

      sum(a, /[, axis, keepdims, stream])

      sum(a, /[, axis, keepdims, stream])

      Sum reduce the array over the given axes.

      swapaxes(a, /, axis1, axis2, *[, stream])

      swapaxes(a, /, axis1, axis2, *[, stream])

      Swap two axes of an array.

      take(a, /, indices[, axis, stream])

      take(a, /, indices[, axis, stream])

      Take elements along an axis.

      take_along_axis(a, /, indices[, axis, stream])

      take_along_axis(a, /, indices[, axis, stream])

      Take values along an axis at the specified indices.

      tan(a, /, *[, stream])

      tan(a, /, *[, stream])

      Element-wise tangent.

      tanh(a, /, *[, stream])

      tanh(a, /, *[, stream])

      Element-wise hyperbolic tangent.

      tensordot(a, b, /[, axes, stream])

      tensordot(a, b, /[, axes, stream])

      Compute the tensor dot product along the specified axes.

      tile(a, reps, /, *[, stream])

      tile(a, reps, /, *[, stream])

      Construct an array by repeating a the number of times given by reps.

      topk(a, /, k[, axis, stream])

      topk(a, /, k[, axis, stream])

      Returns the k largest elements from the input along a given axis.

      trace(a, /[, offset, axis1, axis2, dtype, ...])

      trace(a, /[, offset, axis1, axis2, dtype, ...])

      Return the sum along a specified diagonal in the given array.

      transpose(a, /[, axes, stream])

      transpose(a, /[, axes, stream])

      Transpose the dimensions of the array.

      tri(n, m, k[, dtype, stream])

      tri(n, m, k[, dtype, stream])

      An array with ones at and below the given diagonal and zeros elsewhere.

      tril(x, k, *[, stream])

      tril(x, k, *[, stream])

      Zeros the array above the given diagonal.

      triu(x, k, *[, stream])

      triu(x, k, *[, stream])

      Zeros the array below the given diagonal.

      unflatten(a, /, axis, shape, *[, stream])

      unflatten(a, /, axis, shape, *[, stream])

      Unflatten an axis of an array to a shape.

      var(a, /[, axis, keepdims, ddof, stream])

      var(a, /[, axis, keepdims, ddof, stream])

      Compute the variance(s) over the given axes.

      view(a, dtype[, stream])

      view(a, dtype[, stream])

      View the array as a different type.

      where(condition, x, y, /, *[, stream])

      where(condition, x, y, /, *[, stream])

      Select from x or y according to condition.

      zeros(shape[, dtype, stream])

      zeros(shape[, dtype, stream])

      Construct an array of zeros.

      zeros_like(a, /, *[, stream])

      zeros_like(a, /, *[, stream])

      An array of zeros like the input.
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      + +

      This is the complete list of members for BitwiseInvert, including all inherited members.

      + + +
      operator()(T x)BitwiseInvertinline
      +
      + + + + diff --git a/docs/build/html/struct_bitwise_invert.html b/docs/build/html/struct_bitwise_invert.html new file mode 100644 index 000000000..12c20a3cf --- /dev/null +++ b/docs/build/html/struct_bitwise_invert.html @@ -0,0 +1,161 @@ + + + + + + + +MLX: BitwiseInvert Struct Reference + + + + + + + + + + + + + + + + +
      +
      + + + + + + + +
      +
      MLX +
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      +Public Member Functions | +List of all members
      +
      BitwiseInvert Struct Reference
      +
      +
      + +

      #include <unary_ops.h>

      + + + + + +

      +Public Member Functions

      template<typename T>
      T operator() (T x)
       
      +

      Member Function Documentation

      + +

      ◆ operator()()

      + +
      +
      +
      +template<typename T>
      + + + + + +
      + + + + + + + +
      T BitwiseInvert::operator() (T x)
      +       		+inline
      +
      + +
      +
      +
      The documentation for this struct was generated from the following file: +
      +
      + + + + diff --git a/docs/build/html/struct_bitwise_invert.js b/docs/build/html/struct_bitwise_invert.js new file mode 100644 index 000000000..c0e4363d8 --- /dev/null +++ b/docs/build/html/struct_bitwise_invert.js @@ -0,0 +1,4 @@ +var struct_bitwise_invert = +[ + [ "operator()", "struct_bitwise_invert.html#a8f0c83f39bbb475368494568acdb794c", null ] +]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1core_1_1_command_encoder-members.html b/docs/build/html/structmlx_1_1core_1_1_command_encoder-members.html index a4936acd7..47bd0cae3 100644 --- a/docs/build/html/structmlx_1_1core_1_1_command_encoder-members.html +++ b/docs/build/html/structmlx_1_1core_1_1_command_encoder-members.html @@ -109,7 +109,7 @@ $(function(){initNavTree('structmlx_1_1core_1_1_command_encoder.html',''); initR

      This is the complete list of members for mlx::core::CommandEncoder, including all inherited members.

      - + diff --git a/docs/build/html/structmlx_1_1core_1_1_command_encoder.html b/docs/build/html/structmlx_1_1core_1_1_command_encoder.html index a867270c2..99d5e709c 100644 --- a/docs/build/html/structmlx_1_1core_1_1_command_encoder.html +++ b/docs/build/html/structmlx_1_1core_1_1_command_encoder.html @@ -119,8 +119,8 @@ Classes
      barrier()mlx::core::CommandEncoder
      CommandEncoder(MTL::CommandBuffer *cbuf)mlx::core::CommandEncoder
      CommandEncoder(DeviceStream &stream)mlx::core::CommandEncoderexplicit
      CommandEncoder(const CommandEncoder &)=deletemlx::core::CommandEncoder
      dispatch_threadgroups(MTL::Size grid_dims, MTL::Size group_dims)mlx::core::CommandEncoder
      dispatch_threads(MTL::Size grid_dims, MTL::Size group_dims)mlx::core::CommandEncoder
      - - + + @@ -169,19 +169,27 @@ Public Member Functions

      Public Member Functions

       CommandEncoder (MTL::CommandBuffer *cbuf)
       
       CommandEncoder (DeviceStream &stream)
       
       CommandEncoder (const CommandEncoder &)=delete
       
      CommandEncoder & operator= (const CommandEncoder &)=delete
       

      Constructor & Destructor Documentation

      - -

      ◆ CommandEncoder() [1/2]

      + +

      ◆ CommandEncoder() [1/2]

      + + + + + +
      - +
      mlx::core::metal::CommandEncoder::CommandEncoder (MTL::CommandBuffer * cbuf)DeviceStream & stream)
      +       		+explicit
      diff --git a/docs/build/html/structmlx_1_1core_1_1_command_encoder.js b/docs/build/html/structmlx_1_1core_1_1_command_encoder.js index 8f9dc2674..a9eec42dc 100644 --- a/docs/build/html/structmlx_1_1core_1_1_command_encoder.js +++ b/docs/build/html/structmlx_1_1core_1_1_command_encoder.js @@ -1,7 +1,7 @@ var structmlx_1_1core_1_1_command_encoder = [ [ "ConcurrentContext", "structmlx_1_1core_1_1_command_encoder_1_1_concurrent_context.html", "structmlx_1_1core_1_1_command_encoder_1_1_concurrent_context" ], - [ "CommandEncoder", "structmlx_1_1core_1_1_command_encoder.html#a2334774486f447213ee997e55c2e52a3", null ], + [ "CommandEncoder", "structmlx_1_1core_1_1_command_encoder.html#a7320b3acfa075ffdce5ea38fe107f186", null ], [ "CommandEncoder", "structmlx_1_1core_1_1_command_encoder.html#ac68ca977b5bde5434284ce7979647f14", null ], [ "~CommandEncoder", "structmlx_1_1core_1_1_command_encoder.html#a9b6dd221ccd2d939d544004cb6279198", null ], [ "barrier", "structmlx_1_1core_1_1_command_encoder.html#a7f028c6ca48e75bf2c1806b5b8cfc90e", null ], diff --git a/docs/build/html/structmlx_1_1core_1_1_dtype.html b/docs/build/html/structmlx_1_1core_1_1_dtype.html index 61ddd163d..7ff503765 100644 --- a/docs/build/html/structmlx_1_1core_1_1_dtype.html +++ b/docs/build/html/structmlx_1_1core_1_1_dtype.html @@ -128,9 +128,10 @@ Public Types   int64 , float16 , float32 -, bfloat16 +, float64 ,
      -  complex64 +  bfloat16 +, complex64
      }   @@ -264,6 +265,7 @@ Public Member Functions int64  float16  float32  +float64  bfloat16  complex64  diff --git a/docs/build/html/structmlx_1_1core_1_1_dtype.js b/docs/build/html/structmlx_1_1core_1_1_dtype.js index c37565b2b..e45189984 100644 --- a/docs/build/html/structmlx_1_1core_1_1_dtype.js +++ b/docs/build/html/structmlx_1_1core_1_1_dtype.js @@ -30,6 +30,7 @@ var structmlx_1_1core_1_1_dtype = [ "int64", "structmlx_1_1core_1_1_dtype.html#ade845ef5dcebead13a37fe696436e1daaff9b3f96d37353c528517bc3656a00a8", null ], [ "float16", "structmlx_1_1core_1_1_dtype.html#ade845ef5dcebead13a37fe696436e1daa098e7844282e240fdee28a9dac11c1c6", null ], [ "float32", "structmlx_1_1core_1_1_dtype.html#ade845ef5dcebead13a37fe696436e1daad33ec2b0bbea6d471a4706cea030e1e3", null ], + [ "float64", "structmlx_1_1core_1_1_dtype.html#ade845ef5dcebead13a37fe696436e1daafb7fa22ede616c04c68a7663d0f81e92", null ], [ "bfloat16", "structmlx_1_1core_1_1_dtype.html#ade845ef5dcebead13a37fe696436e1daa444fe01f3a7a54d1809aef0912846a47", null ], [ "complex64", "structmlx_1_1core_1_1_dtype.html#ade845ef5dcebead13a37fe696436e1daa8c022579455bcd2c681f007e84f4e2cf", null ] ] ], diff --git a/docs/build/html/structmlx_1_1core_1_1_print_formatter-members.html b/docs/build/html/structmlx_1_1core_1_1_print_formatter-members.html index 54a975529..561b34415 100644 --- a/docs/build/html/structmlx_1_1core_1_1_print_formatter-members.html +++ b/docs/build/html/structmlx_1_1core_1_1_print_formatter-members.html @@ -119,7 +119,8 @@ $(function(){initNavTree('structmlx_1_1core_1_1_print_formatter.html',''); initR print(std::ostream &os, float16_t val)mlx::core::PrintFormatterinline print(std::ostream &os, bfloat16_t val)mlx::core::PrintFormatterinline print(std::ostream &os, float val)mlx::core::PrintFormatterinline - print(std::ostream &os, complex64_t val)mlx::core::PrintFormatterinline + print(std::ostream &os, double val)mlx::core::PrintFormatterinline + print(std::ostream &os, complex64_t val)mlx::core::PrintFormatterinline
      diff --git a/docs/build/html/structmlx_1_1core_1_1_print_formatter.html b/docs/build/html/structmlx_1_1core_1_1_print_formatter.html index a9717d72e..7efa7ea3d 100644 --- a/docs/build/html/structmlx_1_1core_1_1_print_formatter.html +++ b/docs/build/html/structmlx_1_1core_1_1_print_formatter.html @@ -134,6 +134,8 @@ Public Member Functions   void print (std::ostream &os, float val)   +void print (std::ostream &os, double val) +  void print (std::ostream &os, complex64_t val)   @@ -144,7 +146,7 @@ Public Attributes

      Member Function Documentation

      -

      ◆ print() [1/11]

      +

      ◆ print() [1/12]

      @@ -173,7 +175,7 @@ Public Attributes
      -

      ◆ print() [2/11]

      +

      ◆ print() [2/12]

      @@ -202,7 +204,7 @@ Public Attributes
      -

      ◆ print() [3/11]

      +

      ◆ print() [3/12]

      @@ -228,10 +230,39 @@ Public Attributes
      +
      +
      + +

      ◆ print() [4/12]

      + +
      +
      + + + + + +
      + + + + + + + + + + + +
      void mlx::core::PrintFormatter::print (std::ostream & os,
      double val )
      +       		+inline
      +
      +
      -

      ◆ print() [4/11]

      +

      ◆ print() [5/12]

      @@ -260,7 +291,7 @@ Public Attributes
      -

      ◆ print() [5/11]

      +

      ◆ print() [6/12]

      @@ -289,7 +320,7 @@ Public Attributes
      -

      ◆ print() [6/11]

      +

      ◆ print() [7/12]

      @@ -318,7 +349,7 @@ Public Attributes
      -

      ◆ print() [7/11]

      +

      ◆ print() [8/12]

      @@ -347,7 +378,7 @@ Public Attributes
      -

      ◆ print() [8/11]

      +

      ◆ print() [9/12]

      @@ -376,7 +407,7 @@ Public Attributes
      -

      ◆ print() [9/11]

      +

      ◆ print() [10/12]

      @@ -405,7 +436,7 @@ Public Attributes
      -

      ◆ print() [10/11]

      +

      ◆ print() [11/12]

      @@ -434,7 +465,7 @@ Public Attributes
      -

      ◆ print() [11/11]

      +

      ◆ print() [12/12]

      diff --git a/docs/build/html/structmlx_1_1core_1_1_print_formatter.js b/docs/build/html/structmlx_1_1core_1_1_print_formatter.js index dac3b00b3..6500d5ebc 100644 --- a/docs/build/html/structmlx_1_1core_1_1_print_formatter.js +++ b/docs/build/html/structmlx_1_1core_1_1_print_formatter.js @@ -3,6 +3,7 @@ var structmlx_1_1core_1_1_print_formatter = [ "print", "structmlx_1_1core_1_1_print_formatter.html#ae21005f92bc641f2d657096f5d176a6d", null ], [ "print", "structmlx_1_1core_1_1_print_formatter.html#a79fad4cf5844db8c92b066539146281b", null ], [ "print", "structmlx_1_1core_1_1_print_formatter.html#a9e1dc67c9afb0a09966336504790823d", null ], + [ "print", "structmlx_1_1core_1_1_print_formatter.html#a8287664c29d09f5eff3a0ba87e2c49fb", null ], [ "print", "structmlx_1_1core_1_1_print_formatter.html#a57af5c32561b95d6ac2a3a1dc4f5d43e", null ], [ "print", "structmlx_1_1core_1_1_print_formatter.html#ac4b7895d1168cfc1a3d1186d8a414d2f", null ], [ "print", "structmlx_1_1core_1_1_print_formatter.html#a8da448a8adae671b26359341ea514316", null ], diff --git a/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert-members.html b/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert-members.html new file mode 100644 index 000000000..bd7f7c0e9 --- /dev/null +++ b/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert-members.html @@ -0,0 +1,122 @@ + + + + + + + +MLX: Member List + + + + + + + + + + + + + + + + +
      +
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      MLX +
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      mlx::core::detail::BitwiseInvert Member List
      +
      +
      + +

      This is the complete list of members for mlx::core::detail::BitwiseInvert, including all inherited members.

      + + + +
      operator()(Simd< T, N > x)mlx::core::detail::BitwiseInvertinline
      operator()(T x)mlx::core::detail::BitwiseInvertinline
      +
      + + + + diff --git a/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert.html b/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert.html new file mode 100644 index 000000000..d11ef97e5 --- /dev/null +++ b/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert.html @@ -0,0 +1,191 @@ + + + + + + + +MLX: mlx::core::detail::BitwiseInvert Struct Reference + + + + + + + + + + + + + + + + +
      +
      + + + + + + + +
      +
      MLX +
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      +Public Member Functions | +List of all members
      +
      mlx::core::detail::BitwiseInvert Struct Reference
      +
      +
      + +

      #include <unary_ops.h>

      + + + + + + + + +

      +Public Member Functions

      template<int N, typename T>
      Simd< T, N > operator() (Simd< T, N > x)
       
      template<typename T>
      T operator() (T x)
       
      +

      Member Function Documentation

      + +

      ◆ operator()() [1/2]

      + +
      +
      +
      +template<int N, typename T>
      + + + + + +
      + + + + + + + +
      Simd< T, N > mlx::core::detail::BitwiseInvert::operator() (Simd< T, N > x)
      +       		+inline
      +
      + +
      +
      + +

      ◆ operator()() [2/2]

      + +
      +
      +
      +template<typename T>
      + + + + + +
      + + + + + + + +
      T mlx::core::detail::BitwiseInvert::operator() (T x)
      +       		+inline
      +
      + +
      +
      +
      The documentation for this struct was generated from the following file: +
      +
      + + + + diff --git a/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert.js b/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert.js new file mode 100644 index 000000000..70f9344ec --- /dev/null +++ b/docs/build/html/structmlx_1_1core_1_1detail_1_1_bitwise_invert.js @@ -0,0 +1,5 @@ +var structmlx_1_1core_1_1detail_1_1_bitwise_invert = +[ + [ "operator()", "structmlx_1_1core_1_1detail_1_1_bitwise_invert.html#a82a68523f66008c83dc6ebea184b5fe4", null ], + [ "operator()", "structmlx_1_1core_1_1detail_1_1_bitwise_invert.html#ad6cdfbd47f1fb2d8c251ce0da92c22c6", null ] +]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1core_1_1finfo-members.html b/docs/build/html/structmlx_1_1core_1_1finfo-members.html index 2eb09279f..5843f9cf5 100644 --- a/docs/build/html/structmlx_1_1core_1_1finfo-members.html +++ b/docs/build/html/structmlx_1_1core_1_1finfo-members.html @@ -110,8 +110,8 @@ $(function(){initNavTree('structmlx_1_1core_1_1finfo.html',''); initResizable(tr - - + +
      dtypemlx::core::finfo
      finfo(Dtype dtype)mlx::core::finfoexplicit
      maxmlx::core::finfo
      minmlx::core::finfo
      maxmlx::core::finfo
      minmlx::core::finfo
      diff --git a/docs/build/html/structmlx_1_1core_1_1finfo.html b/docs/build/html/structmlx_1_1core_1_1finfo.html index ebfa3017f..3fe44781f 100644 --- a/docs/build/html/structmlx_1_1core_1_1finfo.html +++ b/docs/build/html/structmlx_1_1core_1_1finfo.html @@ -124,10 +124,10 @@ Public Member Functions Public Attributes Dtype dtype   -float min -  -float max -  +double min +  +double max + 

      Detailed Description

      Holds information about floating-point types.

      @@ -172,28 +172,28 @@ Public Attributes
      - -

      ◆ max

      + +

      ◆ max

      - +
      float mlx::core::finfo::maxdouble mlx::core::finfo::max
      - -

      ◆ min

      + +

      ◆ min

      - +
      float mlx::core::finfo::mindouble mlx::core::finfo::min
      diff --git a/docs/build/html/structmlx_1_1core_1_1finfo.js b/docs/build/html/structmlx_1_1core_1_1finfo.js index 289a8869b..d1b5df28c 100644 --- a/docs/build/html/structmlx_1_1core_1_1finfo.js +++ b/docs/build/html/structmlx_1_1core_1_1finfo.js @@ -2,6 +2,6 @@ var structmlx_1_1core_1_1finfo = [ [ "finfo", "structmlx_1_1core_1_1finfo.html#a00dee158d75d12768d02a3e7b6709109", null ], [ "dtype", "structmlx_1_1core_1_1finfo.html#a4edcbcfae55c1ef3cb8e61d427ac9124", null ], - [ "max", "structmlx_1_1core_1_1finfo.html#a9975908d99d25e9225d0c70bead0abc2", null ], - [ "min", "structmlx_1_1core_1_1finfo.html#a91332dcbb502799b6cc8e1c6933c042b", null ] + [ "max", "structmlx_1_1core_1_1finfo.html#a976ada682716f9531dfccddcf0ab3083", null ], + [ "min", "structmlx_1_1core_1_1finfo.html#a0606e7a2d4c9a5fd6ea8e0eab5445c4a", null ] ]; \ No newline at end of file diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder-members.html b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder-members.html index 9f0ecdbde..83ec674e6 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder-members.html +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder-members.html @@ -109,7 +109,7 @@ $(function(){initNavTree('structmlx_1_1core_1_1metal_1_1_command_encoder.html','

      This is the complete list of members for mlx::core::metal::CommandEncoder, including all inherited members.

      - + diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.html b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.html index 64b82ff7a..569cd530d 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.html +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.html @@ -119,8 +119,8 @@ Classes
      barrier()mlx::core::metal::CommandEncoder
      CommandEncoder(MTL::CommandBuffer *cbuf)mlx::core::metal::CommandEncoder
      CommandEncoder(DeviceStream &stream)mlx::core::metal::CommandEncoderexplicit
      CommandEncoder(const CommandEncoder &)=deletemlx::core::metal::CommandEncoder
      dispatch_threadgroups(MTL::Size grid_dims, MTL::Size group_dims)mlx::core::metal::CommandEncoder
      dispatch_threads(MTL::Size grid_dims, MTL::Size group_dims)mlx::core::metal::CommandEncoder
      - - + + @@ -169,19 +169,27 @@ Public Member Functions

      Public Member Functions

       CommandEncoder (MTL::CommandBuffer *cbuf)
       
       CommandEncoder (DeviceStream &stream)
       
       CommandEncoder (const CommandEncoder &)=delete
       
      CommandEncoder & operator= (const CommandEncoder &)=delete
       

      Constructor & Destructor Documentation

      - -

      ◆ CommandEncoder() [1/2]

      + +

      ◆ CommandEncoder() [1/2]

      + + + + + +
      - +
      mlx::core::metal::CommandEncoder::CommandEncoder (MTL::CommandBuffer * cbuf)DeviceStream & stream)
      +       		+explicit
      diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.js b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.js index 24bf4cf3c..f70a1b4ca 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.js +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_command_encoder.js @@ -1,7 +1,7 @@ var structmlx_1_1core_1_1metal_1_1_command_encoder = [ [ "ConcurrentContext", "structmlx_1_1core_1_1metal_1_1_command_encoder_1_1_concurrent_context.html", "structmlx_1_1core_1_1metal_1_1_command_encoder_1_1_concurrent_context" ], - [ "CommandEncoder", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#a2334774486f447213ee997e55c2e52a3", null ], + [ "CommandEncoder", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#a7320b3acfa075ffdce5ea38fe107f186", null ], [ "CommandEncoder", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#ac68ca977b5bde5434284ce7979647f14", null ], [ "~CommandEncoder", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#a9b6dd221ccd2d939d544004cb6279198", null ], [ "barrier", "structmlx_1_1core_1_1metal_1_1_command_encoder.html#a7f028c6ca48e75bf2c1806b5b8cfc90e", null ], diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream-members.html b/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream-members.html index 2deed1fa6..8affbbb71 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream-members.html +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream-members.html @@ -110,14 +110,15 @@ $(function(){initNavTree('structmlx_1_1core_1_1metal_1_1_device_stream.html','') - - - - - - - - + + + + + + + + +
      buffermlx::core::metal::DeviceStream
      buffer_opsmlx::core::metal::DeviceStream
      DeviceStream(MTL::CommandQueue *queue)mlx::core::metal::DeviceStreaminline
      encodermlx::core::metal::DeviceStream
      fencemlx::core::metal::DeviceStream
      fence_mtxmlx::core::metal::DeviceStream
      outputsmlx::core::metal::DeviceStream
      queuemlx::core::metal::DeviceStream
      temporariesmlx::core::metal::DeviceStream
      ~DeviceStream()mlx::core::metal::DeviceStreaminline
      buffer_sizesmlx::core::metal::DeviceStream
      DeviceStream(MTL::CommandQueue *queue)mlx::core::metal::DeviceStreaminline
      encodermlx::core::metal::DeviceStream
      fencemlx::core::metal::DeviceStream
      fence_mtxmlx::core::metal::DeviceStream
      outputsmlx::core::metal::DeviceStream
      queuemlx::core::metal::DeviceStream
      temporariesmlx::core::metal::DeviceStream
      ~DeviceStream()mlx::core::metal::DeviceStreaminline
      diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream.html b/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream.html index e53022ec3..25b903138 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream.html +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream.html @@ -131,6 +131,8 @@ Public Attributes   int buffer_ops {0}   +size_t buffer_sizes {0} +  std::unique_ptr< CommandEncoder > encoder {nullptr}   std::shared_ptr< Fence > fence @@ -216,6 +218,20 @@ Public Attributes
      +
      + + +

      ◆ buffer_sizes

      + +
      +
      + + + + +
      size_t mlx::core::metal::DeviceStream::buffer_sizes {0}
      +
      +
      diff --git a/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream.js b/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream.js index 4186507ee..401dbf9d8 100644 --- a/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream.js +++ b/docs/build/html/structmlx_1_1core_1_1metal_1_1_device_stream.js @@ -4,6 +4,7 @@ var structmlx_1_1core_1_1metal_1_1_device_stream = [ "~DeviceStream", "structmlx_1_1core_1_1metal_1_1_device_stream.html#a1c4397732f64f5811381dd01e30e020e", null ], [ "buffer", "structmlx_1_1core_1_1metal_1_1_device_stream.html#a99183c92599edfeb75f7fa0f37e1d9eb", null ], [ "buffer_ops", "structmlx_1_1core_1_1metal_1_1_device_stream.html#ab6048b329e65a59033834f3bdd351782", null ], + [ "buffer_sizes", "structmlx_1_1core_1_1metal_1_1_device_stream.html#ae7054233303b06329c67177382ded459", null ], [ "encoder", "structmlx_1_1core_1_1metal_1_1_device_stream.html#a58e435217b9922f882507ebf48bfbbdd", null ], [ "fence", "structmlx_1_1core_1_1metal_1_1_device_stream.html#a876199de8da1efa9a362451029638499", null ], [ "fence_mtx", "structmlx_1_1core_1_1metal_1_1_device_stream.html#a6fa08cca881fc3798ae45994a11a4fcd", null ], diff --git a/docs/build/html/structmlx_1_1core_1_1numeric__limits_3_01double_01_4.html b/docs/build/html/structmlx_1_1core_1_1numeric__limits_3_01double_01_4.html new file mode 100644 index 000000000..a8f720afc --- /dev/null +++ b/docs/build/html/structmlx_1_1core_1_1numeric__limits_3_01double_01_4.html @@ -0,0 +1,129 @@ + + + + + + + +MLX: mlx::core::numeric_limits< double > Struct Reference + + + + + + + + + + + + + + + + +
      +
      + + + + + + + +
      +
      MLX +
      +
      + +   + + + + +
      +
      +
      + + + + +
      +
      + +
      +
      +
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      +
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      +
      Loading...
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      +
      + +
      +
      mlx::core::numeric_limits< double > Struct Reference
      +
      +
      + +

      #include <limits.h>

      +
      +Inheritance diagram for mlx::core::numeric_limits< double >:
      +
      +
      + +
      +
      The documentation for this struct was generated from the following file: +
      +
      + + + + diff --git a/docs/build/html/structmlx_1_1core_1_1numeric__limits_3_01double_01_4.png b/docs/build/html/structmlx_1_1core_1_1numeric__limits_3_01double_01_4.png new file mode 100644 index 0000000000000000000000000000000000000000..3e675b94307a888ee35c82f3ca27e4b17bfdc842 GIT binary patch literal 777 zcmeAS@N?(olHy`uVBq!ia0vp^7lAl{gBeI};7C{iq@)9ULR|m<{|{uoc=NTi|Il&^ z1I+@7>1SR%c<=xyZhAIs2~du+B*-tA0mugfbEer>7#NtQc)B=-R4~4sdvnrj1s<1Z z{mXy<$JgvlP!@Y!p>?uAbJ>edM$ST(7m{gd&YW(Om@|bYrre+9qH=TlyN*L|gx?%0 zll+hzIXxxE^nUwCdk2?EonFuFl{T5q{Jnq2qfa~Q*mH$%-$~oSpHp0YUH(+&ZoQ4` zy)JDRNdMj|crNaxbKX=`eoW)a>yH_t4obxsFRzkLrYWDGq zDmhZ;eB+;}9sO9XJx!14r%r7A+HY&CXJ-7Zb`jAlopwkpkfZSUl{Gw5pO~D}n7vQA zD`x%ti?-({mrrT;&8v8NP4s=omPMxbFBW#auX2BQZSGdR+f{aDS9W>D8X4t(-};%qu3etW(zSo0E30$!ge)5hA(S9Sr}@G652m`=FNa6&r1%oTqa%F zt~OES>)J^#{Ht8hc(x327esSDi&wgT%*D{w(Bi~iqYVvq*jaJ4=sRPg;|4 zw!CD{qsQe>x}ug|`}t_{w1zi)bH7dBs<&GIZB)5i#nx+{mjr%kUHmp}b?4M2=9%+A qUiMV+1O}I9(EX^6GiTf`*>Cy!N8t0UDbIk3mci52&t;ucLK6UE19=Ak literal 0 HcmV?d00001 diff --git a/docs/build/html/transforms_8h_source.html b/docs/build/html/transforms_8h_source.html index 634505ba3..b668571e9 100644 --- a/docs/build/html/transforms_8h_source.html +++ b/docs/build/html/transforms_8h_source.html @@ -284,7 +284,7 @@ $(function(){initNavTree('transforms_8h_source.html',''); initResizable(true); }
      mlx::core::ValueAndGradFn
      std::function< std::pair< std::vector< array >, std::vector< array > >( const std::vector< array > &)> ValueAndGradFn
      Definition transforms.h:68
      mlx::core::value_and_grad
      ValueAndGradFn value_and_grad(const std::function< std::vector< array >(const std::vector< array > &)> &fun, const std::vector< int > &argnums)
      Returns a function which computes the value and gradient of the input function with respect to a vect...
      mlx::core::vmap
      std::function< array(const array &)> vmap(const std::function< array(const array &)> &fun, int in_axis=0, int out_axis=0)
      Automatically vectorize a unary function over the requested axes.
      -
      mlx::core::enable_for_arrays_t
      typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
      Definition array.h:615
      +
      mlx::core::enable_for_arrays_t
      typename std::enable_if_t< is_arrays_v< T... > > enable_for_arrays_t
      Definition array.h:630
      diff --git a/docs/build/html/usage/compile.html b/docs/build/html/usage/compile.html index 393bd6ce9..3d1e854d2 100644 --- a/docs/build/html/usage/compile.html +++ b/docs/build/html/usage/compile.html @@ -8,7 +8,7 @@ - Compilation — MLX 0.22.1 documentation + Compilation — MLX 0.23.0 documentation @@ -39,7 +39,7 @@ - + @@ -51,7 +51,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.22.1 documentation - Home - MLX 0.22.1 documentation - Home + MLX 0.23.0 documentation - Home + MLX 0.23.0 documentation - Home @@ -276,6 +276,7 @@
    • mlx.core.atleast_2d
    • mlx.core.atleast_3d
    • mlx.core.bitwise_and
      • +
    • mlx.core.bitwise_invert
    • mlx.core.bitwise_or
    • mlx.core.bitwise_xor
    • mlx.core.block_masked_mm
      • @@ -486,6 +487,10 @@
    • mlx.core.linalg.svd
    • mlx.core.linalg.eigvalsh
    • mlx.core.linalg.eigh
      • +
    • mlx.core.linalg.lu
      • +
    • mlx.core.linalg.lu_factor
      • +
    • mlx.core.linalg.solve
      • +
    • mlx.core.linalg.solve_triangular
  • Metal
  • Metal
  • Metal
  • Metal
  • Metal
  • Metal
  • Metal
      @@ -901,11 +906,13 @@

      Note

      -

      Since NumPy does not support bfloat16 arrays, you will need to convert to float16 or float32 first: -np.array(a.astype(mx.float32)). -Otherwise, you will receive an error like: Item size 2 for PEP 3118 buffer format string does not match the dtype V item size 0.

      +

      Since NumPy does not support bfloat16 arrays, you will need to convert +to float16 or float32 first: np.array(a.astype(mx.float32)). +Otherwise, you will receive an error like: Item size 2 for PEP 3118 +buffer format string does not match the dtype V item size 0.

      -

      By default, NumPy copies data to a new array. This can be prevented by creating an array view:

      +

      By default, NumPy copies data to a new array. This can be prevented by creating +an array view:

      a = mx.arange(3)
 a_view = np.array(a, copy=False)
 print(a_view.flags.owndata) # False
@@ -913,9 +920,15 @@ Otherwise, you will receive an error like: print(a[0].item()) # 1
      -

      A NumPy array view is a normal NumPy array, except that it does not own its memory. -This means writing to the view is reflected in the original array.

      -

      While this is quite powerful to prevent copying arrays, it should be noted that external changes to the memory of arrays cannot be reflected in gradients.

      +
      +

      Note

      +

      NumPy arrays with type float64 will be default converted to MLX arrays +with type float32.

      +
      +

      A NumPy array view is a normal NumPy array, except that it does not own its +memory. This means writing to the view is reflected in the original array.

      +

      While this is quite powerful to prevent copying arrays, it should be noted that +external changes to the memory of arrays cannot be reflected in gradients.

      Let’s demonstrate this in an example:

      def f(x):
     x_view = np.array(x, copy=False)
@@ -929,11 +942,12 @@ This means writing to the view is reflected in the original array.

      The function f indirectly modifies the array x through a memory view. -However, this modification is not reflected in the gradient, as seen in the last line outputting 1.0, -representing the gradient of the sum operation alone. -The squaring of x occurs externally to MLX, meaning that no gradient is incorporated. -It’s important to note that a similar issue arises during array conversion and copying. -For instance, a function defined as mx.array(np.array(x)**2).sum() would also result in an incorrect gradient, +However, this modification is not reflected in the gradient, as seen in the +last line outputting 1.0, representing the gradient of the sum operation +alone. The squaring of x occurs externally to MLX, meaning that no +gradient is incorporated. It’s important to note that a similar issue arises +during array conversion and copying. For instance, a function defined as +mx.array(np.array(x)**2).sum() would also result in an incorrect gradient, even though no in-place operations on MLX memory are executed.

      PyTorch#

      @@ -942,7 +956,8 @@ even though no in-place operations on MLX memory are executed.

      PyTorch Support for memoryview is experimental and can break for multi-dimensional arrays. Casting to NumPy first is advised for now.

      -

      PyTorch supports the buffer protocol, but it requires an explicit memoryview.

      +

      PyTorch supports the buffer protocol, but it requires an explicit +memoryview.

      import mlx.core as mx
 import torch
 
@@ -951,7 +966,8 @@ multi-dimensional arrays. Casting to NumPy first is advised for now.
      
 c = mx.array(b.numpy())
      -

      Conversion from PyTorch tensors back to arrays must be done via intermediate NumPy arrays with numpy().

      +

      Conversion from PyTorch tensors back to arrays must be done via intermediate +NumPy arrays with numpy().

      JAX#

      @@ -967,7 +983,8 @@ multi-dimensional arrays. Casting to NumPy first is advised for now.

      TensorFlow#

      -

      TensorFlow supports the buffer protocol, but it requires an explicit memoryview.

      +

      TensorFlow supports the buffer protocol, but it requires an explicit +memoryview.

      import mlx.core as mx
 import tensorflow as tf
 
diff --git a/docs/build/html/usage/quick_start.html b/docs/build/html/usage/quick_start.html
index 7990f3c79..cec9f0f6f 100644
--- a/docs/build/html/usage/quick_start.html
+++ b/docs/build/html/usage/quick_start.html
@@ -8,7 +8,7 @@
     
     
 
-    Quick Start Guide — MLX 0.22.1 documentation
+    Quick Start Guide — MLX 0.23.0 documentation
   
   
   
@@ -39,7 +39,7 @@
   
 
 
-    
+    
     
     
     
@@ -51,7 +51,7 @@
     
   
   
-  
+  
   
   
   
@@ -130,8 +130,8 @@
       
     
     
-    MLX 0.22.1 documentation - Home
-    MLX 0.22.1 documentation - Home
+    MLX 0.23.0 documentation - Home
+    MLX 0.23.0 documentation - Home
      @@ -276,6 +276,7 @@
    • mlx.core.atleast_2d
    • mlx.core.atleast_3d
    • mlx.core.bitwise_and
      • +
    • mlx.core.bitwise_invert
    • mlx.core.bitwise_or
    • mlx.core.bitwise_xor
    • mlx.core.block_masked_mm
      • @@ -486,6 +487,10 @@
    • mlx.core.linalg.svd
    • mlx.core.linalg.eigvalsh
    • mlx.core.linalg.eigh
      • +
    • mlx.core.linalg.lu
      • +
    • mlx.core.linalg.lu_factor
      • +
    • mlx.core.linalg.solve
      • +
    • mlx.core.linalg.solve_triangular
  • Metal
  • Metal
  • Metal
  • Metal