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+- .../mlx.nn.Module.parameters.html | 10 +- .../mlx.nn.Module.save_weights.html | 12 +- .../_autosummary/mlx.nn.Module.set_dtype.html | 12 +- .../nn/_autosummary/mlx.nn.Module.state.html | 10 +- .../nn/_autosummary/mlx.nn.Module.train.html | 14 +- .../mlx.nn.Module.trainable_parameters.html | 10 +- .../_autosummary/mlx.nn.Module.training.html | 10 +- .../_autosummary/mlx.nn.Module.unfreeze.html | 18 +- .../nn/_autosummary/mlx.nn.Module.update.html | 14 +- .../mlx.nn.Module.update_modules.html | 14 +- .../mlx.nn.MultiHeadAttention.html | 28 +- .../python/nn/_autosummary/mlx.nn.PReLU.html | 10 +- .../mlx.nn.QuantizedEmbedding.html | 20 +- .../_autosummary/mlx.nn.QuantizedLinear.html | 22 +- .../nn/_autosummary/mlx.nn.RMSNorm.html | 16 +- .../python/nn/_autosummary/mlx.nn.RNN.html | 18 +- .../python/nn/_autosummary/mlx.nn.ReLU.html | 10 +- .../python/nn/_autosummary/mlx.nn.ReLU6.html | 10 +- .../python/nn/_autosummary/mlx.nn.RoPE.html | 20 +- .../python/nn/_autosummary/mlx.nn.SELU.html | 10 +- .../nn/_autosummary/mlx.nn.Sequential.html | 12 +- .../python/nn/_autosummary/mlx.nn.SiLU.html | 10 +- .../nn/_autosummary/mlx.nn.Sigmoid.html | 10 +- .../mlx.nn.SinusoidalPositionalEncoding.html | 24 +- .../nn/_autosummary/mlx.nn.Softmax.html | 10 +- .../nn/_autosummary/mlx.nn.Softmin.html | 10 +- .../nn/_autosummary/mlx.nn.Softplus.html | 10 +- .../nn/_autosummary/mlx.nn.Softshrink.html | 10 +- .../nn/_autosummary/mlx.nn.Softsign.html | 10 +- .../python/nn/_autosummary/mlx.nn.Step.html | 12 +- .../python/nn/_autosummary/mlx.nn.Tanh.html | 10 +- .../nn/_autosummary/mlx.nn.Transformer.html | 26 +- .../nn/_autosummary/mlx.nn.Upsample.html | 18 +- .../nn/_autosummary/mlx.nn.init.constant.html | 14 +- .../mlx.nn.init.glorot_normal.html | 14 +- .../mlx.nn.init.glorot_uniform.html | 14 +- .../_autosummary/mlx.nn.init.he_normal.html | 14 +- .../_autosummary/mlx.nn.init.he_uniform.html | 14 +- .../nn/_autosummary/mlx.nn.init.identity.html | 12 +- .../nn/_autosummary/mlx.nn.init.normal.html | 16 +- .../nn/_autosummary/mlx.nn.init.uniform.html | 16 +- .../_autosummary_functions/mlx.nn.celu.html | 10 +- .../nn/_autosummary_functions/mlx.nn.elu.html | 10 +- .../_autosummary_functions/mlx.nn.gelu.html | 10 +- .../mlx.nn.gelu_approx.html | 10 +- .../mlx.nn.gelu_fast_approx.html | 10 +- .../nn/_autosummary_functions/mlx.nn.glu.html | 14 +- .../mlx.nn.hard_shrink.html | 10 +- .../mlx.nn.hard_tanh.html | 10 +- .../mlx.nn.hardswish.html | 10 +- .../mlx.nn.leaky_relu.html | 10 +- .../mlx.nn.log_sigmoid.html | 10 +- .../mlx.nn.log_softmax.html | 10 +- .../mlx.nn.losses.binary_cross_entropy.html | 16 +- .../mlx.nn.losses.cosine_similarity_loss.html | 18 +- .../mlx.nn.losses.cross_entropy.html | 18 +- .../mlx.nn.losses.gaussian_nll_loss.html | 18 +- .../mlx.nn.losses.hinge_loss.html | 14 +- .../mlx.nn.losses.huber_loss.html | 16 +- .../mlx.nn.losses.kl_div_loss.html | 16 +- .../mlx.nn.losses.l1_loss.html | 14 +- .../mlx.nn.losses.log_cosh_loss.html | 14 +- .../mlx.nn.losses.margin_ranking_loss.html | 16 +- .../mlx.nn.losses.mse_loss.html | 14 +- .../mlx.nn.losses.nll_loss.html | 16 +- .../mlx.nn.losses.smooth_l1_loss.html | 16 +- .../mlx.nn.losses.triplet_loss.html | 22 +- .../_autosummary_functions/mlx.nn.mish.html | 10 +- .../_autosummary_functions/mlx.nn.prelu.html | 10 +- .../_autosummary_functions/mlx.nn.relu.html | 10 +- .../_autosummary_functions/mlx.nn.relu6.html | 10 +- .../_autosummary_functions/mlx.nn.selu.html | 10 +- .../mlx.nn.sigmoid.html | 10 +- .../_autosummary_functions/mlx.nn.silu.html | 10 +- .../mlx.nn.softmax.html | 10 +- .../mlx.nn.softmin.html | 10 +- .../mlx.nn.softplus.html | 10 +- .../mlx.nn.softshrink.html | 12 +- .../_autosummary_functions/mlx.nn.step.html | 12 +- .../_autosummary_functions/mlx.nn.tanh.html | 10 +- docs/build/html/python/nn/functions.html | 10 +- docs/build/html/python/nn/init.html | 10 +- docs/build/html/python/nn/layers.html | 10 +- docs/build/html/python/nn/losses.html | 10 +- docs/build/html/python/nn/module.html | 10 +- docs/build/html/python/ops.html | 95 +- docs/build/html/python/optimizers.html | 10 +- .../_autosummary/mlx.optimizers.AdaDelta.html | 18 +- .../mlx.optimizers.Adafactor.html | 30 +- .../_autosummary/mlx.optimizers.Adagrad.html | 16 +- .../_autosummary/mlx.optimizers.Adam.html | 18 +- .../_autosummary/mlx.optimizers.AdamW.html | 20 +- .../_autosummary/mlx.optimizers.Adamax.html | 18 +- .../_autosummary/mlx.optimizers.Lion.html | 18 +- ....optimizers.Optimizer.apply_gradients.html | 16 +- .../mlx.optimizers.Optimizer.init.html | 14 +- .../mlx.optimizers.Optimizer.state.html | 10 +- .../mlx.optimizers.Optimizer.update.html | 14 +- .../_autosummary/mlx.optimizers.RMSprop.html | 18 +- .../_autosummary/mlx.optimizers.SGD.html | 22 +- .../mlx.optimizers.cosine_decay.html | 18 +- .../mlx.optimizers.exponential_decay.html | 16 +- .../mlx.optimizers.join_schedules.html | 16 +- .../mlx.optimizers.linear_schedule.html | 18 +- .../mlx.optimizers.step_decay.html | 18 +- .../python/optimizers/common_optimizers.html | 10 +- .../html/python/optimizers/optimizer.html | 10 +- .../html/python/optimizers/schedulers.html | 10 +- docs/build/html/python/random.html | 13 +- docs/build/html/python/transforms.html | 16 +- docs/build/html/python/tree_utils.html | 10 +- docs/build/html/search.html | 10 +- docs/build/html/searchindex.js | 2 +- ...1core_1_1_contiguous_iterator-members.html | 93 -- ...ctmlx_1_1core_1_1_contiguous_iterator.html | 191 ---- docs/build/html/usage/compile.html | 10 +- docs/build/html/usage/distributed.html | 10 +- .../build/html/usage/function_transforms.html | 14 +- docs/build/html/usage/indexing.html | 16 +- docs/build/html/usage/lazy_evaluation.html | 12 +- docs/build/html/usage/numpy.html | 16 +- docs/build/html/usage/quick_start.html | 10 +- docs/build/html/usage/saving_and_loading.html | 12 +- docs/build/html/usage/unified_memory.html | 10 +- docs/build/html/usage/using_streams.html | 10 +- 496 files changed, 5955 insertions(+), 3210 deletions(-) create mode 100644 docs/build/html/_sources/python/_autosummary/mlx.core.random.permutation.rst create mode 100644 docs/build/html/_sources/python/_autosummary/mlx.core.roll.rst create mode 100644 docs/build/html/python/_autosummary/mlx.core.random.permutation.html create mode 100644 docs/build/html/python/_autosummary/mlx.core.roll.html delete mode 100644 docs/build/html/structmlx_1_1core_1_1_contiguous_iterator-members.html delete mode 100644 docs/build/html/structmlx_1_1core_1_1_contiguous_iterator.html diff --git a/docs/build/html/.buildinfo b/docs/build/html/.buildinfo index bfb5ce6e3..fcec0f83f 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: 85eddbee44d4b85d5bc17c721e79c928 +config: afad7f1e99088fbef94fcb4df3f67506 tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/docs/build/html/_sources/python/_autosummary/mlx.core.random.permutation.rst b/docs/build/html/_sources/python/_autosummary/mlx.core.random.permutation.rst new file mode 100644 index 000000000..3e0ce913e --- /dev/null +++ b/docs/build/html/_sources/python/_autosummary/mlx.core.random.permutation.rst @@ -0,0 +1,6 @@ +mlx.core.random.permutation +=========================== + +.. currentmodule:: mlx.core.random + +.. autofunction:: permutation \ No newline at end of file diff --git a/docs/build/html/_sources/python/_autosummary/mlx.core.roll.rst b/docs/build/html/_sources/python/_autosummary/mlx.core.roll.rst new file mode 100644 index 000000000..4aa94949a --- /dev/null +++ b/docs/build/html/_sources/python/_autosummary/mlx.core.roll.rst @@ -0,0 +1,6 @@ +mlx.core.roll +============= + +.. currentmodule:: mlx.core + +.. autofunction:: roll \ No newline at end of file diff --git a/docs/build/html/_sources/python/ops.rst b/docs/build/html/_sources/python/ops.rst index e0d70ea14..e3c50e2ff 100644 --- a/docs/build/html/_sources/python/ops.rst +++ b/docs/build/html/_sources/python/ops.rst @@ -130,6 +130,7 @@ Operations repeat reshape right_shift + roll round rsqrt save diff --git a/docs/build/html/_sources/python/random.rst b/docs/build/html/_sources/python/random.rst index 5d98304bb..248959108 100644 --- a/docs/build/html/_sources/python/random.rst +++ b/docs/build/html/_sources/python/random.rst @@ -45,3 +45,4 @@ we use a splittable version of Threefry, which is a counter-based PRNG. truncated_normal uniform laplace + permutation diff --git a/docs/build/html/_static/documentation_options.js b/docs/build/html/_static/documentation_options.js index ca5dbe08b..6fe754faf 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: '0.18.0', + VERSION: '0.18.1', LANGUAGE: 'en', COLLAPSE_INDEX: false, BUILDER: 'html', diff --git a/docs/build/html/cpp/ops.html b/docs/build/html/cpp/ops.html index 407ce2662..0fc669da6 100644 --- a/docs/build/html/cpp/ops.html +++ b/docs/build/html/cpp/ops.html @@ -8,7 +8,7 @@ - Operations — MLX 0.18.0 documentation + Operations — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
  • mlx.core.repeat
  • mlx.core.reshape
  • mlx.core.right_shift
    • +
  • mlx.core.roll
  • mlx.core.round
  • mlx.core.rsqrt
  • mlx.core.save
    • @@ -425,6 +426,7 @@
  • mlx.core.random.truncated_normal
  • mlx.core.random.uniform
  • mlx.core.random.laplace
    • +
  • mlx.core.random.permutation
  • Transforms @@ -2923,6 +2931,37 @@ document.write(` array view(const array &a, const Dtype &dtype, StreamOrDevice s = {})#
    +
    +
    +array roll(const array &a, int shift, StreamOrDevice s = {})#
    +

    Roll elements along an axis and introduce them on the other side.

    +
    + +
    +
    +array roll(const array &a, const std::vector<int> &shift, StreamOrDevice s = {})#
    +
    + +
    +
    +array roll(const array &a, int shift, int axis, StreamOrDevice s = {})#
    +
    + +
    +
    +array roll(const array &a, int shift, const std::vector<int> &axes, StreamOrDevice s = {})#
    +
    + +
    +
    +array roll(const array &a, const std::vector<int> &shift, int axis, StreamOrDevice s = {})#
    +
    + +
    +
    +array roll(const array &a, const std::vector<int> &shift, const std::vector<int> &axes, StreamOrDevice s = {})#
    +
    + @@ -3269,6 +3308,12 @@ document.write(`
  • right_shift()
  • operator>>()
  • view()
    • +
  • roll()
    • +
  • roll()
    • +
  • roll()
    • +
  • roll()
    • +
  • roll()
    • +
  • roll()
    • diff --git a/docs/build/html/dev/custom_metal_kernels.html b/docs/build/html/dev/custom_metal_kernels.html index c4b1975d4..2c0fdcd59 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 0.18.0 documentation + Custom Metal Kernels — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -130,8 +130,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -369,6 +369,7 @@
  • mlx.core.repeat
  • mlx.core.reshape
  • mlx.core.right_shift
    • +
  • mlx.core.roll
  • mlx.core.round
  • mlx.core.rsqrt
  • mlx.core.save
    • @@ -424,6 +425,7 @@
  • mlx.core.random.truncated_normal
  • mlx.core.random.uniform
  • mlx.core.random.laplace
    • +
  • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms - +
  • Transforms
  • Transforms
  • Transforms
      @@ -878,7 +880,7 @@ document.write(`

      A device to run operations on.

      -__init__(self, type: mlx.core.DeviceType, index: int = 0) → None#
      +__init__(self, type: mlx.core.DeviceType, index: int = 0) → None#

      Methods

      diff --git a/docs/build/html/python/_autosummary/mlx.core.Dtype.html b/docs/build/html/python/_autosummary/mlx.core.Dtype.html index 7cdee3468..c4f1514b1 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 0.18.0 documentation + mlx.core.Dtype — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.addmm#

      -addmm(c: array, a: array, b: array, /, alpha: float = 1.0, beta: float = 1.0, *, stream: None | Stream | Device = None) → array#
      +addmm(c: array, a: array, b: array, /, alpha: float = 1.0, beta: float = 1.0, *, stream: None | Stream | Device = None) → array#

      Matrix multiplication with addition and optional scaling.

      Perform the (possibly batched) matrix multiplication of two arrays and add to the result with optional scaling factors.

      @@ -881,9 +883,9 @@ with optional scaling factors.

    • c (array) – Input array or scalar.

    • a (array) – Input array or scalar.

    • b (array) – Input array or scalar.

      • -

    • alpha (float, optional) – Scaling factor for the +

    • alpha (float, optional) – Scaling factor for the matrix product of a and b (default: 1)

      • -

    • beta (float, optional) – Scaling factor for c (default: 1)

      • +

    • beta (float, optional) – Scaling factor for c (default: 1)

    Returns:
    diff --git a/docs/build/html/python/_autosummary/mlx.core.all.html b/docs/build/html/python/_autosummary/mlx.core.all.html index e00ea9552..c5c1acd89 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 0.18.0 documentation + mlx.core.all — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
  • mlx.core.repeat
  • mlx.core.reshape
  • mlx.core.right_shift
    • +
  • mlx.core.roll
  • mlx.core.round
  • mlx.core.rsqrt
  • mlx.core.save
    • @@ -425,6 +426,7 @@
  • mlx.core.random.truncated_normal
  • mlx.core.random.uniform
  • mlx.core.random.laplace
    • +
  • mlx.core.random.permutation
  • Transforms
      @@ -871,16 +873,16 @@ document.write(`

      mlx.core.all#

      -all(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
      +all(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

      An and reduction over the given axes.

      Parameters:

      • a (array) – Input array.

        • -

      • axis (int or list(int), optional) – Optional axis or +

      • axis (int or list(int), optional) – Optional axis or axes to reduce over. If unspecified this defaults to reducing over the entire array.

        • -

      • keepdims (bool, optional) – Keep reduced axes as +

      • keepdims (bool, optional) – Keep reduced axes as singleton dimensions, defaults to False.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.allclose.html b/docs/build/html/python/_autosummary/mlx.core.allclose.html index eb86cae35..6d0e1a616 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 0.18.0 documentation + mlx.core.allclose — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.allclose#

      -allclose(a: array, b: array, /, rtol: float = 1e-05, atol: float = 1e-08, *, equal_nan: bool = False, stream: None | Stream | Device = None) → array#
      +allclose(a: array, b: array, /, rtol: float = 1e-05, atol: float = 1e-08, *, equal_nan: bool = False, stream: None | Stream | Device = None) → array#

      Approximate comparison of two arrays.

      Infinite values are considered equal if they have the same sign, NaN values are not equal unless equal_nan is True.

      The arrays are considered equal if:

      @@ -885,9 +887,9 @@ broadcasting.

      • a (array) – Input array.

      • b (array) – Input array.

        • -

      • rtol (float) – Relative tolerance.

        • -

      • atol (float) – Absolute tolerance.

        • -

      • equal_nan (bool) – If True, NaNs are considered equal. +

      • rtol (float) – Relative tolerance.

        • +

      • atol (float) – Absolute tolerance.

        • +

      • equal_nan (bool) – If True, NaNs are considered equal. Defaults to False.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.any.html b/docs/build/html/python/_autosummary/mlx.core.any.html index 2b33cd99d..bf4f11379 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 0.18.0 documentation + mlx.core.any — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,16 +873,16 @@ document.write(`

      mlx.core.any#

      -any(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
      +any(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

      An or reduction over the given axes.

      Parameters:

      • a (array) – Input array.

        • -

      • axis (int or list(int), optional) – Optional axis or +

      • axis (int or list(int), optional) – Optional axis or axes to reduce over. If unspecified this defaults to reducing over the entire array.

        • -

      • keepdims (bool, optional) – Keep reduced axes as +

      • keepdims (bool, optional) – Keep reduced axes as singleton dimensions, defaults to False.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.arange.html b/docs/build/html/python/_autosummary/mlx.core.arange.html index 138628131..8ec7fe317 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 0.18.0 documentation + mlx.core.arange — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,38 +873,34 @@ document.write(`

      mlx.core.arange#

      -arange(start: int | float, stop: int | float, step: None | int | float, dtype: Dtype | None = None, *, stream: None | Stream | Device = None) → array#
      +arange(start: int | float, stop: int | float, step: None | int | float, dtype: Dtype | None = None, *, stream: None | Stream | Device = None) → array#
      -arange(stop: int | float, step: None | int | float = None, dtype: Dtype | None = None, *, stream: None | Stream | Device = None) → array
      -

      Generates ranges of numbers.

      +arange(stop: int | float, step: None | int | float = None, dtype: Dtype | None = None, *, stream: None | Stream | Device = None) → array +

      Overloaded function.

      +
        +

      1. arange(start : Union[int, float], stop : Union[int, float], step : Union[None, int, float], dtype: Optional[Dtype] = None, *, stream: Union[None, Stream, Device] = None) -> array

        +
        +

        Generates ranges of numbers.

        Generate numbers in the half-open interval [start, stop) in increments of step.

        -
        -
        Parameters:
        -
          -

        • start (float or int, optional) – Starting value which defaults to 0.

          • -

        • stop (float or int) – Stopping value.

          • -

        • step (float or int, optional) – Increment which defaults to 1.

          • -

        • dtype (Dtype, optional) – Specifies the data type of the output. -If unspecified will default to float32 if any of start, -stop, or step are float. Otherwise will default to -int32.

          • -
        +
        +
        Args:

        start (float or int, optional): Starting value which defaults to 0. +stop (float or int): Stopping value. +step (float or int, optional): Increment which defaults to 1. +dtype (Dtype, optional): Specifies the data type of the output. If unspecified will default to float32 if any of start, stop, or step are float. Otherwise will default to int32.

        -
        Returns:
        -

        The range of values.

        +
        Returns:

        array: The range of values.

        -
        Return type:
        -

        array

        -
        -
        -
        -

        Note

        -

        Following the Numpy convention the actual increment used to +

        Note:

        Following the Numpy convention the actual increment used to generate numbers is dtype(start + step) - dtype(start). This can lead to unexpected results for example if start + step is a fractional value and the dtype is integral.

        -
        +
      +
      + + +

    • arange(stop : Union[int, float], step : Union[None, int, float] = None, dtype: Optional[Dtype] = None, *, stream: Union[None, Stream, Device] = None) -> array

      • + diff --git a/docs/build/html/python/_autosummary/mlx.core.arccos.html b/docs/build/html/python/_autosummary/mlx.core.arccos.html index 39323b182..4fb8526b3 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 0.18.0 documentation + mlx.core.arccos — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -871,15 +873,15 @@ document.write(`

      mlx.core.argmax#

      -argmax(a: array, /, axis: None | int = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
      +argmax(a: array, /, axis: None | int = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

      Indices of the maximum values along the axis.

      Parameters:

      • a (array) – Input array.

        • -

      • axis (int, optional) – Optional axis to reduce over. If unspecified +

      • axis (int, optional) – Optional axis to reduce over. If unspecified this defaults to reducing over the entire array.

        • -

      • keepdims (bool, optional) – Keep reduced axes as +

      • keepdims (bool, optional) – Keep reduced axes as singleton dimensions, defaults to False.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.argmin.html b/docs/build/html/python/_autosummary/mlx.core.argmin.html index 61b07853d..7addbd5ad 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 0.18.0 documentation + mlx.core.argmin — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,15 +873,15 @@ document.write(`

      mlx.core.argmin#

      -argmin(a: array, /, axis: None | int = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
      +argmin(a: array, /, axis: None | int = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

      Indices of the minimum values along the axis.

      Parameters:

      • a (array) – Input array.

        • -

      • axis (int, optional) – Optional axis to reduce over. If unspecified +

      • axis (int, optional) – Optional axis to reduce over. If unspecified this defaults to reducing over the entire array.

        • -

      • keepdims (bool, optional) – Keep reduced axes as +

      • keepdims (bool, optional) – Keep reduced axes as singleton dimensions, defaults to False.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.argpartition.html b/docs/build/html/python/_autosummary/mlx.core.argpartition.html index 88cf0ba7f..e6ad208be 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 0.18.0 documentation + mlx.core.argpartition — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.argpartition#

      -argpartition(a: array, /, kth: int, axis: None | int = -1, *, stream: None | Stream | Device = None) → array#
      +argpartition(a: array, /, kth: int, axis: None | int = -1, *, stream: None | Stream | Device = None) → array#

      Returns the indices that partition the array.

      The ordering of the elements within a partition in given by the indices is undefined.

      @@ -879,12 +881,12 @@ is undefined.

      Parameters:

      • a (array) – Input array.

        • -

      • kth (int) – Element index at the kth position in the output will +

      • kth (int) – Element index at the kth position in the output will give the sorted position. All indices before the kth position will be of elements less or equal to the element at the kth index and all indices after will be of elements greater or equal to the element at the kth index.

        • -

      • axis (int or None, optional) – Optional axis to partition over. +

      • axis (int or None, optional) – Optional axis to partition over. If None, this partitions over the flattened array. If unspecified, it defaults to -1.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.argsort.html b/docs/build/html/python/_autosummary/mlx.core.argsort.html index 9b2f652af..dbf779c55 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 0.18.0 documentation + mlx.core.argsort — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,13 +873,13 @@ document.write(`

      mlx.core.argsort#

      -argsort(a: array, /, axis: None | int = -1, *, stream: None | Stream | Device = None) → array#
      +argsort(a: array, /, axis: None | int = -1, *, stream: None | Stream | Device = None) → array#

      Returns the indices that sort the array.

      Parameters:

      • a (array) – Input array.

        • -

      • axis (int or None, optional) – Optional axis to sort over. +

      • axis (int or None, optional) – Optional axis to sort over. If None, this sorts over the flattened array. If unspecified, it defaults to -1 (sorting over the last axis).

      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 b4ffb0515..03467eb58 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 0.18.0 documentation + mlx.core.array.T — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.array.item#

      -array.item(self) → object#
      +array.item(self) → object#

      Access the value of a scalar array.

      Returns:
      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 d6e1a3b53..cad425e14 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 0.18.0 documentation + mlx.core.array.itemsize — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -871,8 +873,8 @@ document.write(`

      mlx.core.array.tolist#

      -array.tolist(self) → object#
      -

      Convert the array to a Python list.

      +array.tolist(self) → object# +

      Convert the array to a Python list.

      Returns:

      The Python list.

      @@ -884,7 +886,7 @@ list of lists.

      Return type:
      -

      list

      +

      list

      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 51c9f1e9f..285a9b777 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 0.18.0 documentation + mlx.core.array.transpose — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.array_equal#

      -array_equal(a: scalar | array, b: scalar | array, equal_nan: bool = False, stream: None | Stream | Device = None) → array#
      +array_equal(a: scalar | array, b: scalar | array, equal_nan: bool = False, stream: None | Stream | Device = None) → array#

      Array equality check.

      Compare two arrays for equality. Returns True if and only if the arrays have the same shape and their values are equal. The arrays need not have @@ -881,7 +883,7 @@ the same type to be considered equal.

      • a (array) – Input array or scalar.

      • b (array) – Input array or scalar.

        • -

      • equal_nan (bool) – If True, NaNs are considered equal. +

      • equal_nan (bool) – If True, NaNs are considered equal. Defaults to False.

      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 3613643b2..c14b2325f 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 0.18.0 documentation + mlx.core.as_strided — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.as_strided#

      -as_strided(a: array, /, shape: Sequence[int] | None = None, strides: Sequence[int] | None = None, offset: int = 0, *, stream: None | Stream | Device = None) → array#
      +as_strided(a: array, /, shape: Sequence[int] | None = None, strides: Sequence[int] | None = None, offset: int = 0, *, stream: None | Stream | Device = None) → array#

      Create a view into the array with the given shape and strides.

      The resulting array will always be as if the provided array was row contiguous regardless of the provided arrays storage order and current @@ -887,12 +889,12 @@ result into crashes.

      Parameters:

      • a (array) – Input array

        • -

      • shape (list(int), optional) – The shape of the resulting array. If +

      • shape (list(int), optional) – The shape of the resulting array. If None it defaults to a.shape().

        • -

      • strides (list(int), optional) – The strides of the resulting array. If +

      • strides (list(int), optional) – The strides of the resulting array. If None it defaults to the reverse exclusive cumulative product of a.shape().

        • -

      • offset (int) – Skip that many elements from the beginning of the input +

      • offset (int) – Skip that many elements from the beginning of the input array.

      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 547dc727b..aa484178d 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 0.18.0 documentation + mlx.core.atleast_1d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.bitwise_and#

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

      Element-wise bitwise and.

      Take the bitwise and of two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

      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 f23a06561..38ef639a7 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 0.18.0 documentation + mlx.core.bitwise_or — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.bitwise_or#

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

      Element-wise bitwise or.

      Take the bitwise or of two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.bitwise_xor.html b/docs/build/html/python/_autosummary/mlx.core.bitwise_xor.html index e299b8a1e..6a6547f73 100644 --- a/docs/build/html/python/_autosummary/mlx.core.bitwise_xor.html +++ b/docs/build/html/python/_autosummary/mlx.core.bitwise_xor.html @@ -8,7 +8,7 @@ - mlx.core.bitwise_xor — MLX 0.18.0 documentation + mlx.core.bitwise_xor — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.bitwise_xor#

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

      Element-wise bitwise xor.

      Take the bitwise exclusive or of two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be 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 4dc4b70fc..909acc9a1 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 0.18.0 documentation + mlx.core.block_masked_mm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@

    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -426,6 +427,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -872,7 +874,7 @@ document.write(`

      mlx.core.block_masked_mm#

      -block_masked_mm(a: array, b: array, /, block_size: int = 64, mask_out: array | None = None, mask_lhs: array | None = None, mask_rhs: array | None = None, *, stream: None | Stream | Device = None) → array#
      +block_masked_mm(a: array, b: array, /, block_size: int = 64, mask_out: array | None = None, mask_lhs: array | None = None, mask_rhs: array | None = None, *, stream: None | Stream | Device = None) → array#

      Matrix multiplication with block masking.

      Perform the (possibly batched) matrix multiplication of two arrays and with blocks of size block_size x block_size optionally masked out.

      @@ -888,7 +890,7 @@ of size block_size<

      • a (array) – Input array or scalar.

      • b (array) – Input array or scalar.

        • -

      • block_size (int) – Size of blocks to be masked. Must be 32 or 64. Default: 64.

        • +

      • block_size (int) – Size of blocks to be masked. Must be 32 or 64. Default: 64.

      • mask_out (array, optional) – Mask for output. Default: None.

      • mask_lhs (array, optional) – Mask for a. Default: None.

      • mask_rhs (array, optional) – Mask for b. Default: None.

        • 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 2a670dbe6..3b2de5706 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 0.18.0 documentation + mlx.core.broadcast_to — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,14 +873,14 @@ document.write(`

        mlx.core.broadcast_to#

        -broadcast_to(a: scalar | array, /, shape: Sequence[int], *, stream: None | Stream | Device = None) → array#
        +broadcast_to(a: scalar | array, /, shape: Sequence[int], *, stream: None | Stream | Device = None) → array#

        Broadcast an array to the given shape.

        The broadcasting semantics are the same as Numpy.

        Parameters:

        • a (array) – Input array.

          • -

        • shape (list(int)) – The shape to broadcast to.

          • +

        • shape (list(int)) – The shape to broadcast to.

        Returns:
        diff --git a/docs/build/html/python/_autosummary/mlx.core.ceil.html b/docs/build/html/python/_autosummary/mlx.core.ceil.html index 6b40079bd..bbd4efccd 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 0.18.0 documentation + mlx.core.ceil — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
    • Transforms
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.compile#

        -compile(fun: Callable, inputs: object | None = None, outputs: object | None = None, shapeless: bool = False) → Callable#
        +compile(fun: Callable, inputs: object | None = None, outputs: object | None = None, shapeless: bool = False) → Callable#

        Returns a compiled function which produces the same output as fun.

        Parameters:
        @@ -879,17 +881,17 @@ document.write(`

      • fun (Callable) – A function which takes a variable number of array or trees of array and returns a variable number of array or trees of array.

        • -

      • inputs (list or dict, optional) – These inputs will be captured during +

      • inputs (list or dict, optional) – These inputs will be captured during the function compilation along with the inputs to fun. The inputs -can be a list or a dict containing arbitrarily nested +can be a list or a dict containing arbitrarily nested lists, dictionaries, or arrays. Leaf nodes that are not array are ignored. Default: None

        • -

      • outputs (list or dict, optional) – These outputs will be captured and +

      • outputs (list or dict, optional) – These outputs will be captured and updated in a compiled function. The outputs can be a -list or a dict containing arbitrarily nested lists, +list or a dict containing arbitrarily nested lists, dictionaries, or arrays. Leaf nodes that are not array are ignored. Default: None

        • -

      • shapeless (bool, optional) – A function compiled with the shapeless +

      • shapeless (bool, optional) – A function compiled with the shapeless option enabled will not be recompiled when the input shape changes. Not all functions can be compiled with shapeless enabled. Attempting to compile such functions with shapeless enabled will throw. Note, changing the number diff --git a/docs/build/html/python/_autosummary/mlx.core.concatenate.html b/docs/build/html/python/_autosummary/mlx.core.concatenate.html index 213bbb104..b4836e3a5 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 0.18.0 documentation + mlx.core.concatenate — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@

      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
    • Transforms
    • Transforms
    • Transforms
        @@ -871,17 +873,17 @@ document.write(`

        mlx.core.conv1d#

        -conv1d(input: array, weight: array, /, stride: int = 1, padding: int = 0, dilation: int = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#
        +conv1d(input: array, weight: array, /, stride: int = 1, padding: int = 0, dilation: int = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#

        1D convolution over an input with several channels

        Parameters:

        • input (array) – Input array of shape (N, H, C_in).

        • weight (array) – Weight array of shape (C_out, H, C_in).

          • -

        • stride (int, optional) – Kernel stride. Default: 1.

          • -

        • padding (int, optional) – Input padding. Default: 0.

          • -

        • dilation (int, optional) – Kernel dilation. Default: 1.

          • -

        • groups (int, optional) – Input feature groups. Default: 1.

          • +

        • stride (int, optional) – Kernel stride. Default: 1.

          • +

        • padding (int, optional) – Input padding. Default: 0.

          • +

        • dilation (int, optional) – Kernel dilation. Default: 1.

          • +

        • groups (int, optional) – Input feature groups. Default: 1.

        Returns:
        diff --git a/docs/build/html/python/_autosummary/mlx.core.conv2d.html b/docs/build/html/python/_autosummary/mlx.core.conv2d.html index 3f4429b5d..b3c6273b8 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 0.18.0 documentation + mlx.core.conv2d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,23 +873,23 @@ document.write(`

        mlx.core.conv2d#

        -conv2d(input: array, weight: array, /, stride: int | tuple[int, int] = 1, padding: int | tuple[int, int] = 0, dilation: int | tuple[int, int] = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#
        +conv2d(input: array, weight: array, /, stride: int | tuple[int, int] = 1, padding: int | tuple[int, int] = 0, dilation: int | tuple[int, int] = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#

        2D convolution over an input with several channels

        Parameters:

        • input (array) – Input array of shape (N, H, W, C_in).

        • weight (array) – Weight array of shape (C_out, H, W, C_in).

          • -

        • stride (int or tuple(int), optional) – tuple of size 2 with +

        • stride (int or tuple(int), optional) – tuple of size 2 with kernel strides. All spatial dimensions get the same stride if only one number is specified. Default: 1.

          • -

        • padding (int or tuple(int), optional) – tuple of size 2 with +

        • padding (int or tuple(int), optional) – tuple of size 2 with symmetric input padding. All spatial dimensions get the same padding if only one number is specified. Default: 0.

          • -

        • dilation (int or tuple(int), optional) – tuple of size 2 with +

        • dilation (int or tuple(int), optional) – tuple of size 2 with kernel dilation. All spatial dimensions get the same dilation if only one number is specified. Default: 1

          • -

        • groups (int, optional) – input feature groups. Default: 1.

          • +

        • groups (int, optional) – input feature groups. Default: 1.

        Returns:
        diff --git a/docs/build/html/python/_autosummary/mlx.core.conv3d.html b/docs/build/html/python/_autosummary/mlx.core.conv3d.html index f10d332ff..b51a1b9c6 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 0.18.0 documentation + mlx.core.conv3d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.conv3d#

        -conv3d(input: array, weight: array, /, stride: int | tuple[int, int, int] = 1, padding: int | tuple[int, int, int] = 0, dilation: int | tuple[int, int, int] = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#
        +conv3d(input: array, weight: array, /, stride: int | tuple[int, int, int] = 1, padding: int | tuple[int, int, int] = 0, dilation: int | tuple[int, int, int] = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#

        3D convolution over an input with several channels

        Note: Only the default groups=1 is currently supported.

        @@ -879,16 +881,16 @@ document.write(`

        • input (array) – Input array of shape (N, D, H, W, C_in).

        • weight (array) – Weight array of shape (C_out, D, H, W, C_in).

          • -

        • stride (int or tuple(int), optional) – tuple of size 3 with +

        • stride (int or tuple(int), optional) – tuple of size 3 with kernel strides. All spatial dimensions get the same stride if only one number is specified. Default: 1.

          • -

        • padding (int or tuple(int), optional) – tuple of size 3 with +

        • padding (int or tuple(int), optional) – tuple of size 3 with symmetric input padding. All spatial dimensions get the same padding if only one number is specified. Default: 0.

          • -

        • dilation (int or tuple(int), optional) – tuple of size 3 with +

        • dilation (int or tuple(int), optional) – tuple of size 3 with kernel dilation. All spatial dimensions get the same dilation if only one number is specified. Default: 1

          • -

        • groups (int, optional) – input feature groups. Default: 1.

          • +

        • groups (int, optional) – input feature groups. Default: 1.

        Returns:
        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 5c4d8ed9f..87d61193e 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 0.18.0 documentation + mlx.core.conv_general — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,26 +873,26 @@ document.write(`

        mlx.core.conv_general#

        -conv_general(input: array, weight: array, /, stride: int | Sequence[int] = 1, padding: int | Sequence[int] | tuple[Sequence[int], Sequence[int]] = 0, kernel_dilation: int | Sequence[int] = 1, input_dilation: int | Sequence[int] = 1, groups: int = 1, flip: bool = False, *, stream: None | Stream | Device = None) → array#
        +conv_general(input: array, weight: array, /, stride: int | Sequence[int] = 1, padding: int | Sequence[int] | tuple[Sequence[int], Sequence[int]] = 0, kernel_dilation: int | Sequence[int] = 1, input_dilation: int | Sequence[int] = 1, groups: int = 1, flip: bool = False, *, stream: None | Stream | Device = None) → array#

        General convolution over an input with several channels

        Parameters:

        • input (array) – Input array of shape (N, ..., C_in).

        • weight (array) – Weight array of shape (C_out, ..., C_in).

          • -

        • stride (int or list(int), optional) – list with kernel strides. +

        • stride (int or list(int), optional) – list with kernel strides. All spatial dimensions get the same stride if only one number is specified. Default: 1.

          • -

        • padding (int, list(int), or tuple(list(int), list(int)), optional) – list with input padding. All spatial dimensions get the same +

        • padding (int, list(int), or tuple(list(int), list(int)), optional) – list with input padding. All spatial dimensions get the same padding if only one number is specified. Default: 0.

          • -

        • kernel_dilation (int or list(int), optional) – list with +

        • kernel_dilation (int or list(int), optional) – list with kernel dilation. All spatial dimensions get the same dilation if only one number is specified. Default: 1

          • -

        • input_dilation (int or list(int), optional) – list with +

        • input_dilation (int or list(int), optional) – list with input dilation. All spatial dimensions get the same dilation if only one number is specified. Default: 1

          • -

        • groups (int, optional) – Input feature groups. Default: 1.

          • -

        • flip (bool, optional) – Flip the order in which the spatial dimensions of +

        • groups (int, optional) – Input feature groups. Default: 1.

          • +

        • flip (bool, optional) – Flip the order in which the spatial dimensions of the weights are processed. Performs the cross-correlation operator when flip is False and the convolution operator otherwise. Default: False.

          • 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 aa2e52695..922f00ace 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 0.18.0 documentation + mlx.core.conv_transpose1d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,17 +873,17 @@ document.write(`

          mlx.core.conv_transpose1d#

          -conv_transpose1d(input: array, weight: array, /, stride: int = 1, padding: int = 0, dilation: int = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#
          +conv_transpose1d(input: array, weight: array, /, stride: int = 1, padding: int = 0, dilation: int = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#

          1D transposed convolution over an input with several channels

          Parameters:

          • input (array) – Input array of shape (N, H, C_in).

          • weight (array) – Weight array of shape (C_out, H, C_in).

            • -

          • stride (int, optional) – Kernel stride. Default: 1.

            • -

          • padding (int, optional) – Input padding. Default: 0.

            • -

          • dilation (int, optional) – Kernel dilation. Default: 1.

            • -

          • groups (int, optional) – Input feature groups. Default: 1.

            • +

          • stride (int, optional) – Kernel stride. Default: 1.

            • +

          • padding (int, optional) – Input padding. Default: 0.

            • +

          • dilation (int, optional) – Kernel dilation. Default: 1.

            • +

          • groups (int, optional) – Input feature groups. Default: 1.

          Returns:
          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 5a7bc8e07..0f9116a7a 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 0.18.0 documentation + mlx.core.conv_transpose2d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.core.conv_transpose2d#

          -conv_transpose2d(input: array, weight: array, /, stride: int | Tuple[int, int] = 1, padding: int | Tuple[int, int] = 0, dilation: int | Tuple[int, int] = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#
          +conv_transpose2d(input: array, weight: array, /, stride: int | Tuple[int, int] = 1, padding: int | Tuple[int, int] = 0, dilation: int | Tuple[int, int] = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#

          2D transposed convolution over an input with several channels

          Note: Only the default groups=1 is currently supported.

          @@ -879,16 +881,16 @@ document.write(`

          • input (array) – Input array of shape (N, H, W, C_in).

          • weight (array) – Weight array of shape (C_out, H, W, C_in).

            • -

          • stride (int or tuple(int), optional) – tuple of size 2 with +

          • stride (int or tuple(int), optional) – tuple of size 2 with kernel strides. All spatial dimensions get the same stride if only one number is specified. Default: 1.

            • -

          • padding (int or tuple(int), optional) – tuple of size 2 with +

          • padding (int or tuple(int), optional) – tuple of size 2 with symmetric input padding. All spatial dimensions get the same padding if only one number is specified. Default: 0.

            • -

          • dilation (int or tuple(int), optional) – tuple of size 2 with +

          • dilation (int or tuple(int), optional) – tuple of size 2 with kernel dilation. All spatial dimensions get the same dilation if only one number is specified. Default: 1

            • -

          • groups (int, optional) – input feature groups. Default: 1.

            • +

          • groups (int, optional) – input feature groups. Default: 1.

          Returns:
          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 056a3fc49..dd672e57e 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 0.18.0 documentation + mlx.core.conv_transpose3d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.core.conv_transpose3d#

          -conv_transpose3d(input: array, weight: array, /, stride: int | Tuple[int, int, int] = 1, padding: int | Tuple[int, int, int] = 0, dilation: int | Tuple[int, int, int] = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#
          +conv_transpose3d(input: array, weight: array, /, stride: int | Tuple[int, int, int] = 1, padding: int | Tuple[int, int, int] = 0, dilation: int | Tuple[int, int, int] = 1, groups: int = 1, *, stream: None | Stream | Device = None) → array#

          3D transposed convolution over an input with several channels

          Note: Only the default groups=1 is currently supported.

          @@ -879,16 +881,16 @@ document.write(`

          • input (array) – Input array of shape (N, D, H, W, C_in).

          • weight (array) – Weight array of shape (C_out, D, H, W, C_in).

            • -

          • stride (int or tuple(int), optional) – tuple of size 3 with +

          • stride (int or tuple(int), optional) – tuple of size 3 with kernel strides. All spatial dimensions get the same stride if only one number is specified. Default: 1.

            • -

          • padding (int or tuple(int), optional) – tuple of size 3 with +

          • padding (int or tuple(int), optional) – tuple of size 3 with symmetric input padding. All spatial dimensions get the same padding if only one number is specified. Default: 0.

            • -

          • dilation (int or tuple(int), optional) – tuple of size 3 with +

          • dilation (int or tuple(int), optional) – tuple of size 3 with kernel dilation. All spatial dimensions get the same dilation if only one number is specified. Default: 1

            • -

          • groups (int, optional) – input feature groups. Default: 1.

            • +

          • groups (int, optional) – input feature groups. Default: 1.

          Returns:
          diff --git a/docs/build/html/python/_autosummary/mlx.core.convolve.html b/docs/build/html/python/_autosummary/mlx.core.convolve.html index b01c30c18..2a4f7bb80 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 0.18.0 documentation + mlx.core.convolve — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.core.convolve#

          -convolve(a: array, v: array, /, mode: str = 'full', *, stream: None | Stream | Device = None) → array#
          +convolve(a: array, v: array, /, mode: str = 'full', *, stream: None | Stream | Device = None) → array#

          The discrete convolution of 1D arrays.

          If v is longer than a, then they are swapped. The conv filter is flipped following signal processing convention.

          @@ -880,7 +882,7 @@ The conv filter is flipped following signal processing convention.

          • a (array) – 1D Input array.

          • v (array) – 1D Input array.

            • -

          • mode (str, optional) – {‘full’, ‘valid’, ‘same’}

            • +

          • mode (str, optional) – {‘full’, ‘valid’, ‘same’}

          Returns:
          diff --git a/docs/build/html/python/_autosummary/mlx.core.cos.html b/docs/build/html/python/_autosummary/mlx.core.cos.html index 72923915e..559d0f57f 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 0.18.0 documentation + mlx.core.cos — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
      • Transforms
      • Transforms
          @@ -871,17 +873,17 @@ document.write(`

          mlx.core.cummax#

          -cummax(a: array, /, axis: int | None = None, *, reverse: bool = False, inclusive: bool = True, stream: None | Stream | Device = None) → array#
          +cummax(a: array, /, axis: int | None = None, *, reverse: bool = False, inclusive: bool = True, stream: None | Stream | Device = None) → array#

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

          Parameters:

          • a (array) – Input array

            • -

          • axis (int, optional) – Optional axis to compute the cumulative maximum +

          • axis (int, optional) – Optional axis to compute the cumulative maximum over. If unspecified the cumulative maximum of the flattened array is returned.

            • -

          • reverse (bool) – Perform the cumulative maximum in reverse.

            • -

          • inclusive (bool) – The i-th element of the output includes the i-th +

          • reverse (bool) – Perform the cumulative maximum in reverse.

            • +

          • inclusive (bool) – The i-th element of the output includes the i-th element of the input.

          diff --git a/docs/build/html/python/_autosummary/mlx.core.cummin.html b/docs/build/html/python/_autosummary/mlx.core.cummin.html index 059c22455..0e3edf7ef 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 0.18.0 documentation + mlx.core.cummin — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,17 +873,17 @@ document.write(`

          mlx.core.cummin#

          -cummin(a: array, /, axis: int | None = None, *, reverse: bool = False, inclusive: bool = True, stream: None | Stream | Device = None) → array#
          +cummin(a: array, /, axis: int | None = None, *, reverse: bool = False, inclusive: bool = True, stream: None | Stream | Device = None) → array#

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

          Parameters:

          • a (array) – Input array

            • -

          • axis (int, optional) – Optional axis to compute the cumulative minimum +

          • axis (int, optional) – Optional axis to compute the cumulative minimum over. If unspecified the cumulative minimum of the flattened array is returned.

            • -

          • reverse (bool) – Perform the cumulative minimum in reverse.

            • -

          • inclusive (bool) – The i-th element of the output includes the i-th +

          • reverse (bool) – Perform the cumulative minimum in reverse.

            • +

          • inclusive (bool) – The i-th element of the output includes the i-th element of the input.

          diff --git a/docs/build/html/python/_autosummary/mlx.core.cumprod.html b/docs/build/html/python/_autosummary/mlx.core.cumprod.html index 14ddcf9c3..cad69637a 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 0.18.0 documentation + mlx.core.cumprod — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,17 +873,17 @@ document.write(`

          mlx.core.cumprod#

          -cumprod(a: array, /, axis: int | None = None, *, reverse: bool = False, inclusive: bool = True, stream: None | Stream | Device = None) → array#
          +cumprod(a: array, /, axis: int | None = None, *, reverse: bool = False, inclusive: bool = True, stream: None | Stream | Device = None) → array#

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

          Parameters:

          • a (array) – Input array

            • -

          • axis (int, optional) – Optional axis to compute the cumulative product +

          • axis (int, optional) – Optional axis to compute the cumulative product over. If unspecified the cumulative product of the flattened array is returned.

            • -

          • reverse (bool) – Perform the cumulative product in reverse.

            • -

          • inclusive (bool) – The i-th element of the output includes the i-th +

          • reverse (bool) – Perform the cumulative product in reverse.

            • +

          • inclusive (bool) – The i-th element of the output includes the i-th element of the input.

          diff --git a/docs/build/html/python/_autosummary/mlx.core.cumsum.html b/docs/build/html/python/_autosummary/mlx.core.cumsum.html index 456ba11cd..4f263bda5 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 0.18.0 documentation + mlx.core.cumsum — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,17 +873,17 @@ document.write(`

          mlx.core.cumsum#

          -cumsum(a: array, /, axis: int | None = None, *, reverse: bool = False, inclusive: bool = True, stream: None | Stream | Device = None) → array#
          +cumsum(a: array, /, axis: int | None = None, *, reverse: bool = False, inclusive: bool = True, stream: None | Stream | Device = None) → array#

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

          Parameters:

          • a (array) – Input array

            • -

          • axis (int, optional) – Optional axis to compute the cumulative sum +

          • axis (int, optional) – Optional axis to compute the cumulative sum over. If unspecified the cumulative sum of the flattened array is returned.

            • -

          • reverse (bool) – Perform the cumulative sum in reverse.

            • -

          • inclusive (bool) – The i-th element of the output includes the i-th +

          • reverse (bool) – Perform the cumulative sum in reverse.

            • +

          • inclusive (bool) – The i-th element of the output includes the i-th element of the input.

          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 ad59d5644..26dfb5ce4 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 0.18.0 documentation + mlx.core.custom_function — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
      • Transforms
      • Transforms
      • Transforms
      • Transforms
          @@ -872,7 +874,7 @@ document.write(`

          mlx.core.dequantize#

          -dequantize(w: array, /, scales: array, biases: array, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → array#
          +dequantize(w: array, /, scales: array, biases: array, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → array#

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

          Formally, given the notation in quantize(), we compute @@ -886,9 +888,9 @@ document.write(`

        • w (array) – Matrix to be quantized

        • scales (array) – The scales to use per group_size elements of w

        • biases (array) – The biases to use per group_size elements of w

          • -

        • group_size (int, optional) – The size of the group in w that shares a +

        • group_size (int, optional) – The size of the group in w that shares a scale and bias. Default: 64.

          • -

        • bits (int, optional) – The number of bits occupied by each element in +

        • bits (int, optional) – The number of bits occupied by each element in w. Default: 4.

        • diff --git a/docs/build/html/python/_autosummary/mlx.core.diag.html b/docs/build/html/python/_autosummary/mlx.core.diag.html index 7fa56b472..0444122f4 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 0.18.0 documentation + mlx.core.diag — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -426,6 +427,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -872,7 +874,7 @@ document.write(`

        mlx.core.diag#

        -diag(a: array, /, k: int = 0, *, stream: None | Stream | Device = None) → array#
        +diag(a: array, /, k: int = 0, *, stream: None | Stream | Device = None) → array#

        Extract a diagonal or construct a diagonal matrix. If a is 1-D then a diagonal matrix is constructed with a on the \(k\)-th diagonal. If a is 2-D then the \(k\)-th diagonal is @@ -881,7 +883,7 @@ returned.

        Parameters:

        • a (array) – 1-D or 2-D input array.

          • -

        • k (int, optional) – The diagonal to extract or construct. +

        • k (int, optional) – The diagonal to extract or construct. Default: 0.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.diagonal.html b/docs/build/html/python/_autosummary/mlx.core.diagonal.html index 2600e1eb6..9f3d24332 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 0.18.0 documentation + mlx.core.diagonal — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.diagonal#

        -diagonal(a: array, offset: int = 0, axis1: int = 0, axis2: int = 1, stream: None | Stream | Device = None) → array#
        +diagonal(a: array, offset: int = 0, axis1: int = 0, axis2: int = 1, stream: None | Stream | Device = None) → array#

        Return specified diagonals.

        If a is 2-D, then a 1-D array containing the diagonal at the given offset is returned.

        @@ -883,11 +885,11 @@ new dimension inserted at the end corresponding to the diagonal.

        Parameters:

        • a (array) – Input array

          • -

        • offset (int, optional) – Offset of the diagonal from the main diagonal. +

        • offset (int, optional) – Offset of the diagonal from the main diagonal. Can be positive or negative. Default: 0.

          • -

        • axis1 (int, optional) – The first axis of the 2-D sub-arrays from which +

        • axis1 (int, optional) – The first axis of the 2-D sub-arrays from which the diagonals should be taken. Default: 0.

          • -

        • axis2 (int, optional) – The second axis of the 2-D sub-arrays from which +

        • axis2 (int, optional) – The second axis of the 2-D sub-arrays from which the diagonals should be taken. Default: 1.

        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 7965a432f..f36033ef9 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 0.18.0 documentation + mlx.core.disable_compile — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.disable_compile#

        -disable_compile() → None#
        +disable_compile() → None#

        Globally disable compilation. Setting the environment variable MLX_DISABLE_COMPILE can also be used to disable compilation.

        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 ef224f63b..30109f924 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 0.18.0 documentation + mlx.core.distributed.Group — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        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 27ebc79b3..c702a2966 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 0.18.0 documentation + mlx.core.distributed.all_gather — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.distributed.all_gather#

        -all_gather(x: array, *, group: Group | None = None, stream: None | Stream | Device = None) → array#
        +all_gather(x: array, *, group: Group | None = None, stream: None | Stream | Device = None) → array#

        Gather arrays from all processes.

        Gather the x arrays from all processes in the group and concatenate them along the first axis. The arrays should all have the same shape.

        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 be7a1245e..9818c1da5 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 0.18.0 documentation + mlx.core.distributed.all_sum — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
    • Transforms
        @@ -871,11 +873,11 @@ document.write(`

        mlx.core.distributed.init#

        -init(strict: bool = False) → Group#
        +init(strict: bool = False) → Group#

        Initialize the communication backend and create the global communication group.

        Parameters:
        -

        strict (bool, optional) – If set to False it returns a singleton group +

        strict (bool, optional) – If set to False it returns a singleton group in case mx.distributed.is_available() returns False otherwise it throws a runtime error. Default: False

        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 0251d0ac0..200d9f0b7 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 0.18.0 documentation + mlx.core.distributed.is_available — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.distributed.is_available#

        -is_available() → bool#
        +is_available() → bool#

        Check if a communication backend is available.

        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 3ef42743f..04ada83be 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 0.18.0 documentation + mlx.core.distributed.recv — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,15 +873,15 @@ document.write(`

        mlx.core.distributed.recv#

        -recv(shape: Sequence[int], dtype: Dtype, src: int, *, group: Group | None = None, stream: None | Stream | Device = None) → array#
        +recv(shape: Sequence[int], dtype: Dtype, src: int, *, group: Group | None = None, stream: None | Stream | Device = None) → array#

        Recv an array with shape shape and dtype dtype from process with rank src.

        Parameters:
          -

        • shape (Tuple[int]) – The shape of the array we are receiving.

          • +

        • shape (Tuple[int]) – The shape of the array we are receiving.

        • dtype (Dtype) – The data type of the array we are receiving.

          • -

        • src (int) – Rank of the source process in the group.

          • +

        • src (int) – Rank of the source process in the group.

        • group (Group) – The group of processes that will participate in the recv. If set to None the global group is used. Default: None.

          • 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 f86ab1c63..7bb347286 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 0.18.0 documentation + mlx.core.distributed.recv_like — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.core.distributed.recv_like#

          -recv_like(x: array, src: int, *, group: Group | None = None, stream: None | Stream | Device = None) → array#
          +recv_like(x: array, src: int, *, group: Group | None = None, stream: None | Stream | Device = None) → array#

          Recv an array with shape and type like x from process with rank src.

          It is equivalent to calling mx.distributed.recv(x.shape, x.dtype, src).

          @@ -880,7 +882,7 @@ document.write(`

          • x (array) – An array defining the shape and dtype of the array we are receiving.

            • -

          • src (int) – Rank of the source process in the group.

            • +

          • src (int) – Rank of the source process in the group.

          • group (Group) – The group of processes that will participate in the recv. If set to None the global group is used. Default: None.

            • 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 b577c93c2..351411e3c 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 0.18.0 documentation + mlx.core.distributed.send — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
          • mlx.core.repeat
          • mlx.core.reshape
          • mlx.core.right_shift
            • +
          • mlx.core.roll
          • mlx.core.round
          • mlx.core.rsqrt
          • mlx.core.save
            • @@ -425,6 +426,7 @@
          • mlx.core.random.truncated_normal
          • mlx.core.random.uniform
          • mlx.core.random.laplace
            • +
          • mlx.core.random.permutation
        • Transforms
            @@ -871,14 +873,14 @@ document.write(`

            mlx.core.distributed.send#

            -send(x: array, dst: int, *, group: Group | None = None, stream: None | Stream | Device = None) → array#
            +send(x: array, dst: int, *, group: Group | None = None, stream: None | Stream | Device = None) → array#

            Send an array from the current process to the process that has rank dst in the group.

            Parameters:

            • x (array) – Input array.

              • -

            • dst (int) – Rank of the destination process in the group.

              • +

            • dst (int) – Rank of the destination process in the group.

            • group (Group) – The group of processes that will participate in the sned. If set to None the global group is used. Default: None.

              • diff --git a/docs/build/html/python/_autosummary/mlx.core.divide.html b/docs/build/html/python/_autosummary/mlx.core.divide.html index 07d03463f..9f0e45503 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 0.18.0 documentation + mlx.core.divide — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
            • mlx.core.repeat
            • mlx.core.reshape
            • mlx.core.right_shift
              • +
            • mlx.core.roll
            • mlx.core.round
            • mlx.core.rsqrt
            • mlx.core.save
              • @@ -425,6 +426,7 @@
            • mlx.core.random.truncated_normal
            • mlx.core.random.uniform
            • mlx.core.random.laplace
              • +
            • mlx.core.random.permutation
          • Transforms
          • Transforms
              @@ -871,7 +873,7 @@ document.write(`

              mlx.core.divmod#

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

              Element-wise quotient and remainder.

              The fuction divmod(a, b) is equivalent to but faster than (a // b, a % b). The function uses numpy-style broadcasting @@ -887,7 +889,7 @@ semantics. Either or both input arrays can also be scalars.

              The quotient a // b and remainder a % b.

              Return type:
              -

              tuple(array, array)

              +

              tuple(array, array)

            • diff --git a/docs/build/html/python/_autosummary/mlx.core.einsum.html b/docs/build/html/python/_autosummary/mlx.core.einsum.html index 9c069ab4f..b522b7c10 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 0.18.0 documentation + mlx.core.einsum — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
          • mlx.core.repeat
          • mlx.core.reshape
          • mlx.core.right_shift
            • +
          • mlx.core.roll
          • mlx.core.round
          • mlx.core.rsqrt
          • mlx.core.save
            • @@ -425,6 +426,7 @@
          • mlx.core.random.truncated_normal
          • mlx.core.random.uniform
          • mlx.core.random.laplace
            • +
          • mlx.core.random.permutation
        • Transforms
            @@ -871,12 +873,12 @@ document.write(`

            mlx.core.einsum#

            -einsum(subscripts: str, *operands, stream: None | Stream | Device = None) → array#
            +einsum(subscripts: str, *operands, stream: None | Stream | Device = None) → array#

            Perform the Einstein summation convention on the operands.

            Parameters:
              -

            • subscripts (str) – The Einstein summation convention equation.

              • +

            • subscripts (str) – The Einstein summation convention equation.

            • *operands (array) – The input arrays.

            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 3950d836f..76ab75cba 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 0.18.0 documentation + mlx.core.einsum_path — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
          • mlx.core.repeat
          • mlx.core.reshape
          • mlx.core.right_shift
            • +
          • mlx.core.roll
          • mlx.core.round
          • mlx.core.rsqrt
          • mlx.core.save
            • @@ -425,6 +426,7 @@
          • mlx.core.random.truncated_normal
          • mlx.core.random.uniform
          • mlx.core.random.laplace
            • +
          • mlx.core.random.permutation
        • Transforms
            @@ -871,12 +873,12 @@ document.write(`

            mlx.core.einsum_path#

            -einsum_path(subscripts: str, *operands)#
            +einsum_path(subscripts: str, *operands)#

            Compute the contraction order for the given Einstein summation.

            Parameters:
              -

            • subscripts (str) – The Einstein summation convention equation.

              • +

            • subscripts (str) – The Einstein summation convention equation.

            • *operands (array) – The input arrays.

            @@ -885,7 +887,7 @@ document.write(` chosen path.

            Return type:
            -

            tuple(list(tuple(int, int)), str)

            +

            tuple(list(tuple(int, int)), str)

          • 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 69639aefc..ac9020322 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 0.18.0 documentation + mlx.core.enable_compile — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.core.enable_compile#

          -enable_compile() → None#
          +enable_compile() → None#

          Globally enable compilation. This will override the environment variable MLX_DISABLE_COMPILE if set.

          diff --git a/docs/build/html/python/_autosummary/mlx.core.equal.html b/docs/build/html/python/_autosummary/mlx.core.equal.html index 0b7058312..79ef51f7a 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 0.18.0 documentation + mlx.core.equal — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
      • Transforms
      • Transforms
      • Transforms
          @@ -871,13 +873,13 @@ document.write(`

          mlx.core.eval#

          -eval(*args) → None#
          +eval(*args) → None#

          Evaluate an array or tree of array.

          Parameters:

          *args (arrays or trees of arrays) – Each argument can be a single array or a tree of arrays. If a tree is given the nodes can be a Python -list, tuple or dict. Leaves which are not +list, tuple or dict. Leaves which are not arrays are ignored.

          diff --git a/docs/build/html/python/_autosummary/mlx.core.exp.html b/docs/build/html/python/_autosummary/mlx.core.exp.html index 4a7d5b9b7..c2f2c3dd7 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 0.18.0 documentation + mlx.core.exp — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
      • Transforms
      • Transforms
      • Transforms
          @@ -871,14 +873,14 @@ document.write(`

          mlx.core.eye#

          -eye(n: int, m: int | None = None, k: int = 0, dtype: Dtype | None = float32, *, stream: None | Stream | Device = None) → array#
          +eye(n: int, m: int | None = None, k: int = 0, dtype: Dtype | None = float32, *, stream: None | Stream | Device = None) → array#

          Create an identity matrix or a general diagonal matrix.

          Parameters:
            -

          • n (int) – The number of rows in the output.

            • -

          • m (int, optional) – The number of columns in the output. Defaults to n.

            • -

          • k (int, optional) – Index of the diagonal. Defaults to 0 (main diagonal).

            • +

          • n (int) – The number of rows in the output.

            • +

          • m (int, optional) – The number of columns in the output. Defaults to n.

            • +

          • k (int, optional) – Index of the diagonal. Defaults to 0 (main diagonal).

          • dtype (Dtype, optional) – Data type of the output array. Defaults to float32.

          • stream (Stream, optional) – Stream or device. Defaults to None.

          diff --git a/docs/build/html/python/_autosummary/mlx.core.fast.affine_quantize.html b/docs/build/html/python/_autosummary/mlx.core.fast.affine_quantize.html index 6a9992222..ed72ab74d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fast.affine_quantize.html +++ b/docs/build/html/python/_autosummary/mlx.core.fast.affine_quantize.html @@ -8,7 +8,7 @@ - mlx.core.fast.affine_quantize — MLX 0.18.0 documentation + mlx.core.fast.affine_quantize — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -426,6 +427,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -872,7 +874,7 @@ document.write(`

          mlx.core.fast.affine_quantize#

          -affine_quantize(w: array, /, scales: array, biases: array, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → array#
          +affine_quantize(w: array, /, scales: array, biases: array, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → array#

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

          Formally, given the notation in quantize(), we compute @@ -886,9 +888,9 @@ document.write(`

        • w (array) – Matrix to be quantize

        • scales (array) – The scales to use per group_size elements of w

        • biases (array) – The biases to use per group_size elements of w

          • -

        • group_size (int, optional) – The size of the group in w that shares a +

        • group_size (int, optional) – The size of the group in w that shares a scale and bias. (default: 64)

          • -

        • bits (int, optional) – The number of bits occupied by each element in +

        • bits (int, optional) – The number of bits occupied by each element in w. (default: 4)

        • 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 731b38d51..92a09b51d 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 0.18.0 documentation + mlx.core.fast.layer_norm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.fast.layer_norm#

        -layer_norm(x: array, weight: array | None, bias: array | None, eps: float, *, stream: None | Stream | Device = None) → array#
        +layer_norm(x: array, weight: array | None, bias: array | None, eps: float, *, stream: None | Stream | Device = None) → array#

        Layer normalization.

        The normalization is with respect to the last axis of the input x.

        @@ -884,7 +886,7 @@ as the last axis of

        bias (array, optional) – An additive offset to be added to the result. The bias should be one-dimensional with the same size as the last axis of x. If set to None then no translation happens.

        -

      • eps (float) – A small additive constant for numerical stability.

        • +

      • eps (float) – A small additive constant for numerical stability.

      • Returns:
      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 e0dfe9c60..bffb146c4 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 0.18.0 documentation + mlx.core.fast.metal_kernel — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,24 +873,24 @@ document.write(`

      mlx.core.fast.metal_kernel#

      -metal_kernel(name: str, input_names: Sequence[str], output_names: Sequence[str], source: str, header: str = '', ensure_row_contiguous: bool = True, atomic_outputs: bool = False) → object#
      +metal_kernel(name: str, input_names: Sequence[str], output_names: Sequence[str], source: str, header: str = '', ensure_row_contiguous: bool = True, atomic_outputs: bool = False) → object#

      A jit-compiled custom Metal kernel defined from a source string.

      Parameters:
        -

      • name (str) – Name for the kernel.

        • -

      • input_names (List[str]) – The parameter names of the inputs in the +

      • name (str) – Name for the kernel.

        • +

      • input_names (List[str]) – The parameter names of the inputs in the function signature.

        • -

      • output_names (List[str]) – The parameter names of the outputs in the +

      • output_names (List[str]) – The parameter names of the outputs in the function signature.

        • -

      • source (str) – Source code. This is the body of a function in Metal, +

      • source (str) – Source code. This is the body of a function in Metal, the function signature will be automatically generated.

        • -

      • header (str) – Header source code to include before the main function. +

      • header (str) – Header source code to include before the main function. Useful for helper functions or includes that should live outside of the main function body.

        • -

      • ensure_row_contiguous (bool) – Whether to ensure the inputs are row contiguous +

      • ensure_row_contiguous (bool) – Whether to ensure the inputs are row contiguous before the kernel runs. Default: True.

        • -

      • atomic_outputs (bool) – Whether to use atomic outputs in the function signature +

      • atomic_outputs (bool) – Whether to use atomic outputs in the function signature e.g. device atomic<float>. Default: False.

      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 dfd83aa18..487efb3e9 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 0.18.0 documentation + mlx.core.fast.rms_norm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.fast.rms_norm#

      -rms_norm(x: array, weight: array, eps: float, *, stream: None | Stream | Device = None) → array#
      +rms_norm(x: array, weight: array, eps: float, *, stream: None | Stream | Device = None) → array#

      Root Mean Square normalization (RMS norm).

      The normalization is with respect to the last axis of the input x.

      @@ -881,7 +883,7 @@ document.write(`

    • weight (array) – A multiplicative weight to scale the result by. The weight should be one-dimensional with the same size as the last axis of x.

      • -

    • eps (float) – A small additive constant for numerical stability.

      • +

    • eps (float) – A small additive constant for numerical stability.

    Returns:
    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 27710b82e..6e75f0db9 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 0.18.0 documentation + mlx.core.fast.rope — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
  • mlx.core.repeat
  • mlx.core.reshape
  • mlx.core.right_shift
    • +
  • mlx.core.roll
  • mlx.core.round
  • mlx.core.rsqrt
  • mlx.core.save
    • @@ -425,6 +426,7 @@
  • mlx.core.random.truncated_normal
  • mlx.core.random.uniform
  • mlx.core.random.laplace
    • +
  • mlx.core.random.permutation
  • Transforms
      @@ -871,21 +873,21 @@ document.write(`

      mlx.core.fast.rope#

      -rope(a: array, dims: int, *, traditional: bool, base: float | None, scale: float, offset: int, freqs: array | None = None, stream: None | Stream | Device = None) → array#
      +rope(a: array, dims: int, *, traditional: bool, base: float | None, scale: float, offset: int, freqs: array | None = None, stream: None | Stream | Device = None) → array#

      Apply rotary positional encoding to the input.

      Parameters:

      • a (array) – Input array.

        • -

      • dims (int) – The feature dimensions to be rotated. If the input feature +

      • dims (int) – The feature dimensions to be rotated. If the input feature is larger than dims then the rest is left unchanged.

        • -

      • traditional (bool) – If set to True choose the traditional +

      • traditional (bool) – If set to True choose the traditional implementation which rotates consecutive dimensions.

        • -

      • base (float, optional) – The base used to compute angular frequency for +

      • base (float, optional) – The base used to compute angular frequency for each dimension in the positional encodings. Exactly one of base and freqs must be None.

        • -

      • scale (float) – The scale used to scale the positions.

        • -

      • offset (int) – The position offset to start at.

        • +

      • scale (float) – The scale used to scale the positions.

        • +

      • offset (int) – The position offset to start at.

      • freqs (array, optional) – Optional frequencies to use with RoPE. If set, the base parameter must be None. Default: None.

      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 d3ef49eeb..44d8ae7c4 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 0.18.0 documentation + mlx.core.fast.scaled_dot_product_attention — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.fast.scaled_dot_product_attention#

      -scaled_dot_product_attention(q: array, k: array, v: array, *, scale: float, mask: array | None = None, stream: None | Stream | Device = None) → array#
      +scaled_dot_product_attention(q: array, k: array, v: array, *, scale: float, mask: array | None = None, stream: None | Stream | Device = None) → array#

      A fast implementation of multi-head attention: O = softmax(Q @ K.T, dim=-1) @ V.

      Supports:

        @@ -889,7 +891,7 @@ and v

      • q (array) – Input query array.

      • k (array) – Input keys array.

      • v (array) – Input values array.

        • -

      • scale (float) – Scale for queries (typically 1.0 / sqrt(q.shape(-1))

        • +

      • scale (float) – Scale for queries (typically 1.0 / sqrt(q.shape(-1))

      • mask (array, optional) – An additive mask to apply to the query-key scores.

      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 dcb9b413d..d7c9b687a 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 0.18.0 documentation + mlx.core.fft.fft — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,16 +873,16 @@ document.write(`

      mlx.core.fft.fft#

      -fft(a: array, n: Optional[int] = None, axis: int = -1, stream: Optional[Union[Stream, Device]] = None) → array#
      +fft(a: array, n: Optional[int] = None, axis: int = -1, stream: Optional[Union[Stream, Device]] = None) → array#

      One dimensional discrete Fourier Transform.

      Parameters:

      • a (array) – The input array.

        • -

      • n (int, optional) – Size of the transformed axis. The +

      • n (int, optional) – Size of the transformed axis. The corresponding axis in the input is truncated or padded with zeros to match n. The default value is a.shape[axis].

        • -

      • axis (int, optional) – Axis along which to perform the FFT. The +

      • axis (int, optional) – Axis along which to perform the FFT. The default is -1.

      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 9638a265d..5aa06395a 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 0.18.0 documentation + mlx.core.fft.fft2 — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
      @@ -871,16 +873,16 @@ document.write(`

      mlx.core.fft.ifft#

      -ifft(a: array, n: Optional[int] = None, axis: int = -1, stream: Optional[Union[Stream, Device]] = None) → array#
      +ifft(a: array, n: Optional[int] = None, axis: int = -1, stream: Optional[Union[Stream, Device]] = None) → array#

      One dimensional inverse discrete Fourier Transform.

      Parameters:

      • a (array) – The input array.

        • -

      • n (int, optional) – Size of the transformed axis. The +

      • n (int, optional) – Size of the transformed axis. The corresponding axis in the input is truncated or padded with zeros to match n. The default value is a.shape[axis].

        • -

      • axis (int, optional) – Axis along which to perform the FFT. The +

      • axis (int, optional) – Axis along which to perform the FFT. The default is -1.

      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 207ccc6af..f04ce539c 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 0.18.0 documentation + mlx.core.fft.ifft2 — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.fft.irfft#

      -irfft(a: array, n: Optional[int] = None, axis: int = -1, stream: Optional[Union[Stream, Device]] = None) → array#
      +irfft(a: array, n: Optional[int] = None, axis: int = -1, stream: Optional[Union[Stream, Device]] = None) → array#

      The inverse of rfft().

      The output has the same shape as the input except along axis in which case it has size n.

      @@ -879,11 +881,11 @@ which case it has size Parameters:

      • a (array) – The input array.

        • -

      • n (int, optional) – Size of the transformed axis. The +

      • n (int, optional) – Size of the transformed axis. The corresponding axis in the input is truncated or padded with zeros to match n // 2 + 1. The default value is a.shape[axis] // 2 + 1.

        • -

      • axis (int, optional) – Axis along which to perform the FFT. The +

      • axis (int, optional) – Axis along which to perform the FFT. The default is -1.

      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 c0d5489a0..c016c65cc 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 0.18.0 documentation + mlx.core.fft.irfft2 — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.fft.irfft2#

      -irfft2(a: array, s: Optional[Sequence[int]] = None, axes: Optional[Sequence[int]] = [-2, -1], stream: Optional[Union[Stream, Device]] = None) → array#
      +irfft2(a: array, s: Optional[Sequence[int]] = None, axes: Optional[Sequence[int]] = [-2, -1], stream: Optional[Union[Stream, Device]] = None) → array#

      The inverse of rfft2().

      Note the input is generally complex. The dimensions of the input specified in axes are padded or truncated to match the sizes @@ -881,12 +883,12 @@ and will have size

      Parameters:

      • a (array) – The input array.

        • -

      • s (list(int), optional) – Sizes of the transformed axes. The +

      • s (list(int), optional) – Sizes of the transformed axes. The corresponding axes in the input are truncated or padded with zeros to match the sizes in s except for the last axis which has size s[-1] // 2 + 1. The default value is the sizes of a along axes.

        • -

      • axes (list(int), optional) – Axes along which to perform the FFT. +

      • axes (list(int), optional) – Axes along which to perform the FFT. The default is [-2, -1].

      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.irfftn.html b/docs/build/html/python/_autosummary/mlx.core.fft.irfftn.html index 7b6ba043b..be6d1daf4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.irfftn.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.irfftn.html @@ -8,7 +8,7 @@ - mlx.core.fft.irfftn — MLX 0.18.0 documentation + mlx.core.fft.irfftn — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.fft.irfftn#

      -irfftn(a: array, s: Optional[Sequence[int]] = None, axes: Optional[Sequence[int]] = None, stream: Optional[Union[Stream, Device]] = None) → array#
      +irfftn(a: array, s: Optional[Sequence[int]] = None, axes: Optional[Sequence[int]] = None, stream: Optional[Union[Stream, Device]] = None) → array#

      The inverse of rfftn().

      Note the input is generally complex. The dimensions of the input specified in axes are padded or truncated to match the sizes @@ -881,11 +883,11 @@ and will have size

      Parameters:

      • a (array) – The input array.

        • -

      • s (list(int), optional) – Sizes of the transformed axes. The +

      • s (list(int), optional) – Sizes of the transformed axes. The corresponding axes in the input are truncated or padded with zeros to match the sizes in s. The default value is the sizes of a along axes.

        • -

      • axes (list(int), optional) – Axes along which to perform the FFT. +

      • axes (list(int), optional) – Axes along which to perform the FFT. The default is None in which case the FFT is over the last len(s) axes or all axes if s is also None.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.rfft.html b/docs/build/html/python/_autosummary/mlx.core.fft.rfft.html index 733cabe5a..7befc5f70 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.rfft.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.rfft.html @@ -8,7 +8,7 @@ - mlx.core.fft.rfft — MLX 0.18.0 documentation + mlx.core.fft.rfft — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.fft.rfft#

      -rfft(a: array, n: Optional[int] = None, axis: int = -1, stream: Optional[Union[Stream, Device]] = None) → array#
      +rfft(a: array, n: Optional[int] = None, axis: int = -1, stream: Optional[Union[Stream, Device]] = None) → array#

      One dimensional discrete Fourier Transform on a real input.

      The output has the same shape as the input except along axis in which case it has size n // 2 + 1.

      @@ -880,10 +882,10 @@ which case it has size

      • a (array) – The input array. If the array is complex it will be silently cast to a real type.

        • -

      • n (int, optional) – Size of the transformed axis. The +

      • n (int, optional) – Size of the transformed axis. The corresponding axis in the input is truncated or padded with zeros to match n. The default value is a.shape[axis].

        • -

      • axis (int, optional) – Axis along which to perform the FFT. The +

      • axis (int, optional) – Axis along which to perform the FFT. The default is -1.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.rfft2.html b/docs/build/html/python/_autosummary/mlx.core.fft.rfft2.html index fd6b61c44..9db365d09 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.rfft2.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.rfft2.html @@ -8,7 +8,7 @@ - mlx.core.fft.rfft2 — MLX 0.18.0 documentation + mlx.core.fft.rfft2 — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.fft.rfft2#

      -rfft2(a: array, s: Optional[Sequence[int]] = None, axes: Optional[Sequence[int]] = [-2, -1], stream: Optional[Union[Stream, Device]] = None) → array#
      +rfft2(a: array, s: Optional[Sequence[int]] = None, axes: Optional[Sequence[int]] = [-2, -1], stream: Optional[Union[Stream, Device]] = None) → array#

      Two dimensional real discrete Fourier Transform.

      The output has the same shape as the input except along the dimensions in axes in which case it has sizes from s. The last axis in axes is @@ -881,11 +883,11 @@ treated as the real axis and will have size

      • a (array) – The input array. If the array is complex it will be silently cast to a real type.

        • -

      • s (list(int), optional) – Sizes of the transformed axes. The +

      • s (list(int), optional) – Sizes of the transformed axes. The corresponding axes in the input are truncated or padded with zeros to match the sizes in s. The default value is the sizes of a along axes.

        • -

      • axes (list(int), optional) – Axes along which to perform the FFT. +

      • axes (list(int), optional) – Axes along which to perform the FFT. The default is [-2, -1].

      diff --git a/docs/build/html/python/_autosummary/mlx.core.fft.rfftn.html b/docs/build/html/python/_autosummary/mlx.core.fft.rfftn.html index 1d969350c..d9b451a5b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.fft.rfftn.html +++ b/docs/build/html/python/_autosummary/mlx.core.fft.rfftn.html @@ -8,7 +8,7 @@ - mlx.core.fft.rfftn — MLX 0.18.0 documentation + mlx.core.fft.rfftn — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.fft.rfftn#

      -rfftn(a: array, s: Optional[Sequence[int]] = None, axes: Optional[Sequence[int]] = None, stream: Optional[Union[Stream, Device]] = None) → array#
      +rfftn(a: array, s: Optional[Sequence[int]] = None, axes: Optional[Sequence[int]] = None, stream: Optional[Union[Stream, Device]] = None) → array#

      n-dimensional real discrete Fourier Transform.

      The output has the same shape as the input except along the dimensions in axes in which case it has sizes from s. The last axis in axes is @@ -881,11 +883,11 @@ treated as the real axis and will have size

      • a (array) – The input array. If the array is complex it will be silently cast to a real type.

        • -

      • s (list(int), optional) – Sizes of the transformed axes. The +

      • s (list(int), optional) – Sizes of the transformed axes. The corresponding axes in the input are truncated or padded with zeros to match the sizes in s. The default value is the sizes of a along axes.

        • -

      • axes (list(int), optional) – Axes along which to perform the FFT. +

      • axes (list(int), optional) – Axes along which to perform the FFT. The default is None in which case the FFT is over the last len(s) axes or all axes if s is also None.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.flatten.html b/docs/build/html/python/_autosummary/mlx.core.flatten.html index fc54b7563..566d88890 100644 --- a/docs/build/html/python/_autosummary/mlx.core.flatten.html +++ b/docs/build/html/python/_autosummary/mlx.core.flatten.html @@ -8,7 +8,7 @@ - mlx.core.flatten — MLX 0.18.0 documentation + mlx.core.flatten — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.flatten#

      -flatten(a: array, /, start_axis: int = 0, end_axis: int = -1, *, stream: None | Stream | Device = None) → array#
      +flatten(a: array, /, start_axis: int = 0, end_axis: int = -1, *, stream: None | Stream | Device = None) → array#

      Flatten an array.

      The axes flattened will be between start_axis and end_axis, inclusive. Negative axes are supported. After converting negative axis to @@ -881,8 +883,8 @@ positive, axes outside the valid range will be clamped to a valid value,

      Parameters:

      • a (array) – Input array.

        • -

      • start_axis (int, optional) – The first dimension to flatten. Defaults to 0.

        • -

      • end_axis (int, optional) – The last dimension to flatten. Defaults to -1.

        • +

      • start_axis (int, optional) – The first dimension to flatten. Defaults to 0.

        • +

      • end_axis (int, optional) – The last dimension to flatten. Defaults to -1.

      • stream (Stream, optional) – Stream or device. Defaults to None in which case the default stream of the default device is used.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.floor.html b/docs/build/html/python/_autosummary/mlx.core.floor.html index e152060f0..0b6e1da01 100644 --- a/docs/build/html/python/_autosummary/mlx.core.floor.html +++ b/docs/build/html/python/_autosummary/mlx.core.floor.html @@ -8,7 +8,7 @@ - mlx.core.floor — MLX 0.18.0 documentation + mlx.core.floor — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
      @@ -871,15 +873,15 @@ document.write(`

      mlx.core.full#

      -full(shape: int | Sequence[int], vals: scalar | array, dtype: Dtype | None = None, *, stream: None | Stream | Device = None) → array#
      +full(shape: int | Sequence[int], vals: scalar | array, dtype: Dtype | None = None, *, stream: None | Stream | Device = None) → array#

      Construct an array with the given value.

      Constructs an array of size shape filled with vals. If vals is an array it must be broadcastable to the given shape.

      Parameters:
        -

      • shape (int or list(int)) – The shape of the output array.

        • -

      • vals (float or int or array) – Values to fill the array with.

        • +

      • shape (int or list(int)) – The shape of the output array.

        • +

      • vals (float or int or array) – Values to fill the array with.

      • dtype (Dtype, optional) – Data type of the output array. If unspecified the output type is inferred from vals.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.gather_mm.html b/docs/build/html/python/_autosummary/mlx.core.gather_mm.html index 7ef11662b..b8fc47750 100644 --- a/docs/build/html/python/_autosummary/mlx.core.gather_mm.html +++ b/docs/build/html/python/_autosummary/mlx.core.gather_mm.html @@ -8,7 +8,7 @@ - mlx.core.gather_mm — MLX 0.18.0 documentation + mlx.core.gather_mm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.gather_mm#

      -gather_mm(a: array, b: array, /, lhs_indices: array, rhs_indices: array, *, stream: None | Stream | Device = None) → array#
      +gather_mm(a: array, b: array, /, lhs_indices: array, rhs_indices: array, *, stream: None | Stream | Device = None) → array#

      Matrix multiplication with matrix-level gather.

      Performs a gather of the operands with the given indices followed by a (possibly batched) matrix multiplication of two arrays. This operation diff --git a/docs/build/html/python/_autosummary/mlx.core.gather_qmm.html b/docs/build/html/python/_autosummary/mlx.core.gather_qmm.html index 871df93a5..39126cb9b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.gather_qmm.html +++ b/docs/build/html/python/_autosummary/mlx.core.gather_qmm.html @@ -8,7 +8,7 @@ - mlx.core.gather_qmm — MLX 0.18.0 documentation + mlx.core.gather_qmm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@

    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.gather_qmm#

      -gather_qmm(x: array, w: array, /, scales: array, biases: array, lhs_indices: array | None = None, rhs_indices: array | None = None, transpose: bool = True, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → array#
      +gather_qmm(x: array, w: array, /, scales: array, biases: array, lhs_indices: array | None = None, rhs_indices: array | None = None, transpose: bool = True, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → array#

      Perform quantized matrix multiplication with matrix-level gather.

      This operation is the quantized equivalent to gather_mm(). Similar to gather_mm(), the indices lhs_indices and @@ -888,12 +890,12 @@ as w

    • biases (array) – The biases to use per group_size elements of w

    • lhs_indices (array, optional) – Integer indices for x. Default: None.

    • rhs_indices (array, optional) – Integer indices for w. Default: None.

      • -

    • transpose (bool, optional) – Defines whether to multiply with the +

    • transpose (bool, optional) – Defines whether to multiply with the transposed w or not, namely whether we are performing x @ w.T or x @ w. Default: True.

      • -

    • group_size (int, optional) – The size of the group in w that +

    • group_size (int, optional) – The size of the group in w that shares a scale and bias. Default: 64.

      • -

    • bits (int, optional) – The number of bits occupied by each element in +

    • bits (int, optional) – The number of bits occupied by each element in w. Default: 4.

    diff --git a/docs/build/html/python/_autosummary/mlx.core.grad.html b/docs/build/html/python/_autosummary/mlx.core.grad.html index 50b3056b8..30f82aee7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.grad.html +++ b/docs/build/html/python/_autosummary/mlx.core.grad.html @@ -8,7 +8,7 @@ - mlx.core.grad — MLX 0.18.0 documentation + mlx.core.grad — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
  • mlx.core.repeat
  • mlx.core.reshape
  • mlx.core.right_shift
    • +
  • mlx.core.roll
  • mlx.core.round
  • mlx.core.rsqrt
  • mlx.core.save
    • @@ -425,6 +426,7 @@
  • mlx.core.random.truncated_normal
  • mlx.core.random.uniform
  • mlx.core.random.laplace
    • +
  • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.grad#

      -grad(fun: Callable, argnums: int | list[int] | None = None, argnames: str | list[str] = []) → Callable#
      +grad(fun: Callable, argnums: int | list[int] | None = None, argnames: str | list[str] = []) → Callable#

      Returns a function which computes the gradient of fun.

      Parameters:
      @@ -879,12 +881,12 @@ document.write(`

    • fun (Callable) – A function which takes a variable number of array or trees of array and returns a scalar output array.

      • -

    • argnums (int or list(int), optional) – Specify the index (or indices) +

    • argnums (int or list(int), optional) – Specify the index (or indices) of the positional arguments of fun to compute the gradient with respect to. If neither argnums nor argnames are provided argnums defaults to 0 indicating fun’s first argument.

      • -

    • argnames (str or list(str), optional) – Specify keyword arguments of +

    • argnames (str or list(str), optional) – Specify keyword arguments of fun to compute gradients with respect to. It defaults to [] so no gradients for keyword arguments by default.

    diff --git a/docs/build/html/python/_autosummary/mlx.core.greater.html b/docs/build/html/python/_autosummary/mlx.core.greater.html index 62d987b66..270aa8da1 100644 --- a/docs/build/html/python/_autosummary/mlx.core.greater.html +++ b/docs/build/html/python/_autosummary/mlx.core.greater.html @@ -8,7 +8,7 @@ - mlx.core.greater — MLX 0.18.0 documentation + mlx.core.greater — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
  • mlx.core.repeat
  • mlx.core.reshape
  • mlx.core.right_shift
    • +
  • mlx.core.roll
  • mlx.core.round
  • mlx.core.rsqrt
  • mlx.core.save
    • @@ -425,6 +426,7 @@
  • mlx.core.random.truncated_normal
  • mlx.core.random.uniform
  • mlx.core.random.laplace
    • +
  • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.greater#

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

      Element-wise greater than.

      Strict greater than on two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.greater_equal.html b/docs/build/html/python/_autosummary/mlx.core.greater_equal.html index 79ea135aa..0efba75c3 100644 --- a/docs/build/html/python/_autosummary/mlx.core.greater_equal.html +++ b/docs/build/html/python/_autosummary/mlx.core.greater_equal.html @@ -8,7 +8,7 @@ - mlx.core.greater_equal — MLX 0.18.0 documentation + mlx.core.greater_equal — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.greater_equal#

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

      Element-wise greater or equal.

      Greater than or equal on two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.hadamard_transform.html b/docs/build/html/python/_autosummary/mlx.core.hadamard_transform.html index c0c863949..7f7e096f0 100644 --- a/docs/build/html/python/_autosummary/mlx.core.hadamard_transform.html +++ b/docs/build/html/python/_autosummary/mlx.core.hadamard_transform.html @@ -8,7 +8,7 @@ - mlx.core.hadamard_transform — MLX 0.18.0 documentation + mlx.core.hadamard_transform — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.hadamard_transform#

      -hadamard_transform(a: array, scale: float | None = None, stream: None | Stream | Device = None) → array#
      +hadamard_transform(a: array, scale: float | None = None, stream: None | Stream | Device = None) → array#

      Perform the Walsh-Hadamard transform along the final axis.

      Equivalent to:

      from scipy.linalg import hadamard
@@ -885,7 +887,7 @@ document.write(`
 
      Parameters:
      
 
        
 
      • a (array) – Input array or scalar.
        • 
-
      • scale (float) – Scale the output by this factor.
+
      • scale (float) – Scale the output by this factor.
 Defaults to 1/sqrt(a.shape[-1]) so that the Hadamard matrix is orthonormal.
        • 
 
      
 
      
diff --git a/docs/build/html/python/_autosummary/mlx.core.identity.html b/docs/build/html/python/_autosummary/mlx.core.identity.html
index 94dcafc90..641a7dda0 100644
--- a/docs/build/html/python/_autosummary/mlx.core.identity.html
+++ b/docs/build/html/python/_autosummary/mlx.core.identity.html
@@ -8,7 +8,7 @@
     
     
 
-    mlx.core.identity — MLX 0.18.0 documentation
+    mlx.core.identity — MLX 0.18.1 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -131,8 +131,8 @@
       
     
     
-    MLX 0.18.0 documentation - Home
-    
+    MLX 0.18.1 documentation - Home
+
      @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,12 +873,12 @@ document.write(`

      mlx.core.identity#

      -identity(n: int, dtype: Dtype | None = float32, *, stream: None | Stream | Device = None) → array#
      +identity(n: int, dtype: Dtype | None = float32, *, stream: None | Stream | Device = None) → array#

      Create a square identity matrix.

      Parameters:
        -

      • n (int) – The number of rows and columns in the output.

        • +

      • n (int) – The number of rows and columns in the output.

      • dtype (Dtype, optional) – Data type of the output array. Defaults to float32.

      • stream (Stream, optional) – Stream or device. Defaults to None.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.inner.html b/docs/build/html/python/_autosummary/mlx.core.inner.html index b672ccbe1..12d56dca4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.inner.html +++ b/docs/build/html/python/_autosummary/mlx.core.inner.html @@ -8,7 +8,7 @@ - mlx.core.inner — MLX 0.18.0 documentation + mlx.core.inner — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.isclose#

      -isclose(a: array, b: array, /, rtol: float = 1e-05, atol: float = 1e-08, *, equal_nan: bool = False, stream: None | Stream | Device = None) → array#
      +isclose(a: array, b: array, /, rtol: float = 1e-05, atol: float = 1e-08, *, equal_nan: bool = False, stream: None | Stream | Device = None) → array#

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

      Infinite values are considered equal if they have the same sign, NaN values are not equal unless equal_nan is True.

      @@ -886,9 +888,9 @@ broadcasting.

      • a (array) – Input array.

      • b (array) – Input array.

        • -

      • rtol (float) – Relative tolerance.

        • -

      • atol (float) – Absolute tolerance.

        • -

      • equal_nan (bool) – If True, NaNs are considered equal. +

      • rtol (float) – Relative tolerance.

        • +

      • atol (float) – Absolute tolerance.

        • +

      • equal_nan (bool) – If True, NaNs are considered equal. Defaults to False.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.isfinite.html b/docs/build/html/python/_autosummary/mlx.core.isfinite.html index a6ab2eeaf..a010baa05 100644 --- a/docs/build/html/python/_autosummary/mlx.core.isfinite.html +++ b/docs/build/html/python/_autosummary/mlx.core.isfinite.html @@ -8,7 +8,7 @@ - mlx.core.isfinite — MLX 0.18.0 documentation + mlx.core.isfinite — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.jvp#

      -jvp(fun: Callable, primals: list[array], tangents: list[array]) → tuple[list[array], list[array]]#
      +jvp(fun: Callable, primals: list[array], tangents: list[array]) → tuple[list[array], list[array]]#

      Compute the Jacobian-vector product.

      This computes the product of the Jacobian of a function fun evaluated at primals with the tangents.

      @@ -880,9 +882,9 @@ at primals

      • fun (Callable) – A function which takes a variable number of array and returns a single array or list of array.

        • -

      • primals (list(array)) – A list of array at which to +

      • primals (list(array)) – A list of array at which to evaluate the Jacobian.

        • -

      • tangents (list(array)) – A list of array which are the +

      • tangents (list(array)) – A list of array which are the “vector” in the Jacobian-vector product. The tangents should be the same in number, shape, and type as the inputs of fun (i.e. the primals).

      @@ -892,7 +894,7 @@ same in number, shape, and type as the inputs of fun.

      Return type:
      -

      list(array)

      +

      list(array)

      diff --git a/docs/build/html/python/_autosummary/mlx.core.left_shift.html b/docs/build/html/python/_autosummary/mlx.core.left_shift.html index 0d8f5d678..8e43b1c65 100644 --- a/docs/build/html/python/_autosummary/mlx.core.left_shift.html +++ b/docs/build/html/python/_autosummary/mlx.core.left_shift.html @@ -8,7 +8,7 @@ - mlx.core.left_shift — MLX 0.18.0 documentation + mlx.core.left_shift — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.left_shift#

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

      Element-wise left shift.

      Shift the bits of the first input to the left by the second using numpy-style broadcasting semantics. Either or both input arrays can diff --git a/docs/build/html/python/_autosummary/mlx.core.less.html b/docs/build/html/python/_autosummary/mlx.core.less.html index 79f405ced..4f2ab6ff4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.less.html +++ b/docs/build/html/python/_autosummary/mlx.core.less.html @@ -8,7 +8,7 @@ - mlx.core.less — MLX 0.18.0 documentation + mlx.core.less — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@

    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.less#

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

      Element-wise less than.

      Strict less than on two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.less_equal.html b/docs/build/html/python/_autosummary/mlx.core.less_equal.html index f8231dcf7..356973488 100644 --- a/docs/build/html/python/_autosummary/mlx.core.less_equal.html +++ b/docs/build/html/python/_autosummary/mlx.core.less_equal.html @@ -8,7 +8,7 @@ - mlx.core.less_equal — MLX 0.18.0 documentation + mlx.core.less_equal — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.less_equal#

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

      Element-wise less than or equal.

      Less than or equal on two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.cholesky.html b/docs/build/html/python/_autosummary/mlx.core.linalg.cholesky.html index 168d94844..263fd99d8 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.cholesky.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.cholesky.html @@ -8,7 +8,7 @@ - mlx.core.linalg.cholesky — MLX 0.18.0 documentation + mlx.core.linalg.cholesky — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.linalg.cholesky#

      -cholesky(a: array, upper: bool = False, *, stream: None | Stream | Device = None) → array#
      +cholesky(a: array, upper: bool = False, *, stream: None | Stream | Device = None) → array#

      Compute the Cholesky decomposition of a real symmetric positive semi-definite matrix.

      This function supports arrays with at least 2 dimensions. When the input has more than two dimensions, the Cholesky decomposition is computed for each matrix @@ -881,7 +883,7 @@ in the last two dimensions of Parameters:

      • a (array) – Input array.

        • -

      • upper (bool, optional) – If True, return the upper triangular Cholesky factor. +

      • upper (bool, optional) – If True, return the upper triangular Cholesky factor. If False, return the lower triangular Cholesky factor. Default: False.

      • stream (Stream, optional) – Stream or device. Defaults to None in which case the default stream of the default device is used.

        • diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.cholesky_inv.html b/docs/build/html/python/_autosummary/mlx.core.linalg.cholesky_inv.html index 539dec0c5..70347cbc2 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.cholesky_inv.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.cholesky_inv.html @@ -8,7 +8,7 @@ - mlx.core.linalg.cholesky_inv — MLX 0.18.0 documentation + mlx.core.linalg.cholesky_inv — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -426,6 +427,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -872,7 +874,7 @@ document.write(`

        mlx.core.linalg.cholesky_inv#

        -cholesky_inv(L: array, upper: bool = False, *, stream: None | Stream | Device = None) → array#
        +cholesky_inv(L: array, upper: bool = False, *, stream: None | Stream | Device = None) → array#

        Compute the inverse of a real symmetric positive semi-definite matrix using it’s Cholesky decomposition.

        Let \(\mathbf{A}\) be a real symmetric positive semi-definite matrix and \(\mathbf{L}\) its Cholesky decomposition such that:

        @@ -888,7 +890,7 @@ in the last two dimensions of \(\math
        Parameters:

        • L (array) – Input array.

          • -

        • upper (bool, optional) – If True, return the upper triangular Cholesky factor. +

        • upper (bool, optional) – If True, return the upper triangular Cholesky factor. If False, return the lower triangular Cholesky factor. Default: False.

        • stream (Stream, optional) – Stream or device. Defaults to None in which case the default stream of the default device is used.

          • diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.cross.html b/docs/build/html/python/_autosummary/mlx.core.linalg.cross.html index e5d93f981..f7320129d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.cross.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.cross.html @@ -8,7 +8,7 @@ - mlx.core.linalg.cross — MLX 0.18.0 documentation + mlx.core.linalg.cross — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.core.linalg.cross#

          -cross(a: array, b: array, axis: int = -1, *, stream: None | Stream | Device = None) → array#
          +cross(a: array, b: array, axis: int = -1, *, stream: None | Stream | Device = None) → array#

          Compute the cross product of two arrays along a specified axis.

          The cross product is defined for arrays with size 2 or 3 in the specified axis. If the size is 2 then the third value is assumed @@ -881,7 +883,7 @@ to be zero.

          • a (array) – Input array.

          • b (array) – Input array.

            • -

          • axis (int, optional) – Axis along which to compute the cross +

          • axis (int, optional) – Axis along which to compute the cross product. Default: -1.

          • stream (Stream, optional) – Stream or device. Defaults to None in which case the default stream of the default device is used.

            • diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.inv.html b/docs/build/html/python/_autosummary/mlx.core.linalg.inv.html index cd3a365fa..2118f00df 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.inv.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.inv.html @@ -8,7 +8,7 @@ - mlx.core.linalg.inv — MLX 0.18.0 documentation + mlx.core.linalg.inv — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
          • mlx.core.repeat
          • mlx.core.reshape
          • mlx.core.right_shift
            • +
          • mlx.core.roll
          • mlx.core.round
          • mlx.core.rsqrt
          • mlx.core.save
            • @@ -425,6 +426,7 @@
          • mlx.core.random.truncated_normal
          • mlx.core.random.uniform
          • mlx.core.random.laplace
            • +
          • mlx.core.random.permutation
        • Transforms
            @@ -871,7 +873,7 @@ document.write(`

            mlx.core.linalg.inv#

            -inv(a: array, *, stream: None | Stream | Device = None) → array#
            +inv(a: array, *, stream: None | Stream | Device = None) → array#

            Compute the inverse of a square matrix.

            This function supports arrays with at least 2 dimensions. When the input has more than two dimensions, the inverse is computed for each matrix diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.norm.html b/docs/build/html/python/_autosummary/mlx.core.linalg.norm.html index 9024683e5..834e4bb6b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.norm.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.norm.html @@ -8,7 +8,7 @@ - mlx.core.linalg.norm — MLX 0.18.0 documentation + mlx.core.linalg.norm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@

          • mlx.core.repeat
          • mlx.core.reshape
          • mlx.core.right_shift
            • +
          • mlx.core.roll
          • mlx.core.round
          • mlx.core.rsqrt
          • mlx.core.save
            • @@ -426,6 +427,7 @@
          • mlx.core.random.truncated_normal
          • mlx.core.random.uniform
          • mlx.core.random.laplace
            • +
          • mlx.core.random.permutation
        • Transforms
            @@ -872,7 +874,7 @@ document.write(`

            mlx.core.linalg.norm#

            -norm(a: array, /, ord: None | int | float | str = None, axis: None | int | list[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
            +norm(a: array, /, ord: None | int | float | str = None, axis: None | int | list[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

            Matrix or vector norm.

            This function computes vector or matrix norms depending on the value of the ord and axis parameters.

            @@ -882,16 +884,16 @@ the ord

            a (array) – Input array. If axis is None, a must be 1-D or 2-D, unless ord is None. If both axis and ord are None, the 2-norm of a.flatten will be returned.

            -

          • ord (int, float or str, optional) – Order of the norm (see table under Notes). +

          • ord (int, float or str, optional) – Order of the norm (see table under Notes). If None, the 2-norm (or Frobenius norm for matrices) will be computed along the given axis. Default: None.

            • -

          • axis (int or list(int), optional) – If axis is an integer, it specifies the +

          • axis (int or list(int), optional) – If axis is an integer, it specifies the axis of a along which to compute the vector norms. If axis is a 2-tuple, it specifies the axes that hold 2-D matrices, and the matrix norms of these matrices are computed. If axis is None then either a vector norm (when a is 1-D) or a matrix norm (when a is 2-D) is returned. Default: None.

            • -

          • keepdims (bool, optional) – If True, the axes which are normed over are +

          • keepdims (bool, optional) – If True, the axes which are normed over are left in the result as dimensions with size one. Default False.

          • diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.qr.html b/docs/build/html/python/_autosummary/mlx.core.linalg.qr.html index 773c7ff55..1f382f309 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.qr.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.qr.html @@ -8,7 +8,7 @@ - mlx.core.linalg.qr — MLX 0.18.0 documentation + mlx.core.linalg.qr — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.core.linalg.qr#

          -qr(a: array, *, stream: None | Stream | Device = None)#
          +qr(a: array, *, stream: None | Stream | Device = None)#

          The QR factorization of the input matrix.

          This function supports arrays with at least 2 dimensions. The matrices which are factorized are assumed to be in the last two dimensions of @@ -888,7 +890,7 @@ in which case the default stream of the default device is used.

          The Q and R matrices.

          Return type:
          -

          tuple(array, array)

          +

          tuple(array, array)

          Example

          diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.svd.html b/docs/build/html/python/_autosummary/mlx.core.linalg.svd.html index c3f45c964..f7ee98201 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.svd.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.svd.html @@ -8,7 +8,7 @@ - mlx.core.linalg.svd — MLX 0.18.0 documentation + mlx.core.linalg.svd — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.core.linalg.svd#

          -svd(a: array, *, stream: None | Stream | Device = None)#
          +svd(a: array, *, stream: None | Stream | Device = None)#

          The Singular Value Decomposition (SVD) of the input matrix.

          This function supports arrays with at least 2 dimensions. When the input has more than two dimensions, the function iterates over all indices of the first @@ -889,7 +891,7 @@ in which case the default stream of the default device is used.

          A = U @ diag(S) @ Vt

          Return type:
          -

          tuple(array, array, array)

          +

          tuple(array, array, array)

        • diff --git a/docs/build/html/python/_autosummary/mlx.core.linalg.tri_inv.html b/docs/build/html/python/_autosummary/mlx.core.linalg.tri_inv.html index 44f8687d5..3de2d671d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linalg.tri_inv.html +++ b/docs/build/html/python/_autosummary/mlx.core.linalg.tri_inv.html @@ -8,7 +8,7 @@ - mlx.core.linalg.tri_inv — MLX 0.18.0 documentation + mlx.core.linalg.tri_inv — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.linalg.tri_inv#

        -tri_inv(a: array, upper: bool = False, *, stream: None | Stream | Device = None) → array#
        +tri_inv(a: array, upper: bool = False, *, stream: None | Stream | Device = None) → array#

        Compute the inverse of a triangular square matrix.

        This function supports arrays with at least 2 dimensions. When the input has more than two dimensions, the inverse is computed for each matrix diff --git a/docs/build/html/python/_autosummary/mlx.core.linspace.html b/docs/build/html/python/_autosummary/mlx.core.linspace.html index 2965bd13d..cba457235 100644 --- a/docs/build/html/python/_autosummary/mlx.core.linspace.html +++ b/docs/build/html/python/_autosummary/mlx.core.linspace.html @@ -8,7 +8,7 @@ - mlx.core.linspace — MLX 0.18.0 documentation + mlx.core.linspace — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@

      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,14 +873,14 @@ document.write(`

        mlx.core.linspace#

        -linspace(start, stop, num: int | None = 50, dtype: Dtype | None = float32, stream: None | Stream | Device = None) → array#
        +linspace(start, stop, num: int | None = 50, dtype: Dtype | None = float32, stream: None | Stream | Device = None) → array#

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

        Parameters:

        • start (scalar) – Starting value.

        • stop (scalar) – Stopping value.

          • -

        • num (int, optional) – Number of samples, defaults to 50.

          • +

        • num (int, optional) – Number of samples, defaults to 50.

        • dtype (Dtype, optional) – Specifies the data type of the output, default to float32.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.load.html b/docs/build/html/python/_autosummary/mlx.core.load.html index ff5b3b2f7..6702c0ad3 100644 --- a/docs/build/html/python/_autosummary/mlx.core.load.html +++ b/docs/build/html/python/_autosummary/mlx.core.load.html @@ -8,7 +8,7 @@ - mlx.core.load — MLX 0.18.0 documentation + mlx.core.load — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,18 +873,18 @@ document.write(`

        mlx.core.load#

        -load(file: str, /, format: str | None = None, return_metadata: bool = False, *, stream: None | Stream | Device = None) → array | dict[str, array]#
        +load(file: str, /, format: str | None = None, return_metadata: bool = False, *, stream: None | Stream | Device = None) → array | dict[str, array]#

        Load array(s) from a binary file.

        The supported formats are .npy, .npz, .safetensors, and .gguf.

        Parameters:
          -

        • file (file, str) – File in which the array is saved.

          • -

        • format (str, optional) – Format of the file. If None, the +

        • file (file, str) – File in which the array is saved.

          • +

        • format (str, optional) – Format of the file. If None, the format is inferred from the file extension. Supported formats: npy, npz, and safetensors. Default: None.

          • -

        • return_metadata (bool, optional) – Load the metadata for formats +

        • return_metadata (bool, optional) – Load the metadata for formats which support matadata. The metadata will be returned as an additional dictionary. Default: False.

        @@ -894,7 +896,7 @@ mapping names to arrays if loading from a Return type: -

        array or dict

        +

        array or dict

        diff --git a/docs/build/html/python/_autosummary/mlx.core.log.html b/docs/build/html/python/_autosummary/mlx.core.log.html index 1bccbd86a..b1c0fd595 100644 --- a/docs/build/html/python/_autosummary/mlx.core.log.html +++ b/docs/build/html/python/_autosummary/mlx.core.log.html @@ -8,7 +8,7 @@ - mlx.core.log — MLX 0.18.0 documentation + mlx.core.log — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
        @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
    • Transforms
    • Transforms
    • Transforms
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.logaddexp#

        -logaddexp(a: scalar | array, b: scalar | array, /, *, stream: None | Stream | Device = None) → array#
        +logaddexp(a: scalar | array, b: scalar | array, /, *, stream: None | Stream | Device = None) → array#

        Element-wise log-add-exp.

        This is a numerically stable log-add-exp of two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.logical_and.html b/docs/build/html/python/_autosummary/mlx.core.logical_and.html index c7bc433ec..2557f028b 100644 --- a/docs/build/html/python/_autosummary/mlx.core.logical_and.html +++ b/docs/build/html/python/_autosummary/mlx.core.logical_and.html @@ -8,7 +8,7 @@ - mlx.core.logical_and — MLX 0.18.0 documentation + mlx.core.logical_and — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
    • Transforms
    • Transforms
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.logsumexp#

        -logsumexp(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
        +logsumexp(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

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

        The log-sum-exp reduction is a numerically stable version of:

        log(sum(exp(a), axis))
@@ -881,10 +883,10 @@ document.write(`
 
        Parameters:
        
 
          
 
        • a (array) – Input array.
          • 
-
        • axis (int or list(int), optional) – Optional axis or
+
        • axis (int or list(int), optional) – Optional axis or
 axes to reduce over. If unspecified this defaults
 to reducing over the entire array.
          • 
-
        • keepdims (bool, optional) – Keep reduced axes as
+
        • keepdims (bool, optional) – Keep reduced axes as
 singleton dimensions, defaults to False.
          • 
 
        
 
        
diff --git a/docs/build/html/python/_autosummary/mlx.core.matmul.html b/docs/build/html/python/_autosummary/mlx.core.matmul.html
index 9e50c8f62..efb03c5de 100644
--- a/docs/build/html/python/_autosummary/mlx.core.matmul.html
+++ b/docs/build/html/python/_autosummary/mlx.core.matmul.html
@@ -8,7 +8,7 @@
     
     
 
-    mlx.core.matmul — MLX 0.18.0 documentation
+    mlx.core.matmul — MLX 0.18.1 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -131,8 +131,8 @@
       
     
     
-    MLX 0.18.0 documentation - Home
-    
+    MLX 0.18.1 documentation - Home
+
        @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
    • Transforms
        @@ -871,16 +873,16 @@ document.write(`

        mlx.core.max#

        -max(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
        +max(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

        A max reduction over the given axes.

        Parameters:

        • a (array) – Input array.

          • -

        • axis (int or list(int), optional) – Optional axis or +

        • axis (int or list(int), optional) – Optional axis or axes to reduce over. If unspecified this defaults to reducing over the entire array.

          • -

        • keepdims (bool, optional) – Keep reduced axes as +

        • keepdims (bool, optional) – Keep reduced axes as singleton dimensions, defaults to False.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.maximum.html b/docs/build/html/python/_autosummary/mlx.core.maximum.html index 8916ca9c9..fb10c777d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.maximum.html +++ b/docs/build/html/python/_autosummary/mlx.core.maximum.html @@ -8,7 +8,7 @@ - mlx.core.maximum — MLX 0.18.0 documentation + mlx.core.maximum — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.maximum#

        -maximum(a: scalar | array, b: scalar | array, /, *, stream: None | Stream | Device = None) → array#
        +maximum(a: scalar | array, b: scalar | array, /, *, stream: None | Stream | Device = None) → array#

        Element-wise maximum.

        Take the element-wise max of two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.mean.html b/docs/build/html/python/_autosummary/mlx.core.mean.html index e37032d5b..8b425a562 100644 --- a/docs/build/html/python/_autosummary/mlx.core.mean.html +++ b/docs/build/html/python/_autosummary/mlx.core.mean.html @@ -8,7 +8,7 @@ - mlx.core.mean — MLX 0.18.0 documentation + mlx.core.mean — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,16 +873,16 @@ document.write(`

        mlx.core.mean#

        -mean(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
        +mean(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

        Compute the mean(s) over the given axes.

        Parameters:

        • a (array) – Input array.

          • -

        • axis (int or list(int), optional) – Optional axis or +

        • axis (int or list(int), optional) – Optional axis or axes to reduce over. If unspecified this defaults to reducing over the entire array.

          • -

        • keepdims (bool, optional) – Keep reduced axes as +

        • keepdims (bool, optional) – Keep reduced axes as singleton dimensions, defaults to False.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.meshgrid.html b/docs/build/html/python/_autosummary/mlx.core.meshgrid.html index ab1bfd649..82c9509d7 100644 --- a/docs/build/html/python/_autosummary/mlx.core.meshgrid.html +++ b/docs/build/html/python/_autosummary/mlx.core.meshgrid.html @@ -8,7 +8,7 @@ - mlx.core.meshgrid — MLX 0.18.0 documentation + mlx.core.meshgrid — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,16 +873,16 @@ document.write(`

        mlx.core.meshgrid#

        -meshgrid(*arrays: array, sparse: bool | None = False, indexing: str | None = 'xy', stream: None | Stream | Device = None) → array#
        +meshgrid(*arrays: array, sparse: bool | None = False, indexing: str | None = 'xy', stream: None | Stream | Device = None) → array#

        Generate multidimensional coordinate grids from 1-D coordinate arrays

        Parameters:

        • arrays (array) – Input arrays.

          • -

        • sparse (bool, optional) – If True, a sparse grid is returned in which each output +

        • sparse (bool, optional) – If True, a sparse grid is returned in which each output array has a single non-zero element. If False, a dense grid is returned. Defaults to False.

          • -

        • indexing (str, optional) – Cartesian (‘xy’) or matrix (‘ij’) indexing of the output arrays. +

        • indexing (str, optional) – Cartesian (‘xy’) or matrix (‘ij’) indexing of the output arrays. Defaults to 'xy'.

        @@ -888,7 +890,7 @@ Defaults to 'xy'

        The output arrays.

        Return type:
        -

        list(array)

        +

        list(array)

      • diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.clear_cache.html b/docs/build/html/python/_autosummary/mlx.core.metal.clear_cache.html index c77cf73b1..5d073fd23 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.clear_cache.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.clear_cache.html @@ -8,7 +8,7 @@ - mlx.core.metal.clear_cache — MLX 0.18.0 documentation + mlx.core.metal.clear_cache — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.clear_cache#

      -clear_cache() → None#
      +clear_cache() → None#

      Clear the memory cache.

      After calling this, get_cache_memory() should return 0.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.device_info.html b/docs/build/html/python/_autosummary/mlx.core.metal.device_info.html index 17cf89155..0499ca774 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.device_info.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.device_info.html @@ -8,7 +8,7 @@ - mlx.core.metal.device_info — MLX 0.18.0 documentation + mlx.core.metal.device_info — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.device_info#

      -device_info() → dict[str, Union[str, int]]#
      +device_info() → dict[str, Union[str, int]]#

      Get information about the GPU device and system settings.

      Currently returns:

        @@ -885,7 +887,7 @@ document.write(`

        A dictionary with string keys and string or integer values.

        Return type:
        -

        dict

        +

        dict

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.get_active_memory.html b/docs/build/html/python/_autosummary/mlx.core.metal.get_active_memory.html index 2a0b6b9ce..ebbfa5b59 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.get_active_memory.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.get_active_memory.html @@ -8,7 +8,7 @@ - mlx.core.metal.get_active_memory — MLX 0.18.0 documentation + mlx.core.metal.get_active_memory — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.get_active_memory#

      -get_active_memory() → int#
      +get_active_memory() → int#

      Get the actively used memory in bytes.

      Note, this will not always match memory use reported by the system because it does not include cached memory buffers.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.get_cache_memory.html b/docs/build/html/python/_autosummary/mlx.core.metal.get_cache_memory.html index 26a3944cd..5822bc78f 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.get_cache_memory.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.get_cache_memory.html @@ -8,7 +8,7 @@ - mlx.core.metal.get_cache_memory — MLX 0.18.0 documentation + mlx.core.metal.get_cache_memory — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.get_cache_memory#

      -get_cache_memory() → int#
      +get_cache_memory() → int#

      Get the cache size in bytes.

      The cache includes memory not currently used that has not been returned to the system allocator.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.get_peak_memory.html b/docs/build/html/python/_autosummary/mlx.core.metal.get_peak_memory.html index 19e1cc52b..4400384db 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.get_peak_memory.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.get_peak_memory.html @@ -8,7 +8,7 @@ - mlx.core.metal.get_peak_memory — MLX 0.18.0 documentation + mlx.core.metal.get_peak_memory — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.get_peak_memory#

      -get_peak_memory() → int#
      +get_peak_memory() → int#

      Get the peak amount of used memory in bytes.

      The maximum memory used recorded from the beginning of the program execution or since the last call to reset_peak_memory().

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.is_available.html b/docs/build/html/python/_autosummary/mlx.core.metal.is_available.html index 319a102cf..d23fb1141 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.is_available.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.is_available.html @@ -8,7 +8,7 @@ - mlx.core.metal.is_available — MLX 0.18.0 documentation + mlx.core.metal.is_available — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.is_available#

      -is_available() → bool#
      +is_available() → bool#

      Check if the Metal back-end is available.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.reset_peak_memory.html b/docs/build/html/python/_autosummary/mlx.core.metal.reset_peak_memory.html index fad1e75be..137f6e83e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.reset_peak_memory.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.reset_peak_memory.html @@ -8,7 +8,7 @@ - mlx.core.metal.reset_peak_memory — MLX 0.18.0 documentation + mlx.core.metal.reset_peak_memory — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.reset_peak_memory#

      -reset_peak_memory() → None#
      +reset_peak_memory() → None#

      Reset the peak memory to zero.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.set_cache_limit.html b/docs/build/html/python/_autosummary/mlx.core.metal.set_cache_limit.html index b4f89d102..bf680cd3d 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.set_cache_limit.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.set_cache_limit.html @@ -8,7 +8,7 @@ - mlx.core.metal.set_cache_limit — MLX 0.18.0 documentation + mlx.core.metal.set_cache_limit — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.set_cache_limit#

      -set_cache_limit(limit: int) → int#
      +set_cache_limit(limit: int) → int#

      Set the free cache limit.

      If using more than the given limit, free memory will be reclaimed from the cache on the next allocation. To disable the cache, set @@ -880,13 +882,13 @@ the limit to 0set_memory_limit() for more details.

      Parameters:
      -

      limit (int) – The cache limit in bytes.

      +

      limit (int) – The cache limit in bytes.

      Returns:

      The previous cache limit in bytes.

      Return type:
      -

      int

      +

      int

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.set_memory_limit.html b/docs/build/html/python/_autosummary/mlx.core.metal.set_memory_limit.html index c84e2e161..486b6548c 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.set_memory_limit.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.set_memory_limit.html @@ -8,7 +8,7 @@ - mlx.core.metal.set_memory_limit — MLX 0.18.0 documentation + mlx.core.metal.set_memory_limit — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.metal.set_memory_limit#

      -set_memory_limit(limit: int, *, relaxed: bool = True) → int#
      +set_memory_limit(limit: int, *, relaxed: bool = True) → int#

      Set the memory limit.

      Memory allocations will wait on scheduled tasks to complete if the limit is exceeded. If there are no more scheduled tasks an error will be raised @@ -882,8 +884,8 @@ size reported by the device.

      Parameters:
        -

      • limit (int) – Memory limit in bytes.

        • -

      • relaxed (bool, optional) – If False` an error is raised if the limit +

      • limit (int) – Memory limit in bytes.

        • +

      • relaxed (bool, optional) – If False` an error is raised if the limit is exceeded. Default: True

      @@ -891,7 +893,7 @@ is exceeded. Default:

      The previous memory limit in bytes.

      Return type:
      -

      int

      +

      int

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.start_capture.html b/docs/build/html/python/_autosummary/mlx.core.metal.start_capture.html index 6cd57a0a6..e23d2162e 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.start_capture.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.start_capture.html @@ -8,7 +8,7 @@ - mlx.core.metal.start_capture — MLX 0.18.0 documentation + mlx.core.metal.start_capture — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,11 +873,11 @@ document.write(`

      mlx.core.metal.start_capture#

      -start_capture(path: str) → None#
      +start_capture(path: str) → None#

      Start a Metal capture.

      Parameters:
      -

      path (str) – The path to save the capture which should have +

      path (str) – The path to save the capture which should have the extension .gputrace.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.metal.stop_capture.html b/docs/build/html/python/_autosummary/mlx.core.metal.stop_capture.html index e309c6f23..f6925aacd 100644 --- a/docs/build/html/python/_autosummary/mlx.core.metal.stop_capture.html +++ b/docs/build/html/python/_autosummary/mlx.core.metal.stop_capture.html @@ -8,7 +8,7 @@ - mlx.core.metal.stop_capture — MLX 0.18.0 documentation + mlx.core.metal.stop_capture — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
      @@ -871,16 +873,16 @@ document.write(`

      mlx.core.min#

      -min(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
      +min(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

      A min reduction over the given axes.

      Parameters:

      • a (array) – Input array.

        • -

      • axis (int or list(int), optional) – Optional axis or +

      • axis (int or list(int), optional) – Optional axis or axes to reduce over. If unspecified this defaults to reducing over the entire array.

        • -

      • keepdims (bool, optional) – Keep reduced axes as +

      • keepdims (bool, optional) – Keep reduced axes as singleton dimensions, defaults to False.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.minimum.html b/docs/build/html/python/_autosummary/mlx.core.minimum.html index 8bba7e6f6..1c3ae10d5 100644 --- a/docs/build/html/python/_autosummary/mlx.core.minimum.html +++ b/docs/build/html/python/_autosummary/mlx.core.minimum.html @@ -8,7 +8,7 @@ - mlx.core.minimum — MLX 0.18.0 documentation + mlx.core.minimum — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.minimum#

      -minimum(a: scalar | array, b: scalar | array, /, *, stream: None | Stream | Device = None) → array#
      +minimum(a: scalar | array, b: scalar | array, /, *, stream: None | Stream | Device = None) → array#

      Element-wise minimum.

      Take the element-wise min of two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.moveaxis.html b/docs/build/html/python/_autosummary/mlx.core.moveaxis.html index ee07629e7..61c0b753a 100644 --- a/docs/build/html/python/_autosummary/mlx.core.moveaxis.html +++ b/docs/build/html/python/_autosummary/mlx.core.moveaxis.html @@ -8,7 +8,7 @@ - mlx.core.moveaxis — MLX 0.18.0 documentation + mlx.core.moveaxis — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,14 +873,14 @@ document.write(`

      mlx.core.moveaxis#

      -moveaxis(a: array, /, source: int, destination: int, *, stream: None | Stream | Device = None) → array#
      +moveaxis(a: array, /, source: int, destination: int, *, stream: None | Stream | Device = None) → array#

      Move an axis to a new position.

      Parameters:

      • a (array) – Input array.

        • -

      • source (int) – Specifies the source axis.

        • -

      • destination (int) – Specifies the destination axis.

        • +

      • source (int) – Specifies the source axis.

        • +

      • destination (int) – Specifies the destination axis.

      Returns:
      diff --git a/docs/build/html/python/_autosummary/mlx.core.multiply.html b/docs/build/html/python/_autosummary/mlx.core.multiply.html index 7a2780a1e..254ba9280 100644 --- a/docs/build/html/python/_autosummary/mlx.core.multiply.html +++ b/docs/build/html/python/_autosummary/mlx.core.multiply.html @@ -8,7 +8,7 @@ - mlx.core.multiply — MLX 0.18.0 documentation + mlx.core.multiply — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.multiply#

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

      Element-wise multiplication.

      Multiply two arrays with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.nan_to_num.html b/docs/build/html/python/_autosummary/mlx.core.nan_to_num.html index b4703f1c6..0a71b29d4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.nan_to_num.html +++ b/docs/build/html/python/_autosummary/mlx.core.nan_to_num.html @@ -8,7 +8,7 @@ - mlx.core.nan_to_num — MLX 0.18.0 documentation + mlx.core.nan_to_num — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,17 +873,17 @@ document.write(`

      mlx.core.nan_to_num#

      -nan_to_num(a: scalar | array, nan: float = 0, posinf: float | None = None, neginf: float | None = None, *, stream: None | Stream | Device = None) → array#
      +nan_to_num(a: scalar | array, nan: float = 0, posinf: float | None = None, neginf: float | None = None, *, stream: None | Stream | Device = None) → array#

      Replace NaN and Inf values with finite numbers.

      Parameters:

      • a (array) – Input array

        • -

      • nan (float, optional) – Value to replace NaN with. Default: 0.

        • -

      • posinf (float, optional) – Value to replace positive infinities +

      • nan (float, optional) – Value to replace NaN with. Default: 0.

        • +

      • posinf (float, optional) – Value to replace positive infinities with. If None, defaults to largest finite value for the given data type. Default: None.

        • -

      • neginf (float, optional) – Value to replace negative infinities +

      • neginf (float, optional) – Value to replace negative infinities with. If None, defaults to the negative of the largest finite value for the given data type. Default: None.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.negative.html b/docs/build/html/python/_autosummary/mlx.core.negative.html index 15993b6f5..51477d139 100644 --- a/docs/build/html/python/_autosummary/mlx.core.negative.html +++ b/docs/build/html/python/_autosummary/mlx.core.negative.html @@ -8,7 +8,7 @@ - mlx.core.negative — MLX 0.18.0 documentation + mlx.core.negative — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -871,12 +873,12 @@ document.write(`

      mlx.core.ones#

      -ones(shape: int | Sequence[int], dtype: Dtype | None = float32, *, stream: None | Stream | Device = None) → array#
      +ones(shape: int | Sequence[int], dtype: Dtype | None = float32, *, stream: None | Stream | Device = None) → array#

      Construct an array of ones.

      Parameters:
        -

      • shape (int or list(int)) – The shape of the output array.

        • +

      • shape (int or list(int)) – The shape of the output array.

      • dtype (Dtype, optional) – Data type of the output array. If unspecified the output type defaults to float32.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.ones_like.html b/docs/build/html/python/_autosummary/mlx.core.ones_like.html index 16ca0b6ea..bd2875c65 100644 --- a/docs/build/html/python/_autosummary/mlx.core.ones_like.html +++ b/docs/build/html/python/_autosummary/mlx.core.ones_like.html @@ -8,7 +8,7 @@ - mlx.core.ones_like — MLX 0.18.0 documentation + mlx.core.ones_like — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
      @@ -871,13 +873,13 @@ document.write(`

      mlx.core.pad#

      -pad(a: array, pad_width: int | tuple[int] | tuple[int, int] | list[tuple[int, int]], mode: Literal['constant', 'edge'] = 'constant', constant_values: scalar | array = 0, *, stream: None | Stream | Device = None) → array#
      +pad(a: array, pad_width: int | tuple[int] | tuple[int, int] | list[tuple[int, int]], mode: Literal['constant', 'edge'] = 'constant', constant_values: scalar | array = 0, *, stream: None | Stream | Device = None) → array#

      Pad an array with a constant value

      Parameters:
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.partition#

        -partition(a: array, /, kth: int, axis: None | int = -1, *, stream: None | Stream | Device = None) → array#
        +partition(a: array, /, kth: int, axis: None | int = -1, *, stream: None | Stream | Device = None) → array#

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

        The ordering of the elements in partitions is undefined.

        @@ -879,11 +881,11 @@ elements are first.

        Parameters:

        • a (array) – Input array.

          • -

        • kth (int) – Element at the kth index will be in its sorted +

        • kth (int) – Element at the kth index will be in its sorted position in the output. All elements before the kth index will be less or equal to the kth element and all elements after will be greater or equal to the kth element in the output.

          • -

        • axis (int or None, optional) – Optional axis to partition over. +

        • axis (int or None, optional) – Optional axis to partition over. If None, this partitions over the flattened array. If unspecified, it defaults to -1.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.power.html b/docs/build/html/python/_autosummary/mlx.core.power.html index 20b8791cd..c6e89c8d4 100644 --- a/docs/build/html/python/_autosummary/mlx.core.power.html +++ b/docs/build/html/python/_autosummary/mlx.core.power.html @@ -8,7 +8,7 @@ - mlx.core.power — MLX 0.18.0 documentation + mlx.core.power — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.power#

        -power(a: scalar | array, b: scalar | array, /, *, stream: None | Stream | Device = None) → array#
        +power(a: scalar | array, b: scalar | array, /, *, stream: None | Stream | Device = None) → array#

        Element-wise power operation.

        Raise the elements of a to the powers in elements of b with numpy-style broadcasting semantics. Either or both input arrays can also be scalars.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.prod.html b/docs/build/html/python/_autosummary/mlx.core.prod.html index 7ddaec972..67611ffb6 100644 --- a/docs/build/html/python/_autosummary/mlx.core.prod.html +++ b/docs/build/html/python/_autosummary/mlx.core.prod.html @@ -8,7 +8,7 @@ - mlx.core.prod — MLX 0.18.0 documentation + mlx.core.prod — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,16 +873,16 @@ document.write(`

        mlx.core.prod#

        -prod(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#
        +prod(a: array, /, axis: None | int | Sequence[int] = None, keepdims: bool = False, *, stream: None | Stream | Device = None) → array#

        An product reduction over the given axes.

        Parameters:

        • a (array) – Input array.

          • -

        • axis (int or list(int), optional) – Optional axis or +

        • axis (int or list(int), optional) – Optional axis or axes to reduce over. If unspecified this defaults to reducing over the entire array.

          • -

        • keepdims (bool, optional) – Keep reduced axes as +

        • keepdims (bool, optional) – Keep reduced axes as singleton dimensions, defaults to False.

        diff --git a/docs/build/html/python/_autosummary/mlx.core.put_along_axis.html b/docs/build/html/python/_autosummary/mlx.core.put_along_axis.html index bd172fbbd..6e8752d71 100644 --- a/docs/build/html/python/_autosummary/mlx.core.put_along_axis.html +++ b/docs/build/html/python/_autosummary/mlx.core.put_along_axis.html @@ -8,7 +8,7 @@ - mlx.core.put_along_axis — MLX 0.18.0 documentation + mlx.core.put_along_axis — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.core.put_along_axis#

        -put_along_axis(a: array, /, indices: array, values: array, axis: int | None = None, *, stream: None | Stream | Device = None) → array#
        +put_along_axis(a: array, /, indices: array, values: array, axis: int | None = None, *, stream: None | Stream | Device = None) → array#

        Put values along an axis at the specified indices.

        Parameters:
        @@ -881,7 +883,7 @@ document.write(` the input array excluding the axis dimension.

      • values (array) – Values array. These should be broadcastable with the indices.

        • -

      • axis (int or None) – Axis in the destination to put the values to. If +

      • axis (int or None) – Axis in the destination to put the values to. If axis == None the destination is flattened prior to the put operation.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.quantize.html b/docs/build/html/python/_autosummary/mlx.core.quantize.html index 99121af7d..5d616e948 100644 --- a/docs/build/html/python/_autosummary/mlx.core.quantize.html +++ b/docs/build/html/python/_autosummary/mlx.core.quantize.html @@ -8,7 +8,7 @@ - mlx.core.quantize — MLX 0.18.0 documentation + mlx.core.quantize — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -426,6 +427,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -872,7 +874,7 @@ document.write(`

      mlx.core.quantize#

      -quantize(w: array, /, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → tuple[array, array, array]#
      +quantize(w: array, /, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → tuple[array, array, array]#

      Quantize the matrix w using bits bits per element.

      Note, every group_size elements in a row of w are quantized together. Hence, number of columns of w should be divisible by @@ -904,9 +906,9 @@ save \(s\) and Parameters:

      • w (array) – Matrix to be quantized

        • -

      • group_size (int, optional) – The size of the group in w that shares a +

      • group_size (int, optional) – The size of the group in w that shares a scale and bias. Default: 64.

        • -

      • bits (int, optional) – The number of bits occupied by each element of +

      • bits (int, optional) – The number of bits occupied by each element of w in the returned quantized matrix. Default: 4.

      @@ -920,7 +922,7 @@ scale and bias. Default:
      Return type:
      -

      tuple

      +

      tuple

      diff --git a/docs/build/html/python/_autosummary/mlx.core.quantized_matmul.html b/docs/build/html/python/_autosummary/mlx.core.quantized_matmul.html index 9022ff33d..1e2d47a63 100644 --- a/docs/build/html/python/_autosummary/mlx.core.quantized_matmul.html +++ b/docs/build/html/python/_autosummary/mlx.core.quantized_matmul.html @@ -8,7 +8,7 @@ - mlx.core.quantized_matmul — MLX 0.18.0 documentation + mlx.core.quantized_matmul — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.core.quantized_matmul#

      -quantized_matmul(x: array, w: array, /, scales: array, biases: array, transpose: bool = True, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → array#
      +quantized_matmul(x: array, w: array, /, scales: array, biases: array, transpose: bool = True, group_size: int = 64, bits: int = 4, *, stream: None | Stream | Device = None) → array#

      Perform the matrix multiplication with the quantized matrix w. The quantization uses one floating point scale and bias per group_size of elements. Each element in w takes bits bits and is packed in an @@ -883,12 +885,12 @@ unsigned 32 bit integer.

    • w (array) – Quantized matrix packed in unsigned integers

    • scales (array) – The scales to use per group_size elements of w

    • biases (array) – The biases to use per group_size elements of w

      • -

    • transpose (bool, optional) – Defines whether to multiply with the +

    • transpose (bool, optional) – Defines whether to multiply with the transposed w or not, namely whether we are performing x @ w.T or x @ w. Default: True.

      • -

    • group_size (int, optional) – The size of the group in w that +

    • group_size (int, optional) – The size of the group in w that shares a scale and bias. Default: 64.

      • -

    • bits (int, optional) – The number of bits occupied by each element in +

    • bits (int, optional) – The number of bits occupied by each element in w. Default: 4.

    diff --git a/docs/build/html/python/_autosummary/mlx.core.radians.html b/docs/build/html/python/_autosummary/mlx.core.radians.html index 19edb0b82..bada06ae3 100644 --- a/docs/build/html/python/_autosummary/mlx.core.radians.html +++ b/docs/build/html/python/_autosummary/mlx.core.radians.html @@ -8,7 +8,7 @@ - mlx.core.radians — MLX 0.18.0 documentation + mlx.core.radians — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
  • mlx.core.repeat
  • mlx.core.reshape
  • mlx.core.right_shift
    • +
  • mlx.core.roll
  • mlx.core.round
  • mlx.core.rsqrt
  • mlx.core.save
    • @@ -425,6 +426,7 @@
  • mlx.core.random.truncated_normal
  • mlx.core.random.uniform
  • mlx.core.random.laplace
    • +
  • mlx.core.random.permutation
  • Transforms
  • Transforms
      @@ -871,17 +873,17 @@ document.write(`

      mlx.core.random.bernoulli#

      -bernoulli(p: scalar | array = 0.5, shape: Sequence[int] | None = None, key: array | None = None, stream: None | Stream | Device = None) → array#
      +bernoulli(p: scalar | array = 0.5, shape: Sequence[int] | None = None, key: array | None = None, stream: None | Stream | Device = None) → array#

      Generate Bernoulli random values.

      The values are sampled from the bernoulli distribution with parameter -p. The parameter p can be a float or array and +p. The parameter p can be a float or array and must be broadcastable to shape.

      Parameters:
        -

      • p (float or array, optional) – Parameter of the Bernoulli +

      • p (float or array, optional) – Parameter of the Bernoulli distribution. Default: 0.5.

        • -

      • shape (list(int), optional) – Shape of the output. +

      • shape (list(int), optional) – Shape of the output. Default: p.shape.

      • key (array, optional) – A PRNG key. Default: None.

      diff --git a/docs/build/html/python/_autosummary/mlx.core.random.categorical.html b/docs/build/html/python/_autosummary/mlx.core.random.categorical.html index d771ea599..03a1ff887 100644 --- a/docs/build/html/python/_autosummary/mlx.core.random.categorical.html +++ b/docs/build/html/python/_autosummary/mlx.core.random.categorical.html @@ -8,7 +8,7 @@ - mlx.core.random.categorical — MLX 0.18.0 documentation + mlx.core.random.categorical — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.utils.tree_map_with_path#

      -tree_map_with_path(fn: Callable, tree: Any, *rest: Any, is_leaf: Callable | None = None, path: Any | None = None) → Any#
      +tree_map_with_path(fn: Callable, tree: Any, *rest: Any, is_leaf: Callable | None = None, path: Any | None = None) → Any#

      Applies fn to the path and leaves of the Python tree tree and returns a new collection with the results.

      This function is the same tree_map() but the fn takes the path as @@ -881,7 +883,7 @@ the first argument followed by the remaining tree nodes.

      • fn (callable) – The function that processes the leaves of the tree.

      • tree (Any) – The main Python tree that will be iterated upon.

        • -

      • rest (tuple[Any]) – Extra trees to be iterated together with tree.

        • +

      • rest (tuple[Any]) – Extra trees to be iterated together with tree.

      • is_leaf (callable, optional) – An optional callable that returns True if the passed object is considered a leaf or False otherwise.

      diff --git a/docs/build/html/python/_autosummary/mlx.utils.tree_reduce.html b/docs/build/html/python/_autosummary/mlx.utils.tree_reduce.html index d76ea3278..6a6b9bf37 100644 --- a/docs/build/html/python/_autosummary/mlx.utils.tree_reduce.html +++ b/docs/build/html/python/_autosummary/mlx.utils.tree_reduce.html @@ -8,7 +8,7 @@ - mlx.utils.tree_reduce — MLX 0.18.0 documentation + mlx.utils.tree_reduce — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.utils.tree_unflatten#

      -tree_unflatten(tree: List[Tuple[str, Any]]) → Any#
      +tree_unflatten(tree: List[Tuple[str, Any]]) → Any#

      Recreate a Python tree from its flat representation.

      from mlx.utils import tree_unflatten
 
@@ -882,7 +884,7 @@ document.write(`
      Parameters:
      -

      tree (list[tuple[str, Any]]) – The flat representation of a Python tree. +

      tree (list[tuple[str, Any]]) – The flat representation of a Python tree. For instance as returned by tree_flatten().

      Returns:
      diff --git a/docs/build/html/python/_autosummary/stream_class.html b/docs/build/html/python/_autosummary/stream_class.html index 93385f489..b37dcd94b 100644 --- a/docs/build/html/python/_autosummary/stream_class.html +++ b/docs/build/html/python/_autosummary/stream_class.html @@ -8,7 +8,7 @@ - mlx.core.Stream — MLX 0.18.0 documentation + mlx.core.Stream — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
      @@ -370,6 +370,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -425,6 +426,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
  • Transforms
      @@ -872,7 +874,7 @@ document.write(`

      mlx.nn.AvgPool1d#

      -class AvgPool1d(kernel_size: int | Tuple[int], stride: int | Tuple[int] | None = None, padding: int | Tuple[int] = 0)#
      +class AvgPool1d(kernel_size: int | Tuple[int], stride: int | Tuple[int] | None = None, padding: int | Tuple[int] = 0)#

      Applies 1-dimensional average pooling.

      Assuming an input of shape \((N, L, C)\) and kernel_size is \(k\), the output is a tensor of shape \((N, L_{out}, C)\), given @@ -887,10 +889,10 @@ by:

      Parameters:
        -

      • kernel_size (int or tuple(int)) – The size of the pooling window kernel.

        • -

      • stride (int or tuple(int), optional) – The stride of the pooling window. +

      • kernel_size (int or tuple(int)) – The size of the pooling window kernel.

        • +

      • stride (int or tuple(int), optional) – The stride of the pooling window. Default: kernel_size.

        • -

      • padding (int or tuple(int), optional) – How much zero padding to apply to +

      • padding (int or tuple(int), optional) – How much zero padding to apply to the input. The padding amount is applied to both sides of the spatial axis. Default: 0.

      diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool2d.html index 1ae33d62e..ef691e4cb 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.AvgPool2d.html @@ -8,7 +8,7 @@ - mlx.nn.AvgPool2d — MLX 0.18.0 documentation + mlx.nn.AvgPool2d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -426,6 +427,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -872,7 +874,7 @@ document.write(`

      mlx.nn.AvgPool2d#

      -class AvgPool2d(kernel_size: int | Tuple[int, int], stride: int | Tuple[int, int] | None = None, padding: int | Tuple[int, int] | None = 0)#
      +class AvgPool2d(kernel_size: int | Tuple[int, int], stride: int | Tuple[int, int] | None = None, padding: int | Tuple[int, int] | None = 0)#

      Applies 2-dimensional average pooling.

      Assuming an input of shape \((N, H, W, C)\) and kernel_size is \((k_H, k_W)\), the output is a tensor of shape \((N, H_{out}, @@ -897,10 +899,10 @@ used for the height axis, the second

      Parameters:
        -

      • kernel_size (int or tuple(int, int)) – The size of the pooling window.

        • -

      • stride (int or tuple(int, int), optional) – The stride of the pooling +

      • kernel_size (int or tuple(int, int)) – The size of the pooling window.

        • +

      • stride (int or tuple(int, int), optional) – The stride of the pooling window. Default: kernel_size.

        • -

      • padding (int or tuple(int, int), optional) – How much zero +

      • padding (int or tuple(int, int), optional) – How much zero padding to apply to the input. The padding is applied on both sides of the height and width axis. Default: 0.

      diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.BatchNorm.html b/docs/build/html/python/nn/_autosummary/mlx.nn.BatchNorm.html index b5a7c1b82..69e322de8 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.BatchNorm.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.BatchNorm.html @@ -8,7 +8,7 @@ - mlx.nn.BatchNorm — MLX 0.18.0 documentation + mlx.nn.BatchNorm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -426,6 +427,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
      @@ -872,7 +874,7 @@ document.write(`

      mlx.nn.BatchNorm#

      -class BatchNorm(num_features: int, eps: float = 1e-05, momentum: float = 0.1, affine: bool = True, track_running_stats: bool = True)#
      +class BatchNorm(num_features: int, eps: float = 1e-05, momentum: float = 0.1, affine: bool = True, track_running_stats: bool = True)#

      Applies Batch Normalization over a 2D or 3D input.

      Computes

      @@ -890,14 +892,14 @@ Covariate Shift.

      Parameters:
        -

      • num_features (int) – The feature dimension to normalize over.

        • -

      • eps (float, optional) – A small additive constant for numerical +

      • num_features (int) – The feature dimension to normalize over.

        • +

      • eps (float, optional) – A small additive constant for numerical stability. Default: 1e-5.

        • -

      • momentum (float, optional) – The momentum for updating the running +

      • momentum (float, optional) – The momentum for updating the running mean and variance. Default: 0.1.

        • -

      • affine (bool, optional) – If True, apply a learned affine +

      • affine (bool, optional) – If True, apply a learned affine transformation after the normalization. Default: True.

        • -

      • track_running_stats (bool, optional) – If True, track the +

      • track_running_stats (bool, optional) – If True, track the running mean and variance. Default: True.

      diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.CELU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.CELU.html index 9a02f37bc..c51089e0f 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.CELU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.CELU.html @@ -8,7 +8,7 @@ - mlx.nn.CELU — MLX 0.18.0 documentation + mlx.nn.CELU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
      @@ -371,6 +371,7 @@
    • mlx.core.repeat
    • mlx.core.reshape
    • mlx.core.right_shift
      • +
    • mlx.core.roll
    • mlx.core.round
    • mlx.core.rsqrt
    • mlx.core.save
      • @@ -426,6 +427,7 @@
    • mlx.core.random.truncated_normal
    • mlx.core.random.uniform
    • mlx.core.random.laplace
      • +
    • mlx.core.random.permutation
  • Transforms
  • Transforms
      @@ -871,7 +873,7 @@ document.write(`

      mlx.nn.Conv1d#

      -class Conv1d(in_channels: int, out_channels: int, kernel_size: int, stride: int = 1, padding: int = 0, dilation: int = 1, groups: int = 1, bias: bool = True)#
      +class Conv1d(in_channels: int, out_channels: int, kernel_size: int, stride: int = 1, padding: int = 0, dilation: int = 1, groups: int = 1, bias: bool = True)#

      Applies a 1-dimensional convolution over the multi-channel input sequence.

      The channels are expected to be last i.e. the input shape should be NLC where:

        @@ -882,17 +884,17 @@ document.write(`
        Parameters:
          -

        • in_channels (int) – The number of input channels

          • -

        • out_channels (int) – The number of output channels

          • -

        • kernel_size (int) – The size of the convolution filters

          • -

        • stride (int, optional) – The stride when applying the filter. +

        • in_channels (int) – The number of input channels

          • +

        • out_channels (int) – The number of output channels

          • +

        • kernel_size (int) – The size of the convolution filters

          • +

        • stride (int, optional) – The stride when applying the filter. Default: 1.

          • -

        • padding (int, optional) – How many positions to 0-pad the input with. +

        • padding (int, optional) – How many positions to 0-pad the input with. Default: 0.

          • -

        • dilation (int, optional) – The dilation of the convolution.

          • -

        • groups (int, optional) – The number of groups for the convolution. +

        • dilation (int, optional) – The dilation of the convolution.

          • +

        • groups (int, optional) – The number of groups for the convolution. Default: 1.

          • -

        • bias (bool, optional) – If True add a learnable bias to the output. +

        • bias (bool, optional) – If True add a learnable bias to the output. Default: True

        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv2d.html index 552d09c27..715b41332 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv2d.html @@ -8,7 +8,7 @@ - mlx.nn.Conv2d — MLX 0.18.0 documentation + mlx.nn.Conv2d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
      • mlx.core.repeat
      • mlx.core.reshape
      • mlx.core.right_shift
        • +
      • mlx.core.roll
      • mlx.core.round
      • mlx.core.rsqrt
      • mlx.core.save
        • @@ -425,6 +426,7 @@
      • mlx.core.random.truncated_normal
      • mlx.core.random.uniform
      • mlx.core.random.laplace
        • +
      • mlx.core.random.permutation
    • Transforms
        @@ -871,7 +873,7 @@ document.write(`

        mlx.nn.Conv2d#

        -class Conv2d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, dilation: int | tuple = 1, bias: bool = True)#
        +class Conv2d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, dilation: int | tuple = 1, bias: bool = True)#

        Applies a 2-dimensional convolution over the multi-channel input image.

        The channels are expected to be last i.e. the input shape should be NHWC where:

          @@ -883,15 +885,15 @@ document.write(`
          Parameters:
            -

          • in_channels (int) – The number of input channels.

            • -

          • out_channels (int) – The number of output channels.

            • -

          • kernel_size (int or tuple) – The size of the convolution filters.

            • -

          • stride (int or tuple, optional) – The size of the stride when +

          • in_channels (int) – The number of input channels.

            • +

          • out_channels (int) – The number of output channels.

            • +

          • kernel_size (int or tuple) – The size of the convolution filters.

            • +

          • stride (int or tuple, optional) – The size of the stride when applying the filter. Default: 1.

            • -

          • padding (int or tuple, optional) – How many positions to 0-pad +

          • padding (int or tuple, optional) – How many positions to 0-pad the input with. Default: 0.

            • -

          • dilation (int or tuple, optional) – The dilation of the convolution.

            • -

          • bias (bool, optional) – If True add a learnable bias to the +

          • dilation (int or tuple, optional) – The dilation of the convolution.

            • +

          • bias (bool, optional) – If True add a learnable bias to the output. Default: True

          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv3d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv3d.html index 9e869358c..312e0f3d1 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Conv3d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Conv3d.html @@ -8,7 +8,7 @@ - mlx.nn.Conv3d — MLX 0.18.0 documentation + mlx.nn.Conv3d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
        • mlx.core.repeat
        • mlx.core.reshape
        • mlx.core.right_shift
          • +
        • mlx.core.roll
        • mlx.core.round
        • mlx.core.rsqrt
        • mlx.core.save
          • @@ -425,6 +426,7 @@
        • mlx.core.random.truncated_normal
        • mlx.core.random.uniform
        • mlx.core.random.laplace
          • +
        • mlx.core.random.permutation
      • Transforms
          @@ -871,7 +873,7 @@ document.write(`

          mlx.nn.Conv3d#

          -class Conv3d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, bias: bool = True)#
          +class Conv3d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, bias: bool = True)#

          Applies a 3-dimensional convolution over the multi-channel input image.

          The channels are expected to be last i.e. the input shape should be NDHWC where:

            @@ -884,14 +886,14 @@ document.write(`
            Parameters:
              -

            • in_channels (int) – The number of input channels.

              • -

            • out_channels (int) – The number of output channels.

              • -

            • kernel_size (int or tuple) – The size of the convolution filters.

              • -

            • stride (int or tuple, optional) – The size of the stride when +

            • in_channels (int) – The number of input channels.

              • +

            • out_channels (int) – The number of output channels.

              • +

            • kernel_size (int or tuple) – The size of the convolution filters.

              • +

            • stride (int or tuple, optional) – The size of the stride when applying the filter. Default: 1.

              • -

            • padding (int or tuple, optional) – How many positions to 0-pad +

            • padding (int or tuple, optional) – How many positions to 0-pad the input with. Default: 0.

              • -

            • bias (bool, optional) – If True add a learnable bias to the +

            • bias (bool, optional) – If True add a learnable bias to the output. Default: True

            diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose1d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose1d.html index edbcb2bdb..2b6e47bd3 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose1d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose1d.html @@ -8,7 +8,7 @@ - mlx.nn.ConvTranspose1d — MLX 0.18.0 documentation + mlx.nn.ConvTranspose1d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
          • mlx.core.repeat
          • mlx.core.reshape
          • mlx.core.right_shift
            • +
          • mlx.core.roll
          • mlx.core.round
          • mlx.core.rsqrt
          • mlx.core.save
            • @@ -425,6 +426,7 @@
          • mlx.core.random.truncated_normal
          • mlx.core.random.uniform
          • mlx.core.random.laplace
            • +
          • mlx.core.random.permutation
        • Transforms
            @@ -871,7 +873,7 @@ document.write(`

            mlx.nn.ConvTranspose1d#

            -class ConvTranspose1d(in_channels: int, out_channels: int, kernel_size: int, stride: int = 1, padding: int = 0, dilation: int = 1, bias: bool = True)#
            +class ConvTranspose1d(in_channels: int, out_channels: int, kernel_size: int, stride: int = 1, padding: int = 0, dilation: int = 1, bias: bool = True)#

            Applies a 1-dimensional transposed convolution over the multi-channel input sequence.

            The channels are expected to be last i.e. the input shape should be NLC where:

              @@ -882,15 +884,15 @@ document.write(`
              Parameters:
                -

              • in_channels (int) – The number of input channels

                • -

              • out_channels (int) – The number of output channels

                • -

              • kernel_size (int) – The size of the convolution filters

                • -

              • stride (int, optional) – The stride when applying the filter. +

              • in_channels (int) – The number of input channels

                • +

              • out_channels (int) – The number of output channels

                • +

              • kernel_size (int) – The size of the convolution filters

                • +

              • stride (int, optional) – The stride when applying the filter. Default: 1.

                • -

              • padding (int, optional) – How many positions to 0-pad the input with. +

              • padding (int, optional) – How many positions to 0-pad the input with. Default: 0.

                • -

              • dilation (int, optional) – The dilation of the convolution.

                • -

              • bias (bool, optional) – If True add a learnable bias to the output. +

              • dilation (int, optional) – The dilation of the convolution.

                • +

              • bias (bool, optional) – If True add a learnable bias to the output. Default: True

              diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose2d.html index 30237b7cd..b56570e82 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose2d.html @@ -8,7 +8,7 @@ - mlx.nn.ConvTranspose2d — MLX 0.18.0 documentation + mlx.nn.ConvTranspose2d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
            • mlx.core.repeat
            • mlx.core.reshape
            • mlx.core.right_shift
              • +
            • mlx.core.roll
            • mlx.core.round
            • mlx.core.rsqrt
            • mlx.core.save
              • @@ -425,6 +426,7 @@
            • mlx.core.random.truncated_normal
            • mlx.core.random.uniform
            • mlx.core.random.laplace
              • +
            • mlx.core.random.permutation
          • Transforms
              @@ -871,7 +873,7 @@ document.write(`

              mlx.nn.ConvTranspose2d#

              -class ConvTranspose2d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, dilation: int | tuple = 1, bias: bool = True)#
              +class ConvTranspose2d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, dilation: int | tuple = 1, bias: bool = True)#

              Applies a 2-dimensional transposed convolution over the multi-channel input image.

              The channels are expected to be last i.e. the input shape should be NHWC where:

                @@ -883,15 +885,15 @@ document.write(`
                Parameters:
                  -

                • in_channels (int) – The number of input channels.

                  • -

                • out_channels (int) – The number of output channels.

                  • -

                • kernel_size (int or tuple) – The size of the convolution filters.

                  • -

                • stride (int or tuple, optional) – The size of the stride when +

                • in_channels (int) – The number of input channels.

                  • +

                • out_channels (int) – The number of output channels.

                  • +

                • kernel_size (int or tuple) – The size of the convolution filters.

                  • +

                • stride (int or tuple, optional) – The size of the stride when applying the filter. Default: 1.

                  • -

                • padding (int or tuple, optional) – How many positions to 0-pad +

                • padding (int or tuple, optional) – How many positions to 0-pad the input with. Default: 0.

                  • -

                • dilation (int or tuple, optional) – The dilation of the convolution.

                  • -

                • bias (bool, optional) – If True add a learnable bias to the +

                • dilation (int or tuple, optional) – The dilation of the convolution.

                  • +

                • bias (bool, optional) – If True add a learnable bias to the output. Default: True

                diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose3d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose3d.html index ec9d38385..59d386f82 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose3d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ConvTranspose3d.html @@ -8,7 +8,7 @@ - mlx.nn.ConvTranspose3d — MLX 0.18.0 documentation + mlx.nn.ConvTranspose3d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
              • mlx.core.repeat
              • mlx.core.reshape
              • mlx.core.right_shift
                • +
              • mlx.core.roll
              • mlx.core.round
              • mlx.core.rsqrt
              • mlx.core.save
                • @@ -425,6 +426,7 @@
              • mlx.core.random.truncated_normal
              • mlx.core.random.uniform
              • mlx.core.random.laplace
                • +
              • mlx.core.random.permutation
            • Transforms
                @@ -871,7 +873,7 @@ document.write(`

                mlx.nn.ConvTranspose3d#

                -class ConvTranspose3d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, bias: bool = True)#
                +class ConvTranspose3d(in_channels: int, out_channels: int, kernel_size: int | tuple, stride: int | tuple = 1, padding: int | tuple = 0, bias: bool = True)#

                Applies a 3-dimensional transposed convolution over the multi-channel input image.

                The channels are expected to be last i.e. the input shape should be NDHWC where:

                  @@ -884,14 +886,14 @@ document.write(`
                  Parameters:
                    -

                  • in_channels (int) – The number of input channels.

                    • -

                  • out_channels (int) – The number of output channels.

                    • -

                  • kernel_size (int or tuple) – The size of the convolution filters.

                    • -

                  • stride (int or tuple, optional) – The size of the stride when +

                  • in_channels (int) – The number of input channels.

                    • +

                  • out_channels (int) – The number of output channels.

                    • +

                  • kernel_size (int or tuple) – The size of the convolution filters.

                    • +

                  • stride (int or tuple, optional) – The size of the stride when applying the filter. Default: 1.

                    • -

                  • padding (int or tuple, optional) – How many positions to 0-pad +

                  • padding (int or tuple, optional) – How many positions to 0-pad the input with. Default: 0.

                    • -

                  • bias (bool, optional) – If True add a learnable bias to the +

                  • bias (bool, optional) – If True add a learnable bias to the output. Default: True

                  diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout.html index 25aa69b93..7bcf9769a 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout.html @@ -8,7 +8,7 @@ - mlx.nn.Dropout — MLX 0.18.0 documentation + mlx.nn.Dropout — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,14 +874,14 @@ document.write(`

                  mlx.nn.Dropout#

                  -class Dropout(p: float = 0.5)#
                  +class Dropout(p: float = 0.5)#

                  Randomly zero a portion of the elements during training.

                  The remaining elements are multiplied with \(\frac{1}{1-p}\) where \(p\) is the probability of zeroing an element. This is done so the expected value of a given element will remain the same.

                  Parameters:
                  -

                  p (float) – The probability to zero an element

                  +

                  p (float) – The probability to zero an element

                  Methods

                  diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout2d.html index a104638e4..8302ccf1e 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout2d.html @@ -8,7 +8,7 @@ - mlx.nn.Dropout2d — MLX 0.18.0 documentation + mlx.nn.Dropout2d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.nn.Dropout2d#

                  -class Dropout2d(p: float = 0.5)#
                  +class Dropout2d(p: float = 0.5)#

                  Apply 2D channel-wise dropout during training.

                  Randomly zero out entire channels independently with probability \(p\). This layer expects the channels to be last, i.e. the input shape should be @@ -889,7 +891,7 @@ regularize activations. For more details, see [1].

                  Efficient Object Localization Using Convolutional Networks. CVPR 2015.

                  Parameters:
                  -

                  p (float) – Probability of zeroing a channel during training.

                  +

                  p (float) – Probability of zeroing a channel during training.

                  Methods

                  diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout3d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout3d.html index e57654b0d..cfc3e8440 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout3d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Dropout3d.html @@ -8,7 +8,7 @@ - mlx.nn.Dropout3d — MLX 0.18.0 documentation + mlx.nn.Dropout3d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.nn.Dropout3d#

                  -class Dropout3d(p: float = 0.5)#
                  +class Dropout3d(p: float = 0.5)#

                  Apply 3D channel-wise dropout during training.

                  Randomly zero out entire channels independently with probability \(p\). This layer expects the channels to be last, i.e., the input shape should be @@ -886,7 +888,7 @@ often beneficial for convolutional layers processing 3D data, like in medical imaging or video processing.

                  Parameters:
                  -

                  p (float) – Probability of zeroing a channel during training.

                  +

                  p (float) – Probability of zeroing a channel during training.

                  Methods

                  diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ELU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ELU.html index 873fa41c3..84a995f5b 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ELU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ELU.html @@ -8,7 +8,7 @@ - mlx.nn.ELU — MLX 0.18.0 documentation + mlx.nn.ELU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
              • Transforms
                  @@ -871,16 +873,16 @@ document.write(`

                  mlx.nn.Embedding#

                  -class Embedding(num_embeddings: int, dims: int)#
                  +class Embedding(num_embeddings: int, dims: int)#

                  Implements a simple lookup table that maps each input integer to a high-dimensional vector.

                  Typically used to embed discrete tokens for processing by neural networks.

                  Parameters:
                    -

                  • num_embeddings (int) – How many possible discrete tokens can we embed. +

                  • num_embeddings (int) – How many possible discrete tokens can we embed. Usually called the vocabulary size.

                    • -

                  • dims (int) – The dimensionality of the embeddings.

                    • +

                  • dims (int) – The dimensionality of the embeddings.

                  diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.GELU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.GELU.html index 9323ac480..525837b6d 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.GELU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.GELU.html @@ -8,7 +8,7 @@ - mlx.nn.GELU — MLX 0.18.0 documentation + mlx.nn.GELU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.nn.GLU#

                  -class GLU(axis: int = -1)#
                  +class GLU(axis: int = -1)#

                  Applies the gated linear unit function.

                  This function splits the axis dimension of the input into two halves (\(a\) and \(b\)) and applies \(a * \sigma(b)\).

                  @@ -880,7 +882,7 @@ document.write(` \[\textrm{GLU}(x) = a * \sigma(b)\]
                  Parameters:
                  -

                  axis (int) – The dimension to split along. Default: -1

                  +

                  axis (int) – The dimension to split along. Default: -1

                  Methods

                  diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.GRU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.GRU.html index 70707e2d1..d247d6cc6 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.GRU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.GRU.html @@ -8,7 +8,7 @@ - mlx.nn.GRU — MLX 0.18.0 documentation + mlx.nn.GRU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.nn.GRU#

                  -class GRU(input_size: int, hidden_size: int, bias: bool = True)#
                  +class GRU(input_size: int, hidden_size: int, bias: bool = True)#

                  A gated recurrent unit (GRU) RNN layer.

                  The input has shape NLD or LD where:

                    @@ -894,9 +896,9 @@ time step of shape
                    Parameters:
                      -

                    • input_size (int) – Dimension of the input, D.

                      • -

                    • hidden_size (int) – Dimension of the hidden state, H.

                      • -

                    • bias (bool) – Whether to use biases or not. Default: True.

                      • +

                    • input_size (int) – Dimension of the input, D.

                      • +

                    • hidden_size (int) – Dimension of the hidden state, H.

                      • +

                    • bias (bool) – Whether to use biases or not. Default: True.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.GroupNorm.html b/docs/build/html/python/nn/_autosummary/mlx.nn.GroupNorm.html index 9b84bfb15..55b81a012 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.GroupNorm.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.GroupNorm.html @@ -8,7 +8,7 @@ - mlx.nn.GroupNorm — MLX 0.18.0 documentation + mlx.nn.GroupNorm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -426,6 +427,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.GroupNorm#

                    -class GroupNorm(num_groups: int, dims: int, eps: float = 1e-05, affine: bool = True, pytorch_compatible: bool = False)#
                    +class GroupNorm(num_groups: int, dims: int, eps: float = 1e-05, affine: bool = True, pytorch_compatible: bool = False)#

                    Applies Group Normalization [1] to the inputs.

                    Computes the same normalization as layer norm, namely

                    @@ -888,12 +890,12 @@ that precede it (except the first) are considered the spatial dimensions.

                    Parameters:
                      -

                    • num_groups (int) – Number of groups to separate the features into

                      • -

                    • dims (int) – The feature dimensions of the input to normalize over

                      • -

                    • eps (float) – A small additive constant for numerical stability

                      • -

                    • affine (bool) – If True learn an affine transform to apply after the +

                    • num_groups (int) – Number of groups to separate the features into

                      • +

                    • dims (int) – The feature dimensions of the input to normalize over

                      • +

                    • eps (float) – A small additive constant for numerical stability

                      • +

                    • affine (bool) – If True learn an affine transform to apply after the normalization.

                      • -

                    • pytorch_compatible (bool) – If True perform the group normalization in +

                    • pytorch_compatible (bool) – If True perform the group normalization in the same order/grouping as PyTorch.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.HardShrink.html b/docs/build/html/python/nn/_autosummary/mlx.nn.HardShrink.html index ee15f0593..82e8461b1 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.HardShrink.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.HardShrink.html @@ -8,7 +8,7 @@ - mlx.nn.HardShrink — MLX 0.18.0 documentation + mlx.nn.HardShrink — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
                    @@ -371,6 +371,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -426,6 +427,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                • Transforms
                • Transforms
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.InstanceNorm#

                    -class InstanceNorm(dims: int, eps: float = 1e-05, affine: bool = False)#
                    +class InstanceNorm(dims: int, eps: float = 1e-05, affine: bool = False)#

                    Applies instance normalization [1] on the inputs.

                    Computes

                    @@ -883,9 +885,9 @@ if
                    Parameters:
                      -

                    • dims (int) – The number of features of the input.

                      • -

                    • eps (float) – A value added to the denominator for numerical stability. Default: 1e-5.

                      • -

                    • affine (bool) – Default: False.

                      • +

                    • dims (int) – The number of features of the input.

                      • +

                    • eps (float) – A value added to the denominator for numerical stability. Default: 1e-5.

                      • +

                    • affine (bool) – Default: False.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.LSTM.html b/docs/build/html/python/nn/_autosummary/mlx.nn.LSTM.html index e6797f4dc..c1aeca511 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.LSTM.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.LSTM.html @@ -8,7 +8,7 @@ - mlx.nn.LSTM — MLX 0.18.0 documentation + mlx.nn.LSTM — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
                    @@ -371,6 +371,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -426,6 +427,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.LSTM#

                    -class LSTM(input_size: int, hidden_size: int, bias: bool = True)#
                    +class LSTM(input_size: int, hidden_size: int, bias: bool = True)#

                    An LSTM recurrent layer.

                    The input has shape NLD or LD where:

                      @@ -897,9 +899,9 @@ each time step, both of shape
                      Parameters:
                        -

                      • input_size (int) – Dimension of the input, D.

                        • -

                      • hidden_size (int) – Dimension of the hidden state, H.

                        • -

                      • bias (bool) – Whether to use biases or not. Default: True.

                        • +

                      • input_size (int) – Dimension of the input, D.

                        • +

                      • hidden_size (int) – Dimension of the hidden state, H.

                        • +

                      • bias (bool) – Whether to use biases or not. Default: True.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.LayerNorm.html b/docs/build/html/python/nn/_autosummary/mlx.nn.LayerNorm.html index 162ce8548..facbe7213 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.LayerNorm.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.LayerNorm.html @@ -8,7 +8,7 @@ - mlx.nn.LayerNorm — MLX 0.18.0 documentation + mlx.nn.LayerNorm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -426,6 +427,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.LayerNorm#

                    -class LayerNorm(dims: int, eps: float = 1e-05, affine: bool = True, bias: bool = True)#
                    +class LayerNorm(dims: int, eps: float = 1e-05, affine: bool = True, bias: bool = True)#

                    Applies layer normalization [1] on the inputs.

                    Computes

                    @@ -883,11 +885,11 @@ parameters initialized at 1 and 0 respectively.

                    Parameters:
                      -

                    • dims (int) – The feature dimension of the input to normalize over

                      • -

                    • eps (float) – A small additive constant for numerical stability

                      • -

                    • affine (bool) – If True learn an affine transform to apply after the +

                    • dims (int) – The feature dimension of the input to normalize over

                      • +

                    • eps (float) – A small additive constant for numerical stability

                      • +

                    • affine (bool) – If True learn an affine transform to apply after the normalization

                      • -

                    • bias (bool) – If True include a translation to the affine +

                    • bias (bool) – If True include a translation to the affine transformation. If set to False the transformation is not really affine just scaling.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.LeakyReLU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.LeakyReLU.html index b45871009..05e8a9006 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.LeakyReLU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.LeakyReLU.html @@ -8,7 +8,7 @@ - mlx.nn.LeakyReLU — MLX 0.18.0 documentation + mlx.nn.LeakyReLU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
                    @@ -370,6 +370,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -425,6 +426,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.Linear#

                    -class Linear(input_dims: int, output_dims: int, bias: bool = True)#
                    +class Linear(input_dims: int, output_dims: int, bias: bool = True)#

                    Applies an affine transformation to the input.

                    Concretely:

                    @@ -884,9 +886,9 @@ where \(k = \frac{1}{\sqrt{D_i}}\)
                    Parameters:
                      -

                    • input_dims (int) – The dimensionality of the input features

                      • -

                    • output_dims (int) – The dimensionality of the output features

                      • -

                    • bias (bool, optional) – If set to False then the layer will +

                    • input_dims (int) – The dimensionality of the input features

                      • +

                    • output_dims (int) – The dimensionality of the output features

                      • +

                    • bias (bool, optional) – If set to False then the layer will not use a bias. Default is True.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.LogSigmoid.html b/docs/build/html/python/nn/_autosummary/mlx.nn.LogSigmoid.html index 230c9572a..a40a1586e 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.LogSigmoid.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.LogSigmoid.html @@ -8,7 +8,7 @@ - mlx.nn.LogSigmoid — MLX 0.18.0 documentation + mlx.nn.LogSigmoid — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -425,6 +426,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                • Transforms
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.MaxPool1d#

                    -class MaxPool1d(kernel_size: int | Tuple[int], stride: int | Tuple[int] | None = None, padding: int | Tuple[int] = 0)#
                    +class MaxPool1d(kernel_size: int | Tuple[int], stride: int | Tuple[int] | None = None, padding: int | Tuple[int] = 0)#

                    Applies 1-dimensional max pooling.

                    Assuming an input of shape \((N, L, C)\) and kernel_size is \(k\), the output is a tensor of shape \((N, L_{out}, C)\), given @@ -887,10 +889,10 @@ by:

                    Parameters:
                      -

                    • kernel_size (int or tuple(int)) – The size of the pooling window kernel.

                      • -

                    • stride (int or tuple(int), optional) – The stride of the pooling window. +

                    • kernel_size (int or tuple(int)) – The size of the pooling window kernel.

                      • +

                    • stride (int or tuple(int), optional) – The stride of the pooling window. Default: kernel_size.

                      • -

                    • padding (int or tuple(int), optional) – How much negative infinity +

                    • padding (int or tuple(int), optional) – How much negative infinity padding to apply to the input. The padding amount is applied to both sides of the spatial axis. Default: 0.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.MaxPool2d.html b/docs/build/html/python/nn/_autosummary/mlx.nn.MaxPool2d.html index eb17ddb36..327ad81fb 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.MaxPool2d.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.MaxPool2d.html @@ -8,7 +8,7 @@ - mlx.nn.MaxPool2d — MLX 0.18.0 documentation + mlx.nn.MaxPool2d — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -426,6 +427,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.MaxPool2d#

                    -class MaxPool2d(kernel_size: int | Tuple[int, int], stride: int | Tuple[int, int] | None = None, padding: int | Tuple[int, int] | None = 0)#
                    +class MaxPool2d(kernel_size: int | Tuple[int, int], stride: int | Tuple[int, int] | None = None, padding: int | Tuple[int, int] | None = 0)#

                    Applies 2-dimensional max pooling.

                    Assuming an input of shape \((N, H, W, C)\) and kernel_size is \((k_H, k_W)\), the output is a tensor of shape \((N, H_{out}, @@ -897,10 +899,10 @@ used for the height axis, the second

                    Parameters:
                      -

                    • kernel_size (int or tuple(int, int)) – The size of the pooling window.

                      • -

                    • stride (int or tuple(int, int), optional) – The stride of the pooling +

                    • kernel_size (int or tuple(int, int)) – The size of the pooling window.

                      • +

                    • stride (int or tuple(int, int), optional) – The stride of the pooling window. Default: kernel_size.

                      • -

                    • padding (int or tuple(int, int), optional) – How much negative infinity +

                    • padding (int or tuple(int, int), optional) – How much negative infinity padding to apply to the input. The padding is applied on both sides of the height and width axis. Default: 0.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Mish.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Mish.html index 5bf528f0f..60d0e4a31 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Mish.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Mish.html @@ -8,7 +8,7 @@ - mlx.nn.Mish — MLX 0.18.0 documentation + mlx.nn.Mish — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -426,6 +427,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                • Transforms
                • Transforms
                    @@ -871,7 +873,7 @@ document.write(`

                    mlx.nn.Module.apply_to_modules#

                    -Module.apply_to_modules(apply_fn: Callable[[str, Module], Any]) → Module#
                    +Module.apply_to_modules(apply_fn: Callable[[str, Module], Any]) → Module#

                    Apply a function to all the modules in this instance (including this instance).

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.children.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.children.html index 057b2e3eb..1e3759906 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.children.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.children.html @@ -8,7 +8,7 @@ - mlx.nn.Module.children — MLX 0.18.0 documentation + mlx.nn.Module.children — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -425,6 +426,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                • Transforms
                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.filter_and_map.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.filter_and_map.html index 62ba4d459..232702ac1 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.filter_and_map.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.filter_and_map.html @@ -8,7 +8,7 @@ - mlx.nn.Module.filter_and_map — MLX 0.18.0 documentation + mlx.nn.Module.filter_and_map — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -425,6 +426,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                • Transforms
                    @@ -871,7 +873,7 @@ document.write(`

                    mlx.nn.Module.freeze#

                    -Module.freeze(*, recurse: bool = True, keys: str | List[str] | None = None, strict: bool = False) → Module#
                    +Module.freeze(*, recurse: bool = True, keys: str | List[str] | None = None, strict: bool = False) → Module#

                    Freeze the Module’s parameters or some of them. Freezing a parameter means not computing gradients for it.

                    This function is idempotent i.e. freezing a frozen model is a no-op.

                    @@ -885,13 +887,13 @@ computing gradients for it.

                    Parameters:
                      -

                    • recurse (bool, optional) – If True then freeze the parameters of the +

                    • recurse (bool, optional) – If True then freeze the parameters of the submodules as well. Default: True.

                      • -

                    • keys (str or list[str], optional) – If provided then only these +

                    • keys (str or list[str], optional) – If provided then only these parameters will be frozen otherwise all the parameters of a module. For instance freeze all biases by calling module.freeze(keys="bias").

                      • -

                    • strict (bool, optional) – If set to True validate that the passed keys exist. +

                    • strict (bool, optional) – If set to True validate that the passed keys exist. Default: False.

                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.leaf_modules.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.leaf_modules.html index ae44ad571..a73bd72dc 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.leaf_modules.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.leaf_modules.html @@ -8,7 +8,7 @@ - mlx.nn.Module.leaf_modules — MLX 0.18.0 documentation + mlx.nn.Module.leaf_modules — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -425,6 +426,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.load_weights.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.load_weights.html index 1cdcd33e1..8bf56d6cf 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.load_weights.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.load_weights.html @@ -8,7 +8,7 @@ - mlx.nn.Module.load_weights — MLX 0.18.0 documentation + mlx.nn.Module.load_weights — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -425,6 +426,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -871,15 +873,15 @@ document.write(`

                    mlx.nn.Module.load_weights#

                    -Module.load_weights(file_or_weights: str | List[Tuple[str, array]], strict: bool = True) → Module#
                    +Module.load_weights(file_or_weights: str | List[Tuple[str, array]], strict: bool = True) → Module#

                    Update the model’s weights from a .npz, a .safetensors file, or a list.

                    Parameters:
                      -

                    • file_or_weights (str or list(tuple(str, mx.array))) – The path to +

                    • file_or_weights (str or list(tuple(str, mx.array))) – The path to the weights .npz file (.npz or .safetensors) or a list of pairs of parameter names and arrays.

                      • -

                    • strict (bool, optional) – If True then checks that the provided +

                    • strict (bool, optional) – If True then checks that the provided weights exactly match the parameters of the model. Otherwise, only the weights actually contained in the model are loaded and shapes are not checked. Default: True.

                      • diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.modules.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.modules.html index 360ddc188..d0f64c0ad 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.modules.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.modules.html @@ -8,7 +8,7 @@ - mlx.nn.Module.modules — MLX 0.18.0 documentation + mlx.nn.Module.modules — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -425,6 +426,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.named_modules.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.named_modules.html index c51dab965..5ab1e63b2 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.named_modules.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.named_modules.html @@ -8,7 +8,7 @@ - mlx.nn.Module.named_modules — MLX 0.18.0 documentation + mlx.nn.Module.named_modules — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -425,6 +426,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                  • Transforms
                      diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.save_weights.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.save_weights.html index 59ff94f34..228efbb3a 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.save_weights.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.save_weights.html @@ -8,7 +8,7 @@ - mlx.nn.Module.save_weights — MLX 0.18.0 documentation + mlx.nn.Module.save_weights — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -425,6 +426,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      @@ -871,7 +873,7 @@ document.write(`

                      mlx.nn.Module.save_weights#

                      -Module.save_weights(file: str)#
                      +Module.save_weights(file: str)#

                      Save the model’s weights to a file. The saving method is determined by the file extension: - .npz will use mx.savez() - .safetensors will use mx.save_safetensors()

                      diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.set_dtype.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.set_dtype.html index 521068139..1e7c8e3cf 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.set_dtype.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.set_dtype.html @@ -8,7 +8,7 @@ - mlx.nn.Module.set_dtype — MLX 0.18.0 documentation + mlx.nn.Module.set_dtype — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -425,6 +426,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      @@ -877,7 +879,7 @@ document.write(`
                      Parameters:

                      • dtype (Dtype) – The new dtype.

                        • -

                      • predicate (Callable, optional) – A predicate to select +

                      • predicate (Callable, optional) – A predicate to select parameters to cast. By default, only parameters of type floating will be updated to avoid casting integer parameters to the new dtype.

                        • diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.state.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.state.html index ef4a682dc..0dc7fe3ee 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.state.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.state.html @@ -8,7 +8,7 @@ - mlx.nn.Module.state — MLX 0.18.0 documentation + mlx.nn.Module.state — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -425,6 +426,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                    • Transforms
                        @@ -871,14 +873,14 @@ document.write(`

                        mlx.nn.Module.train#

                        -Module.train(mode: bool = True) → Module#
                        +Module.train(mode: bool = True) → Module#

                        Set the model in or out of training mode.

                        Training mode only applies to certain layers. For example Dropout applies a random mask in training mode, but is the identity in evaluation mode.

                        Parameters:
                        -

                        mode (bool) – Indicate if the model should be in training or +

                        mode (bool) – Indicate if the model should be in training or evaluation mode. Default: True.

                        Returns:
                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.trainable_parameters.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.trainable_parameters.html index 34a8e0648..3c693821d 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.trainable_parameters.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.trainable_parameters.html @@ -8,7 +8,7 @@ - mlx.nn.Module.trainable_parameters — MLX 0.18.0 documentation + mlx.nn.Module.trainable_parameters — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -425,6 +426,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                    • Transforms
                    • Transforms
                        @@ -871,7 +873,7 @@ document.write(`

                        mlx.nn.Module.unfreeze#

                        -Module.unfreeze(*, recurse: bool = True, keys: str | List[str] | None = None, strict: bool = False) → Module#
                        +Module.unfreeze(*, recurse: bool = True, keys: str | List[str] | None = None, strict: bool = False) → Module#

                        Unfreeze the Module’s parameters or some of them.

                        This function is idempotent ie unfreezing a model that is not frozen is a noop.

                        @@ -885,13 +887,13 @@ a noop.

                        Parameters:
                          -

                        • recurse (bool, optional) – If True then unfreeze the parameters of the +

                        • recurse (bool, optional) – If True then unfreeze the parameters of the submodules as well. Default: True.

                          • -

                        • keys (str or list[str], optional) – If provided then only these +

                        • keys (str or list[str], optional) – If provided then only these parameters will be unfrozen otherwise all the parameters of a module. For instance unfreeze all biases by calling module.unfreeze(keys="bias").

                          • -

                        • strict (bool, optional) – If set to True validate that the passed keys exist. +

                        • strict (bool, optional) – If set to True validate that the passed keys exist. Default: False.

                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.update.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.update.html index deeefc3f2..051e19366 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.update.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.update.html @@ -8,7 +8,7 @@ - mlx.nn.Module.update — MLX 0.18.0 documentation + mlx.nn.Module.update — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -425,6 +426,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        @@ -871,7 +873,7 @@ document.write(`

                        mlx.nn.Module.update#

                        -Module.update(parameters: dict) → Module#
                        +Module.update(parameters: dict) → Module#

                        Replace the parameters of this Module with the provided ones in the dict of dicts and lists.

                        Commonly used by the optimizer to change the model to the updated @@ -882,7 +884,7 @@ similar to

                        Parameters:
                        -

                        parameters (dict) – A complete or partial dictionary of the modules +

                        parameters (dict) – A complete or partial dictionary of the modules parameters.

                        Returns:
                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.update_modules.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.update_modules.html index d620d2978..f3fe4058e 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Module.update_modules.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Module.update_modules.html @@ -8,7 +8,7 @@ - mlx.nn.Module.update_modules — MLX 0.18.0 documentation + mlx.nn.Module.update_modules — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -425,6 +426,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        @@ -871,7 +873,7 @@ document.write(`

                        mlx.nn.Module.update_modules#

                        -Module.update_modules(modules: dict) → Module#
                        +Module.update_modules(modules: dict) → Module#

                        Replace the child modules of this Module instance with the provided ones in the dict of dicts and lists.

                        It is the equivalent of Module.update() but for modules instead @@ -882,7 +884,7 @@ similar to

                        Parameters:
                        -

                        modules (dict) – A complete or partial dictionary of the modules +

                        modules (dict) – A complete or partial dictionary of the modules submodules.

                        Returns:
                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.MultiHeadAttention.html b/docs/build/html/python/nn/_autosummary/mlx.nn.MultiHeadAttention.html index 8ec0300d2..9b313c835 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.MultiHeadAttention.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.MultiHeadAttention.html @@ -8,7 +8,7 @@ - mlx.nn.MultiHeadAttention — MLX 0.18.0 documentation + mlx.nn.MultiHeadAttention — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -425,6 +426,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        @@ -871,7 +873,7 @@ document.write(`

                        mlx.nn.MultiHeadAttention#

                        -class MultiHeadAttention(dims: int, num_heads: int, query_input_dims: int | None = None, key_input_dims: int | None = None, value_input_dims: int | None = None, value_dims: int | None = None, value_output_dims: int | None = None, bias: bool = False)#
                        +class MultiHeadAttention(dims: int, num_heads: int, query_input_dims: int | None = None, key_input_dims: int | None = None, value_input_dims: int | None = None, value_dims: int | None = None, value_output_dims: int | None = None, bias: bool = False)#

                        Implements the scaled dot product attention with multiple heads.

                        Given inputs for queries, keys and values the MultiHeadAttention produces new values by aggregating information from the input values @@ -885,20 +887,20 @@ that should not be attended to.

                        Parameters:
                          -

                        • dims (int) – The model dimensions. This is also the default +

                        • dims (int) – The model dimensions. This is also the default value for the queries, keys, values, and the output.

                          • -

                        • num_heads (int) – The number of attention heads to use.

                          • -

                        • query_input_dims (int, optional) – The input dimensions of the queries. +

                        • num_heads (int) – The number of attention heads to use.

                          • +

                        • query_input_dims (int, optional) – The input dimensions of the queries. Default: dims.

                          • -

                        • key_input_dims (int, optional) – The input dimensions of the keys. +

                        • key_input_dims (int, optional) – The input dimensions of the keys. Default: dims.

                          • -

                        • value_input_dims (int, optional) – The input dimensions of the values. +

                        • value_input_dims (int, optional) – The input dimensions of the values. Default: key_input_dims.

                          • -

                        • value_dims (int, optional) – The dimensions of the values after the +

                        • value_dims (int, optional) – The dimensions of the values after the projection. Default: dims.

                          • -

                        • value_output_dims (int, optional) – The dimensions the new values will +

                        • value_output_dims (int, optional) – The dimensions the new values will be projected to. Default: dims.

                          • -

                        • bias (bool, optional) – Whether or not to use a bias in the projections. +

                        • bias (bool, optional) – Whether or not to use a bias in the projections. Default: False.

                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.PReLU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.PReLU.html index cf96e4994..c81b1ae9c 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.PReLU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.PReLU.html @@ -8,7 +8,7 @@ - mlx.nn.PReLU — MLX 0.18.0 documentation + mlx.nn.PReLU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -426,6 +427,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html b/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html index 513ccb24f..7cfaf0348 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedEmbedding.html @@ -8,7 +8,7 @@ - mlx.nn.QuantizedEmbedding — MLX 0.18.0 documentation + mlx.nn.QuantizedEmbedding — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -425,6 +426,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        @@ -871,7 +873,7 @@ document.write(`

                        mlx.nn.QuantizedEmbedding#

                        -class QuantizedEmbedding(num_embeddings: int, dims: int, group_size: int = 64, bits: int = 4)#
                        +class QuantizedEmbedding(num_embeddings: int, dims: int, group_size: int = 64, bits: int = 4)#

                        The same as Embedding but with a quantized weight matrix.

                        QuantizedEmbedding also provides a from_embedding() classmethod to convert embedding layers to QuantizedEmbedding @@ -879,12 +881,12 @@ layers.

                        Parameters:
                          -

                        • num_embeddings (int) – How many possible discrete tokens can we embed. +

                        • num_embeddings (int) – How many possible discrete tokens can we embed. Usually called the vocabulary size.

                          • -

                        • dims (int) – The dimensionality of the embeddings.

                          • -

                        • group_size (int, optional) – The group size to use for the quantized +

                        • dims (int) – The dimensionality of the embeddings.

                          • +

                        • group_size (int, optional) – The group size to use for the quantized weight. See quantize(). Default: 64.

                          • -

                        • bits (int, optional) – The bit width to use for the quantized weight. +

                        • bits (int, optional) – The bit width to use for the quantized weight. See quantize(). Default: 4.

                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedLinear.html b/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedLinear.html index b7207994d..db58f3c4d 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedLinear.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.QuantizedLinear.html @@ -8,7 +8,7 @@ - mlx.nn.QuantizedLinear — MLX 0.18.0 documentation + mlx.nn.QuantizedLinear — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -425,6 +426,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        @@ -871,7 +873,7 @@ document.write(`

                        mlx.nn.QuantizedLinear#

                        -class QuantizedLinear(input_dims: int, output_dims: int, bias: bool = True, group_size: int = 64, bits: int = 4)#
                        +class QuantizedLinear(input_dims: int, output_dims: int, bias: bool = True, group_size: int = 64, bits: int = 4)#

                        Applies an affine transformation to the input using a quantized weight matrix.

                        It is the quantized equivalent of mlx.nn.Linear. For now its parameters are frozen and will not be included in any gradient computation @@ -881,13 +883,13 @@ convert linear layers to

                        Parameters:
                          -

                        • input_dims (int) – The dimensionality of the input features.

                          • -

                        • output_dims (int) – The dimensionality of the output features.

                          • -

                        • bias (bool, optional) – If set to False then the layer will not use +

                        • input_dims (int) – The dimensionality of the input features.

                          • +

                        • output_dims (int) – The dimensionality of the output features.

                          • +

                        • bias (bool, optional) – If set to False then the layer will not use a bias. Default: True.

                          • -

                        • group_size (int, optional) – The group size to use for the quantized +

                        • group_size (int, optional) – The group size to use for the quantized weight. See quantize(). Default: 64.

                          • -

                        • bits (int, optional) – The bit width to use for the quantized weight. +

                        • bits (int, optional) – The bit width to use for the quantized weight. See quantize(). Default: 4.

                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.RMSNorm.html b/docs/build/html/python/nn/_autosummary/mlx.nn.RMSNorm.html index 3a58a1d95..b1623f7ff 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.RMSNorm.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.RMSNorm.html @@ -8,7 +8,7 @@ - mlx.nn.RMSNorm — MLX 0.18.0 documentation + mlx.nn.RMSNorm — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -426,6 +427,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        @@ -872,7 +874,7 @@ document.write(`

                        mlx.nn.RMSNorm#

                        -class RMSNorm(dims: int, eps: float = 1e-05)#
                        +class RMSNorm(dims: int, eps: float = 1e-05)#

                        Applies Root Mean Square normalization [1] to the inputs.

                        Computes

                        @@ -884,8 +886,8 @@ document.write(`
                        Parameters:
                          -

                        • dims (int) – The feature dimension of the input to normalize over

                          • -

                        • eps (float) – A small additive constant for numerical stability

                          • +

                        • dims (int) – The feature dimension of the input to normalize over

                          • +

                        • eps (float) – A small additive constant for numerical stability

                        diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.RNN.html b/docs/build/html/python/nn/_autosummary/mlx.nn.RNN.html index 3865238dc..b596543c6 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.RNN.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.RNN.html @@ -8,7 +8,7 @@ - mlx.nn.RNN — MLX 0.18.0 documentation + mlx.nn.RNN — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
                        @@ -371,6 +371,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -426,6 +427,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        @@ -872,7 +874,7 @@ document.write(`

                        mlx.nn.RNN#

                        -class RNN(input_size: int, hidden_size: int, bias: bool = True, nonlinearity: Callable | None = None)#
                        +class RNN(input_size: int, hidden_size: int, bias: bool = True, nonlinearity: Callable | None = None)#

                        An Elman recurrent layer.

                        The input is a sequence of shape NLD or LD where:

                          @@ -890,9 +892,9 @@ time step, of shape
                          Parameters:
                            -

                          • input_size (int) – Dimension of the input, D.

                            • -

                          • hidden_size (int) – Dimension of the hidden state, H.

                            • -

                          • bias (bool, optional) – Whether to use a bias. Default: True.

                            • +

                          • input_size (int) – Dimension of the input, D.

                            • +

                          • hidden_size (int) – Dimension of the hidden state, H.

                            • +

                          • bias (bool, optional) – Whether to use a bias. Default: True.

                          • nonlinearity (callable, optional) – Non-linearity to use. If None, then func:tanh is used. Default: None.

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.ReLU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.ReLU.html index fbec908e7..1ede8c4cf 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.ReLU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.ReLU.html @@ -8,7 +8,7 @@ - mlx.nn.ReLU — MLX 0.18.0 documentation + mlx.nn.ReLU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                      • Transforms
                      • Transforms
                          @@ -871,7 +873,7 @@ document.write(`

                          mlx.nn.RoPE#

                          -class RoPE(dims: int, traditional: bool = False, base: float = 10000, scale: float = 1.0)#
                          +class RoPE(dims: int, traditional: bool = False, base: float = 10000, scale: float = 1.0)#

                          Implements the rotary positional encoding.

                          The traditional implementation rotates consecutive pairs of elements in the feature dimension while the default implementation rotates pairs with @@ -881,13 +883,13 @@ Embedding.

                          Parameters:
                            -

                          • dims (int) – The feature dimensions to be rotated. If the input feature +

                          • dims (int) – The feature dimensions to be rotated. If the input feature is larger than dims then the rest is left unchanged.

                            • -

                          • traditional (bool, optional) – If set to True choose the traditional +

                          • traditional (bool, optional) – If set to True choose the traditional implementation which is slightly less efficient. Default: False.

                            • -

                          • base (float, optional) – The base used to compute angular frequency for +

                          • base (float, optional) – The base used to compute angular frequency for each dimension in the positional encodings. Default: 10000.

                            • -

                          • scale (float, optional) – The scale used to scale the positions. Default: 1.0.

                            • +

                          • scale (float, optional) – The scale used to scale the positions. Default: 1.0.

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.SELU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.SELU.html index 5e3c6cc48..1b1f1c1f9 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.SELU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.SELU.html @@ -8,7 +8,7 @@ - mlx.nn.SELU — MLX 0.18.0 documentation + mlx.nn.SELU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                      • Transforms
                          @@ -878,7 +880,7 @@ our functions have learnable parameters they should be implemented as nn.Module instances.

                          Parameters:
                          -

                          modules (tuple of Callables) – The modules to call in order

                          +

                          modules (tuple of Callables) – The modules to call in order

                          Methods

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.SiLU.html b/docs/build/html/python/nn/_autosummary/mlx.nn.SiLU.html index c249b3a59..e917299ac 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.SiLU.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.SiLU.html @@ -8,7 +8,7 @@ - mlx.nn.SiLU — MLX 0.18.0 documentation + mlx.nn.SiLU — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                      • Transforms
                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.SinusoidalPositionalEncoding.html b/docs/build/html/python/nn/_autosummary/mlx.nn.SinusoidalPositionalEncoding.html index 1bef38fc2..5aa61c604 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.SinusoidalPositionalEncoding.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.SinusoidalPositionalEncoding.html @@ -8,7 +8,7 @@ - mlx.nn.SinusoidalPositionalEncoding — MLX 0.18.0 documentation + mlx.nn.SinusoidalPositionalEncoding — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -426,6 +427,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -872,22 +874,22 @@ document.write(`

                          mlx.nn.SinusoidalPositionalEncoding#

                          -class SinusoidalPositionalEncoding(dims: int, min_freq: float = 0.0001, max_freq: float = 1, scale: float | None = None, cos_first: bool = False, full_turns: bool = False)#
                          +class SinusoidalPositionalEncoding(dims: int, min_freq: float = 0.0001, max_freq: float = 1, scale: float | None = None, cos_first: bool = False, full_turns: bool = False)#

                          Implements sinusoidal positional encoding.

                          For more details see the paper Attention Is All You Need.

                          Parameters:
                            -

                          • dims (int) – The dimensionality of the resulting positional embeddings.

                            • -

                          • min_freq (float, optional) – The minimum frequency expected. Default: +

                          • dims (int) – The dimensionality of the resulting positional embeddings.

                            • +

                          • min_freq (float, optional) – The minimum frequency expected. Default: 0.0001.

                            • -

                          • max_freq (float, optional) – The maximum frequency expected. Default: +

                          • max_freq (float, optional) – The maximum frequency expected. Default: 1.

                            • -

                          • scale (float, optional) – A multiplicative scale for the embeddings. +

                          • scale (float, optional) – A multiplicative scale for the embeddings. Default: sqrt(2/dims).

                            • -

                          • cos_first (bool, optional) – If True embed using [cos(x); sin(x)] +

                          • cos_first (bool, optional) – If True embed using [cos(x); sin(x)] instead of the reverse. Default: False.

                            • -

                          • full_turns (bool, optional) – If True multiply the frequencies with +

                          • full_turns (bool, optional) – If True multiply the frequencies with \(2\pi\). Default: False.

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Softmax.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Softmax.html index 4ba73ab26..d80d26516 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Softmax.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Softmax.html @@ -8,7 +8,7 @@ - mlx.nn.Softmax — MLX 0.18.0 documentation + mlx.nn.Softmax — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                      • Transforms
                      • Transforms
                      • Transforms
                      • Transforms
                      • Transforms
                          @@ -872,7 +874,7 @@ document.write(`

                          mlx.nn.Step#

                          -class Step(threshold: float = 0.0)#
                          +class Step(threshold: float = 0.0)#

                          Applies the Step Activation Function.

                          This function implements a binary step activation, where the output is set to 1 if the input is greater than a specified threshold, and 0 otherwise.

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.Tanh.html b/docs/build/html/python/nn/_autosummary/mlx.nn.Tanh.html index 77192cc6f..527e4cbf1 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.Tanh.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.Tanh.html @@ -8,7 +8,7 @@ - mlx.nn.Tanh — MLX 0.18.0 documentation + mlx.nn.Tanh — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                      • Transforms
                          @@ -881,18 +883,18 @@ mechanism.

                          Parameters:
                            -

                          • dims (int, optional) – The number of expected features in the +

                          • dims (int, optional) – The number of expected features in the encoder/decoder inputs. Default: 512.

                            • -

                          • num_heads (int, optional) – The number of attention heads. Default: +

                          • num_heads (int, optional) – The number of attention heads. Default: 8.

                            • -

                          • num_encoder_layers (int, optional) – The number of encoder layers in the +

                          • num_encoder_layers (int, optional) – The number of encoder layers in the Transformer encoder. Default: 6.

                            • -

                          • num_decoder_layers (int, optional) – The number of decoder layers in the +

                          • num_decoder_layers (int, optional) – The number of decoder layers in the Transformer decoder. Default: 6.

                            • -

                          • mlp_dims (int, optional) – The hidden dimension of the MLP block in each +

                          • mlp_dims (int, optional) – The hidden dimension of the MLP block in each Transformer layer. Defaults to 4*dims if not provided. Default: None.

                            • -

                          • dropout (float, optional) – The dropout value for the Transformer +

                          • dropout (float, optional) – The dropout value for the Transformer encoder and decoder. Dropout is used after each attention layer and the activation in the MLP layer. Default: 0.0.

                          • activation (function, optional) – the activation function for the MLP @@ -901,10 +903,10 @@ hidden layer. Default: None.

                          • custom_decoder (Module, optional) – A custom decoder to replace the standard Transformer decoder. Default: None.

                            • -

                          • norm_first (bool, optional) – if True, encoder and decoder layers +

                          • norm_first (bool, optional) – if True, encoder and decoder layers will perform layer normalization before attention and MLP operations, otherwise after. Default: True.

                            • -

                          • checkpoint (bool, optional) – if True perform gradient checkpointing +

                          • checkpoint (bool, optional) – if True perform gradient checkpointing to reduce the memory usage at the expense of more computation. Default: False.

                          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 9e289d6c8..04751cfa8 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 0.18.0 documentation + mlx.nn.Upsample — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -871,7 +873,7 @@ document.write(`

                          mlx.nn.Upsample#

                          -class Upsample(scale_factor: float | Tuple, mode: Literal['nearest', 'linear'] = 'nearest', align_corners: bool = False)#
                          +class Upsample(scale_factor: float | Tuple, mode: Literal['nearest', 'linear'] = 'nearest', align_corners: bool = False)#

                          Upsample the input signal spatially.

                          The spatial dimensions are by convention dimensions 1 to x.ndim - 2. The first is the batch dimension and the last is the feature @@ -893,13 +895,13 @@ output will be matching as will the bottom right edge.

                          Parameters:
                            -

                          • scale_factor (float or tuple) – The multiplier for the spatial size. +

                          • scale_factor (float or tuple) – The multiplier for the spatial size. If a float is provided, it is the multiplier for all spatial dimensions. Otherwise, the number of scale factors provided must match the number of spatial dimensions.

                            • -

                          • mode (str, optional) – The upsampling algorithm, either "nearest", +

                          • mode (str, optional) – The upsampling algorithm, either "nearest", "linear" or "cubic". Default: "nearest".

                            • -

                          • align_corners (bool, optional) – Changes the way the corners are treated +

                          • align_corners (bool, optional) – Changes the way the corners are treated during "linear" and "cubic" upsampling. See the note above and the examples below for more details. Default: False.

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.constant.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.constant.html index a46146ea6..1e394e65c 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.constant.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.constant.html @@ -8,7 +8,7 @@ - mlx.nn.init.constant — MLX 0.18.0 documentation + mlx.nn.init.constant — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -871,12 +873,12 @@ document.write(`

                          mlx.nn.init.constant#

                          -constant(value: float, dtype: Dtype = mlx.core.float32) → Callable[[array], array]#
                          +constant(value: float, dtype: Dtype = mlx.core.float32) → Callable[[array], array]#

                          An initializer that returns an array filled with value.

                          Parameters:
                            -

                          • value (float) – The value to fill the array with.

                            • +

                          • value (float) – The value to fill the array with.

                          • dtype (Dtype, optional) – The data type of the array. Default: float32.

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_normal.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_normal.html index 664db7457..79c03415c 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_normal.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_normal.html @@ -8,7 +8,7 @@ - mlx.nn.init.glorot_normal — MLX 0.18.0 documentation + mlx.nn.init.glorot_normal — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -426,6 +427,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -872,7 +874,7 @@ document.write(`

                          mlx.nn.init.glorot_normal#

                          -glorot_normal(dtype: Dtype = mlx.core.float32) → Callable[[array, float], array]#
                          +glorot_normal(dtype: Dtype = mlx.core.float32) → Callable[[array, float], array]#

                          A Glorot normal initializer.

                          This initializer samples from a normal distribution with a standard deviation computed from the number of input (fan_in) and output @@ -891,7 +893,7 @@ with the same shape as the input, filled with samples from the Glorot normal distribution.

                          Return type:
                          -

                          Callable[[array, float], array]

                          +

                          Callable[[array, float], array]

                          Example

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_uniform.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_uniform.html index e9d477d82..438fefdc2 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_uniform.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.glorot_uniform.html @@ -8,7 +8,7 @@ - mlx.nn.init.glorot_uniform — MLX 0.18.0 documentation + mlx.nn.init.glorot_uniform — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -426,6 +427,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -872,7 +874,7 @@ document.write(`

                          mlx.nn.init.glorot_uniform#

                          -glorot_uniform(dtype: Dtype = mlx.core.float32) → Callable[[array, float], array]#
                          +glorot_uniform(dtype: Dtype = mlx.core.float32) → Callable[[array, float], array]#

                          A Glorot uniform initializer.

                          This initializer samples from a uniform distribution with a range computed from the number of input (fan_in) and output (fan_out) @@ -891,7 +893,7 @@ with the same shape as the input, filled with samples from the Glorot uniform distribution.

                          Return type:
                          -

                          Callable[[array, float], array]

                          +

                          Callable[[array, float], array]

                          Example

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.he_normal.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.he_normal.html index 95f34e469..45eff6fbe 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.he_normal.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.he_normal.html @@ -8,7 +8,7 @@ - mlx.nn.init.he_normal — MLX 0.18.0 documentation + mlx.nn.init.he_normal — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -426,6 +427,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -872,7 +874,7 @@ document.write(`

                          mlx.nn.init.he_normal#

                          -he_normal(dtype: Dtype = mlx.core.float32) → Callable[[array, Literal['fan_in', 'fan_out'], float], array]#
                          +he_normal(dtype: Dtype = mlx.core.float32) → Callable[[array, Literal['fan_in', 'fan_out'], float], array]#

                          Build a He normal initializer.

                          This initializer samples from a normal distribution with a standard deviation computed from the number of input (fan_in) or output @@ -894,7 +896,7 @@ array with the same shape as the input, filled with samples from the He normal distribution.

                          Return type:
                          -

                          Callable[[array, str, float], array]

                          +

                          Callable[[array, str, float], array]

                          Example

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.he_uniform.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.he_uniform.html index 219fc82ed..995be092a 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.he_uniform.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.he_uniform.html @@ -8,7 +8,7 @@ - mlx.nn.init.he_uniform — MLX 0.18.0 documentation + mlx.nn.init.he_uniform — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -426,6 +427,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -872,7 +874,7 @@ document.write(`

                          mlx.nn.init.he_uniform#

                          -he_uniform(dtype: Dtype = mlx.core.float32) → Callable[[array, Literal['fan_in', 'fan_out'], float], array]#
                          +he_uniform(dtype: Dtype = mlx.core.float32) → Callable[[array, Literal['fan_in', 'fan_out'], float], array]#

                          A He uniform (Kaiming uniform) initializer.

                          This initializer samples from a uniform distribution with a range computed from the number of input (fan_in) or output (fan_out) @@ -894,7 +896,7 @@ array with the same shape as the input, filled with samples from the He uniform distribution.

                          Return type:
                          -

                          Callable[[array, str, float], array]

                          +

                          Callable[[array, str, float], array]

                          Example

                          diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.identity.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.identity.html index b26ee973b..b65545f85 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.identity.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.identity.html @@ -8,7 +8,7 @@ - mlx.nn.init.identity — MLX 0.18.0 documentation + mlx.nn.init.identity — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                      • Transforms
                          @@ -871,14 +873,14 @@ document.write(`

                          mlx.nn.init.normal#

                          -normal(mean: float = 0.0, std: float = 1.0, dtype: Dtype = mlx.core.float32) → Callable[[array], array]#
                          +normal(mean: float = 0.0, std: float = 1.0, dtype: Dtype = mlx.core.float32) → Callable[[array], array]#

                          An initializer that returns samples from a normal distribution.

                          Parameters:
                            -

                          • mean (float, optional) – Mean of the normal distribution. Default: +

                          • mean (float, optional) – Mean of the normal distribution. Default: 0.0.

                            • -

                          • std (float, optional) – Standard deviation of the normal distribution. +

                          • std (float, optional) – Standard deviation of the normal distribution. Default: 1.0.

                          • dtype (Dtype, optional) – The data type of the array. Default: float32.

                            • diff --git a/docs/build/html/python/nn/_autosummary/mlx.nn.init.uniform.html b/docs/build/html/python/nn/_autosummary/mlx.nn.init.uniform.html index 328446fd1..a433f5cf5 100644 --- a/docs/build/html/python/nn/_autosummary/mlx.nn.init.uniform.html +++ b/docs/build/html/python/nn/_autosummary/mlx.nn.init.uniform.html @@ -8,7 +8,7 @@ - mlx.nn.init.uniform — MLX 0.18.0 documentation + mlx.nn.init.uniform — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                          • mlx.core.repeat
                          • mlx.core.reshape
                          • mlx.core.right_shift
                            • +
                          • mlx.core.roll
                          • mlx.core.round
                          • mlx.core.rsqrt
                          • mlx.core.save
                            • @@ -425,6 +426,7 @@
                          • mlx.core.random.truncated_normal
                          • mlx.core.random.uniform
                          • mlx.core.random.laplace
                            • +
                          • mlx.core.random.permutation
                        • Transforms
                            @@ -871,14 +873,14 @@ document.write(`

                            mlx.nn.init.uniform#

                            -uniform(low: float = 0.0, high: float = 1.0, dtype: Dtype = mlx.core.float32) → Callable[[array], array]#
                            +uniform(low: float = 0.0, high: float = 1.0, dtype: Dtype = mlx.core.float32) → Callable[[array], array]#

                            An initializer that returns samples from a uniform distribution.

                            Parameters:
                              -

                            • low (float, optional) – The lower bound of the uniform distribution. +

                            • low (float, optional) – The lower bound of the uniform distribution. Default: 0.0.

                              • -

                            • high (float, optional) – The upper bound of the uniform distribution. +

                            • high (float, optional) – The upper bound of the uniform distribution. Default: 1.0

                            • dtype (Dtype, optional) – The data type of the array. Default: float32.

                            diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.celu.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.celu.html index aea29e172..86b3b17e1 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.celu.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.celu.html @@ -8,7 +8,7 @@ - mlx.nn.celu — MLX 0.18.0 documentation + mlx.nn.celu — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                          • mlx.core.repeat
                          • mlx.core.reshape
                          • mlx.core.right_shift
                            • +
                          • mlx.core.roll
                          • mlx.core.round
                          • mlx.core.rsqrt
                          • mlx.core.save
                            • @@ -426,6 +427,7 @@
                          • mlx.core.random.truncated_normal
                          • mlx.core.random.uniform
                          • mlx.core.random.laplace
                            • +
                          • mlx.core.random.permutation
                        • Transforms
                        • Transforms
                        • Transforms
                            diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_approx.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_approx.html index 716e107fa..d550531db 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_approx.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_approx.html @@ -8,7 +8,7 @@ - mlx.nn.gelu_approx — MLX 0.18.0 documentation + mlx.nn.gelu_approx — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                          • mlx.core.repeat
                          • mlx.core.reshape
                          • mlx.core.right_shift
                            • +
                          • mlx.core.roll
                          • mlx.core.round
                          • mlx.core.rsqrt
                          • mlx.core.save
                            • @@ -426,6 +427,7 @@
                          • mlx.core.random.truncated_normal
                          • mlx.core.random.uniform
                          • mlx.core.random.laplace
                            • +
                          • mlx.core.random.permutation
                        • Transforms
                            diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html index 8833859ed..674507f66 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.gelu_fast_approx.html @@ -8,7 +8,7 @@ - mlx.nn.gelu_fast_approx — MLX 0.18.0 documentation + mlx.nn.gelu_fast_approx — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                          • mlx.core.repeat
                          • mlx.core.reshape
                          • mlx.core.right_shift
                            • +
                          • mlx.core.roll
                          • mlx.core.round
                          • mlx.core.rsqrt
                          • mlx.core.save
                            • @@ -426,6 +427,7 @@
                          • mlx.core.random.truncated_normal
                          • mlx.core.random.uniform
                          • mlx.core.random.laplace
                            • +
                          • mlx.core.random.permutation
                        • Transforms
                        • Transforms
                            @@ -872,7 +874,7 @@ document.write(`

                            mlx.nn.glu#

                            -class glu(x: array, axis: int = -1)#
                            +class glu(x: array, axis: int = -1)#

                            Applies the gated linear unit function.

                            This function splits the axis dimension of the input into two halves (\(a\) and \(b\)) and applies \(a * \sigma(b)\).

                            @@ -880,7 +882,7 @@ document.write(` \[\textrm{GLU}(x) = a * \sigma(b)\]
                            Parameters:
                            -

                            axis (int) – The dimension to split along. Default: -1

                            +

                            axis (int) – The dimension to split along. Default: -1

                            diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_shrink.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_shrink.html index f974dcba0..38e7912f6 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_shrink.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.hard_shrink.html @@ -8,7 +8,7 @@ - mlx.nn.hard_shrink — MLX 0.18.0 documentation + mlx.nn.hard_shrink — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                          • mlx.core.repeat
                          • mlx.core.reshape
                          • mlx.core.right_shift
                            • +
                          • mlx.core.roll
                          • mlx.core.round
                          • mlx.core.rsqrt
                          • mlx.core.save
                            • @@ -426,6 +427,7 @@
                          • mlx.core.random.truncated_normal
                          • mlx.core.random.uniform
                          • mlx.core.random.laplace
                            • +
                          • mlx.core.random.permutation
                        • Transforms
                        • Transforms
                        • Transforms
                        • Transforms
                            diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.log_sigmoid.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.log_sigmoid.html index 1ba8d3b8e..68c6d49a3 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.log_sigmoid.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.log_sigmoid.html @@ -8,7 +8,7 @@ - mlx.nn.log_sigmoid — MLX 0.18.0 documentation + mlx.nn.log_sigmoid — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                          • mlx.core.repeat
                          • mlx.core.reshape
                          • mlx.core.right_shift
                            • +
                          • mlx.core.roll
                          • mlx.core.round
                          • mlx.core.rsqrt
                          • mlx.core.save
                            • @@ -426,6 +427,7 @@
                          • mlx.core.random.truncated_normal
                          • mlx.core.random.uniform
                          • mlx.core.random.laplace
                            • +
                          • mlx.core.random.permutation
                        • Transforms
                            diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.log_softmax.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.log_softmax.html index 9ab81ae92..afd84d759 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.log_softmax.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.log_softmax.html @@ -8,7 +8,7 @@ - mlx.nn.log_softmax — MLX 0.18.0 documentation + mlx.nn.log_softmax — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                          • mlx.core.repeat
                          • mlx.core.reshape
                          • mlx.core.right_shift
                            • +
                          • mlx.core.roll
                          • mlx.core.round
                          • mlx.core.rsqrt
                          • mlx.core.save
                            • @@ -426,6 +427,7 @@
                          • mlx.core.random.truncated_normal
                          • mlx.core.random.uniform
                          • mlx.core.random.laplace
                            • +
                          • mlx.core.random.permutation
                        • Transforms
                            diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.binary_cross_entropy.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.binary_cross_entropy.html index 1f9d9664e..7cf0bef4b 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.binary_cross_entropy.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.binary_cross_entropy.html @@ -8,7 +8,7 @@ - mlx.nn.losses.binary_cross_entropy — MLX 0.18.0 documentation + mlx.nn.losses.binary_cross_entropy — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                          • mlx.core.repeat
                          • mlx.core.reshape
                          • mlx.core.right_shift
                            • +
                          • mlx.core.roll
                          • mlx.core.round
                          • mlx.core.rsqrt
                          • mlx.core.save
                            • @@ -425,6 +426,7 @@
                          • mlx.core.random.truncated_normal
                          • mlx.core.random.uniform
                          • mlx.core.random.laplace
                            • +
                          • mlx.core.random.permutation
                        • Transforms
                            @@ -871,7 +873,7 @@ document.write(`

                            mlx.nn.losses.binary_cross_entropy#

                            -class binary_cross_entropy(inputs: array, targets: array, weights: array | None = None, with_logits: bool = True, reduction: Literal['none', 'mean', 'sum'] = 'mean')#
                            +class binary_cross_entropy(inputs: array, targets: array, weights: array | None = None, with_logits: bool = True, reduction: Literal['none', 'mean', 'sum'] = 'mean')#

                            Computes the binary cross entropy loss.

                            By default, this function takes the pre-sigmoid logits, which results in a faster and more precise loss. For improved numerical stability when with_logits=False, @@ -883,9 +885,9 @@ of -100

                            inputs (array) – The predicted values. If with_logits is True, then inputs are unnormalized logits. Otherwise, inputs are probabilities.

                          • targets (array) – The binary target values in {0, 1}.

                            • -

                          • with_logits (bool, optional) – Whether inputs are logits. Default: True.

                            • +

                          • with_logits (bool, optional) – Whether inputs are logits. Default: True.

                          • weights (array, optional) – Optional weights for each target. Default: None.

                            • -

                          • reduction (str, optional) – Specifies the reduction to apply to the output: +

                          • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'mean'.

                          • diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.cosine_similarity_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.cosine_similarity_loss.html index b5e308ada..01fc6856b 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.cosine_similarity_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.cosine_similarity_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.cosine_similarity_loss — MLX 0.18.0 documentation + mlx.nn.losses.cosine_similarity_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -426,6 +427,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -872,7 +874,7 @@ document.write(`

                          mlx.nn.losses.cosine_similarity_loss#

                          -class cosine_similarity_loss(x1: array, x2: array, axis: int = 1, eps: float = 1e-08, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                          +class cosine_similarity_loss(x1: array, x2: array, axis: int = 1, eps: float = 1e-08, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                          Computes the cosine similarity between the two inputs.

                          The cosine similarity loss is given by

                          @@ -882,10 +884,10 @@ document.write(`

                          • x1 (mx.array) – The first set of inputs.

                          • x2 (mx.array) – The second set of inputs.

                            • -

                          • axis (int, optional) – The embedding axis. Default: 1.

                            • -

                          • eps (float, optional) – The minimum value of the denominator used for +

                          • axis (int, optional) – The embedding axis. Default: 1.

                            • +

                          • eps (float, optional) – The minimum value of the denominator used for numerical stability. Default: 1e-8.

                            • -

                          • reduction (str, optional) – Specifies the reduction to apply to the output: +

                          • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                          diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.cross_entropy.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.cross_entropy.html index 9d6d3e3d1..48a286713 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.cross_entropy.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.cross_entropy.html @@ -8,7 +8,7 @@ - mlx.nn.losses.cross_entropy — MLX 0.18.0 documentation + mlx.nn.losses.cross_entropy — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                        • mlx.core.repeat
                        • mlx.core.reshape
                        • mlx.core.right_shift
                          • +
                        • mlx.core.roll
                        • mlx.core.round
                        • mlx.core.rsqrt
                        • mlx.core.save
                          • @@ -425,6 +426,7 @@
                        • mlx.core.random.truncated_normal
                        • mlx.core.random.uniform
                        • mlx.core.random.laplace
                          • +
                        • mlx.core.random.permutation
                      • Transforms
                          @@ -871,7 +873,7 @@ document.write(`

                          mlx.nn.losses.cross_entropy#

                          -class cross_entropy(logits: array, targets: array, weights: array | None = None, axis: int = -1, label_smoothing: float = 0.0, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                          +class cross_entropy(logits: array, targets: array, weights: array | None = None, axis: int = -1, label_smoothing: float = 0.0, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                          Computes the cross entropy loss.

                          Parameters:
                          @@ -884,9 +886,9 @@ the axistargets shape should be the same as the logits shape.

                        • weights (array, optional) – Optional weights for each target. Default: None.

                          • -

                        • axis (int, optional) – The axis over which to compute softmax. Default: -1.

                          • -

                        • label_smoothing (float, optional) – Label smoothing factor. Default: 0.

                          • -

                        • reduction (str, optional) – Specifies the reduction to apply to the output: +

                        • axis (int, optional) – The axis over which to compute softmax. Default: -1.

                          • +

                        • label_smoothing (float, optional) – Label smoothing factor. Default: 0.

                          • +

                        • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                        • diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.gaussian_nll_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.gaussian_nll_loss.html index b4a9bbcce..620210e8c 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.gaussian_nll_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.gaussian_nll_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.gaussian_nll_loss — MLX 0.18.0 documentation + mlx.nn.losses.gaussian_nll_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                      • mlx.core.repeat
                      • mlx.core.reshape
                      • mlx.core.right_shift
                        • +
                      • mlx.core.roll
                      • mlx.core.round
                      • mlx.core.rsqrt
                      • mlx.core.save
                        • @@ -426,6 +427,7 @@
                      • mlx.core.random.truncated_normal
                      • mlx.core.random.uniform
                      • mlx.core.random.laplace
                        • +
                      • mlx.core.random.permutation
                    • Transforms
                        @@ -872,7 +874,7 @@ document.write(`

                        mlx.nn.losses.gaussian_nll_loss#

                        -class gaussian_nll_loss(inputs: array, targets: array, vars: array, full: bool = False, eps: float = 1e-06, reduction: Literal['none', 'mean', 'sum'] = 'mean')#
                        +class gaussian_nll_loss(inputs: array, targets: array, vars: array, full: bool = False, eps: float = 1e-06, reduction: Literal['none', 'mean', 'sum'] = 'mean')#

                        Computes the negative log likelihood loss for a Gaussian distribution.

                        The loss is given by:

                        @@ -887,11 +889,11 @@ predicted variances.

                      • inputs (array) – The predicted expectation of the Gaussian distribution.

                      • targets (array) – The target values (samples from the Gaussian distribution).

                      • vars (array) – The predicted variance of the Gaussian distribution.

                        • -

                      • full (bool, optional) – Whether to include the constant term in the loss calculation. +

                      • full (bool, optional) – Whether to include the constant term in the loss calculation. Default: False.

                        • -

                      • eps (float, optional) – Small positive constant for numerical stability. +

                      • eps (float, optional) – Small positive constant for numerical stability. Default: 1e-6.

                        • -

                      • reduction (str, optional) – Specifies the reduction to apply to the output: +

                      • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                      • diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.hinge_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.hinge_loss.html index 3ebc37656..424d48c85 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.hinge_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.hinge_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.hinge_loss — MLX 0.18.0 documentation + mlx.nn.losses.hinge_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -426,6 +427,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      @@ -872,7 +874,7 @@ document.write(`

                      mlx.nn.losses.hinge_loss#

                      -class hinge_loss(inputs: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                      +class hinge_loss(inputs: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                      Computes the hinge loss between inputs and targets.

                      \[\text{hinge}(y, y_{\text{pred}}) = \max(0, 1 - y \cdot y_{\text{pred}})\]
                      @@ -881,7 +883,7 @@ document.write(`

                      • inputs (array) – The predicted values.

                      • targets (array) – The target values. They should be -1 or 1.

                        • -

                      • reduction (str, optional) – Specifies the reduction to apply to the output: +

                      • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                      diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.huber_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.huber_loss.html index f15df2540..c878aee71 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.huber_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.huber_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.huber_loss — MLX 0.18.0 documentation + mlx.nn.losses.huber_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -426,6 +427,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      @@ -872,7 +874,7 @@ document.write(`

                      mlx.nn.losses.huber_loss#

                      -class huber_loss(inputs: array, targets: array, delta: float = 1.0, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                      +class huber_loss(inputs: array, targets: array, delta: float = 1.0, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                      Computes the Huber loss between inputs and targets.

                      \[\begin{split}l_{\delta}(a) = @@ -885,9 +887,9 @@ document.write(`

                      • inputs (array) – The predicted values.

                      • targets (array) – The target values.

                        • -

                      • delta (float, optional) – The threshold at which to change between L1 and L2 loss. +

                      • delta (float, optional) – The threshold at which to change between L1 and L2 loss. Default: 1.0.

                        • -

                      • reduction (str, optional) – Specifies the reduction to apply to the output: +

                      • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                      diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.kl_div_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.kl_div_loss.html index c77736112..fcd638f19 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.kl_div_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.kl_div_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.kl_div_loss — MLX 0.18.0 documentation + mlx.nn.losses.kl_div_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -425,6 +426,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      @@ -871,7 +873,7 @@ document.write(`

                      mlx.nn.losses.kl_div_loss#

                      -class kl_div_loss(inputs: array, targets: array, axis: int = -1, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                      +class kl_div_loss(inputs: array, targets: array, axis: int = -1, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                      Computes the Kullback-Leibler divergence loss.

                      Computes the following when reduction == 'none':

                      mx.exp(targets) * (targets - inputs).sum(axis)
@@ -882,8 +884,8 @@ document.write(`
 
                        
 
                      • inputs (array) – Log probabilities for the predicted distribution.
                        • 
 
                      • targets (array) – Log probabilities for the target distribution.
                        • 
-
                      • axis (int, optional) – The distribution axis. Default: -1.
                        • 
-
                      • reduction (str, optional) – Specifies the reduction to apply to the output:
+
                      • axis (int, optional) – The distribution axis. Default: -1.
                        • 
+
                      • reduction (str, optional) – Specifies the reduction to apply to the output:
 'none' | 'mean' | 'sum'. Default: 'none'.
                        • 
 
                      
 
                      
diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.l1_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.l1_loss.html
index f7c2fca82..93fec6d65 100644
--- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.l1_loss.html
+++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.l1_loss.html
@@ -8,7 +8,7 @@
     
     
 
-    mlx.nn.losses.l1_loss — MLX 0.18.0 documentation
+    mlx.nn.losses.l1_loss — MLX 0.18.1 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -131,8 +131,8 @@
       
     
     
-    MLX 0.18.0 documentation - Home
-    
+    MLX 0.18.1 documentation - Home
+
                      @@ -370,6 +370,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -425,6 +426,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      @@ -871,14 +873,14 @@ document.write(`

                      mlx.nn.losses.l1_loss#

                      -class l1_loss(predictions: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'mean')#
                      +class l1_loss(predictions: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'mean')#

                      Computes the L1 loss.

                      Parameters:

                      • predictions (array) – The predicted values.

                      • targets (array) – The target values.

                        • -

                      • reduction (str, optional) – Specifies the reduction to apply to the output: +

                      • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'mean'.

                      diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.log_cosh_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.log_cosh_loss.html index 9146514ce..b718defb5 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.log_cosh_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.log_cosh_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.log_cosh_loss — MLX 0.18.0 documentation + mlx.nn.losses.log_cosh_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -426,6 +427,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      @@ -872,7 +874,7 @@ document.write(`

                      mlx.nn.losses.log_cosh_loss#

                      -class log_cosh_loss(inputs: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                      +class log_cosh_loss(inputs: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                      Computes the log cosh loss between inputs and targets.

                      Logcosh acts like L2 loss for small errors, ensuring stable gradients, and like the L1 loss for large errors, reducing sensitivity to outliers. This @@ -886,7 +888,7 @@ dual behavior offers a balanced, robust approach for regression tasks.

                      • inputs (array) – The predicted values.

                      • targets (array) – The target values.

                        • -

                      • reduction (str, optional) – Specifies the reduction to apply to the output: +

                      • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                      diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.margin_ranking_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.margin_ranking_loss.html index f75ae9155..42adb9671 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.margin_ranking_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.margin_ranking_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.margin_ranking_loss — MLX 0.18.0 documentation + mlx.nn.losses.margin_ranking_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                    • mlx.core.repeat
                    • mlx.core.reshape
                    • mlx.core.right_shift
                      • +
                    • mlx.core.roll
                    • mlx.core.round
                    • mlx.core.rsqrt
                    • mlx.core.save
                      • @@ -426,6 +427,7 @@
                    • mlx.core.random.truncated_normal
                    • mlx.core.random.uniform
                    • mlx.core.random.laplace
                      • +
                    • mlx.core.random.permutation
                  • Transforms
                      @@ -872,7 +874,7 @@ document.write(`

                      mlx.nn.losses.margin_ranking_loss#

                      -class margin_ranking_loss(inputs1: array, inputs2: array, targets: array, margin: float = 0.0, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                      +class margin_ranking_loss(inputs1: array, inputs2: array, targets: array, margin: float = 0.0, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                      Calculate the margin ranking loss that loss given inputs \(x_1\), \(x_2\) and a label \(y\) (containing 1 or -1).

                      The loss is given by:

                      @@ -887,9 +889,9 @@ represents inputs2<

                    • inputs2 (array) – Scores for the second input.

                    • targets (array) – Labels indicating whether samples in inputs1 should be ranked higher than samples in inputs2. Values should be 1 or -1.

                      • -

                    • margin (float, optional) – The margin by which the scores should be separated. +

                    • margin (float, optional) – The margin by which the scores should be separated. Default: 0.0.

                      • -

                    • reduction (str, optional) – Specifies the reduction to apply to the output: +

                    • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                    • diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.mse_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.mse_loss.html index 5fc8c6df6..02bfa2a43 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.mse_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.mse_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.mse_loss — MLX 0.18.0 documentation + mlx.nn.losses.mse_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -425,6 +426,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -871,14 +873,14 @@ document.write(`

                    mlx.nn.losses.mse_loss#

                    -class mse_loss(predictions: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'mean')#
                    +class mse_loss(predictions: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'mean')#

                    Computes the mean squared error loss.

                    Parameters:

                    • predictions (array) – The predicted values.

                    • targets (array) – The target values.

                      • -

                    • reduction (str, optional) – Specifies the reduction to apply to the output: +

                    • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'mean'.

                    diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.nll_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.nll_loss.html index 0f841c5f1..4d9dc834b 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.nll_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.nll_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.nll_loss — MLX 0.18.0 documentation + mlx.nn.losses.nll_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -425,6 +426,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -871,15 +873,15 @@ document.write(`

                    mlx.nn.losses.nll_loss#

                    -class nll_loss(inputs: array, targets: array, axis: int = -1, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                    +class nll_loss(inputs: array, targets: array, axis: int = -1, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                    Computes the negative log likelihood loss.

                    Parameters:

                    • inputs (array) – The predicted distribution in log space.

                    • targets (array) – The target values.

                      • -

                    • axis (int, optional) – The distribution axis. Default: -1.

                      • -

                    • reduction (str, optional) – Specifies the reduction to apply to the output: +

                    • axis (int, optional) – The distribution axis. Default: -1.

                      • +

                    • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                    diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.smooth_l1_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.smooth_l1_loss.html index 74c060c1f..284cb8d61 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.smooth_l1_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.smooth_l1_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.smooth_l1_loss — MLX 0.18.0 documentation + mlx.nn.losses.smooth_l1_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -426,6 +427,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.losses.smooth_l1_loss#

                    -class smooth_l1_loss(predictions: array, targets: array, beta: float = 1.0, reduction: Literal['none', 'mean', 'sum'] = 'mean')#
                    +class smooth_l1_loss(predictions: array, targets: array, beta: float = 1.0, reduction: Literal['none', 'mean', 'sum'] = 'mean')#

                    Computes the smooth L1 loss.

                    The smooth L1 loss is a variant of the L1 loss which replaces the absolute difference with a squared difference when the absolute difference is less @@ -888,9 +890,9 @@ than beta

                    • predictions (array) – Predicted values.

                    • targets (array) – Ground truth values.

                      • -

                    • beta (float, optional) – The threshold after which the loss changes +

                    • beta (float, optional) – The threshold after which the loss changes from the squared to the absolute difference. Default: 1.0.

                      • -

                    • reduction (str, optional) – Specifies the reduction to apply to the output: +

                    • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'mean'.

                    diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.triplet_loss.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.triplet_loss.html index 2bf1bc6d8..0dcbb7044 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.triplet_loss.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.losses.triplet_loss.html @@ -8,7 +8,7 @@ - mlx.nn.losses.triplet_loss — MLX 0.18.0 documentation + mlx.nn.losses.triplet_loss — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                  • mlx.core.repeat
                  • mlx.core.reshape
                  • mlx.core.right_shift
                    • +
                  • mlx.core.roll
                  • mlx.core.round
                  • mlx.core.rsqrt
                  • mlx.core.save
                    • @@ -426,6 +427,7 @@
                  • mlx.core.random.truncated_normal
                  • mlx.core.random.uniform
                  • mlx.core.random.laplace
                    • +
                  • mlx.core.random.permutation
                • Transforms
                    @@ -872,7 +874,7 @@ document.write(`

                    mlx.nn.losses.triplet_loss#

                    -class triplet_loss(anchors: array, positives: array, negatives: array, axis: int = -1, p: int = 2, margin: float = 1.0, eps: float = 1e-06, reduction: Literal['none', 'mean', 'sum'] = 'none')#
                    +class triplet_loss(anchors: array, positives: array, negatives: array, axis: int = -1, p: int = 2, margin: float = 1.0, eps: float = 1e-06, reduction: Literal['none', 'mean', 'sum'] = 'none')#

                    Computes the triplet loss for a set of anchor, positive, and negative samples. Margin is represented with alpha in the math section.

                    @@ -883,11 +885,11 @@ Margin is represented with alpha in the math section.

                  • anchors (array) – The anchor samples.

                  • positives (array) – The positive samples.

                  • negatives (array) – The negative samples.

                    • -

                  • axis (int, optional) – The distribution axis. Default: -1.

                    • -

                  • p (int, optional) – The norm degree for pairwise distance. Default: 2.

                    • -

                  • margin (float, optional) – Margin for the triplet loss. Defaults to 1.0.

                    • -

                  • eps (float, optional) – Small positive constant to prevent numerical instability. Defaults to 1e-6.

                    • -

                  • reduction (str, optional) – Specifies the reduction to apply to the output: +

                  • axis (int, optional) – The distribution axis. Default: -1.

                    • +

                  • p (int, optional) – The norm degree for pairwise distance. Default: 2.

                    • +

                  • margin (float, optional) – Margin for the triplet loss. Defaults to 1.0.

                    • +

                  • eps (float, optional) – Small positive constant to prevent numerical instability. Defaults to 1e-6.

                    • +

                  • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

                  • diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.mish.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.mish.html index 7b269d621..befad8f31 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.mish.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.mish.html @@ -8,7 +8,7 @@ - mlx.nn.mish — MLX 0.18.0 documentation + mlx.nn.mish — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.nn.softshrink#

                  -class softshrink(x, lambd: float = 0.5)#
                  +class softshrink(x, lambd: float = 0.5)#

                  Applies the Softshrink activation function.

                  \[\begin{split}\text{softshrink}(x) = \begin{cases} diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.step.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.step.html index 712f17d48..903247110 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.step.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.step.html @@ -8,7 +8,7 @@ - mlx.nn.step — MLX 0.18.0 documentation + mlx.nn.step — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
                  @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.nn.step#

                  -class step(x: array, threshold: float = 0.0)#
                  +class step(x: array, threshold: float = 0.0)#

                  Applies the Step Activation Function.

                  This function implements a binary step activation, where the output is set to 1 if the input is greater than a specified threshold, and 0 otherwise.

                  diff --git a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.tanh.html b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.tanh.html index 5553aa66d..dba3564fa 100644 --- a/docs/build/html/python/nn/_autosummary_functions/mlx.nn.tanh.html +++ b/docs/build/html/python/nn/_autosummary_functions/mlx.nn.tanh.html @@ -8,7 +8,7 @@ - mlx.nn.tanh — MLX 0.18.0 documentation + mlx.nn.tanh — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
              • Transforms
                  @@ -880,7 +882,7 @@ document.write(`

                  An or reduction over the given axes.

                  arange(-> array)

                  -

                  Generates ranges of numbers.

                  +

                  Overloaded function.

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

                  Element-wise inverse cosine.

                  @@ -1227,124 +1229,127 @@ document.write(`

                  right_shift(a, b[, stream])

                  Element-wise right shift.

                  -

                  round(a, /[, decimals, stream])

                  +

                  roll(a, shift[, axis, stream])

                  +

                  Roll array elements along a given axis.

                  + +

                  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.

                  -

                  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.

                  -

                  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.

                  diff --git a/docs/build/html/python/optimizers.html b/docs/build/html/python/optimizers.html index c8dc9f9c8..7ccf70915 100644 --- a/docs/build/html/python/optimizers.html +++ b/docs/build/html/python/optimizers.html @@ -8,7 +8,7 @@ - Optimizers — MLX 0.18.0 documentation + Optimizers — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdaDelta.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdaDelta.html index 1662a033c..e6320b0cf 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdaDelta.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdaDelta.html @@ -8,7 +8,7 @@ - mlx.optimizers.AdaDelta — MLX 0.18.0 documentation + mlx.optimizers.AdaDelta — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.optimizers.AdaDelta#

                  -class AdaDelta(learning_rate: float | Callable[[array], array], rho: float = 0.9, eps: float = 1e-06)#
                  +class AdaDelta(learning_rate: float | Callable[[array], array], rho: float = 0.9, eps: float = 1e-06)#

                  The AdaDelta optimizer with a learning rate [1].

                  Our AdaDelta implementation follows the original paper. In detail,

                  [1]: Zeiler, M.D., 2012. ADADELTA: an adaptive learning rate method. arXiv preprint arXiv:1212.5701.

                  @@ -884,10 +886,10 @@ w_{t+1} &= w_t - \lambda \Delta w_{t+1}\end{split}\]
                  Parameters:
                    -

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • -

                  • rho (float, optional) – The coefficient \(\rho\) used for computing a +

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • +

                  • rho (float, optional) – The coefficient \(\rho\) used for computing a running average of squared gradients. Default: 0.9

                    • -

                  • eps (float, optional) – The term \(\epsilon\) added to the denominator to improve +

                  • eps (float, optional) – The term \(\epsilon\) added to the denominator to improve numerical stability. Default: 1e-8

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adafactor.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adafactor.html index f34450b1c..9ff57a584 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adafactor.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adafactor.html @@ -8,7 +8,7 @@ - mlx.optimizers.Adafactor — MLX 0.18.0 documentation + mlx.optimizers.Adafactor — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,35 +874,35 @@ document.write(`

                  mlx.optimizers.Adafactor#

                  -class Adafactor(learning_rate: float | Callable[[array], array] | None = None, eps: Tuple[float, float] = (1e-30, 0.001), clip_threshold: float = 1.0, decay_rate: float = -0.8, beta_1: float | None = None, weight_decay: float = 0.0, scale_parameter: bool = True, relative_step: bool = True, warmup_init: bool = False)#
                  +class Adafactor(learning_rate: float | Callable[[array], array] | None = None, eps: Tuple[float, float] = (1e-30, 0.001), clip_threshold: float = 1.0, decay_rate: float = -0.8, beta_1: float | None = None, weight_decay: float = 0.0, scale_parameter: bool = True, relative_step: bool = True, warmup_init: bool = False)#

                  The Adafactor optimizer.

                  Our Adafactor implementation follows the original paper: Adafactor: Adaptive Learning Rates with Sublinear Memory Cost

                  Parameters:
                    -

                  • learning_rate (float or callable, optional) – The learning rate. +

                  • learning_rate (float or callable, optional) – The learning rate. Default: None.

                    • -

                  • eps (tuple(float, float), optional) – The first term \(\epsilon_1\) +

                  • eps (tuple(float, float), optional) – The first term \(\epsilon_1\) added to the square of the gradients to improve numerical stability and the second term \(\epsilon_2\) is used for parameter scaling if parameter_scale is set to True. Default: (1e-30, 1e-3).

                    • -

                  • clip_threshold (float, optional) – Clips the unscaled update at +

                  • clip_threshold (float, optional) – Clips the unscaled update at clip_threshold. Default: 1.0.

                    • -

                  • decay_rate (float, optional) – Coefficient for the running average +

                  • decay_rate (float, optional) – Coefficient for the running average of the squared gradient. Default: -0.8.

                    • -

                  • beta_1 (float, optional) – If set to a value bigger than zero +

                  • beta_1 (float, optional) – If set to a value bigger than zero then first moment will be used. Default: None.

                    • -

                  • weight_decay (float, optional) – The weight decay \(\lambda\). +

                  • weight_decay (float, optional) – The weight decay \(\lambda\). Default: 0.0.

                    • -

                  • scale_parameter (bool, optional) – If set to True the learning rate +

                  • scale_parameter (bool, optional) – If set to True the learning rate will be scaled by \(\max(\epsilon_1, \text{RMS}(w_{t-1}))\). Default: True.

                    • -

                  • relative_step (bool, optional) – If set to True the learning_rate +

                  • relative_step (bool, optional) – If set to True the learning_rate will be ignored and relative step size will be computed. Default: True.

                    • -

                  • warmup_init (bool, optional) – If set to True then the relative +

                  • warmup_init (bool, optional) – If set to True then the relative step size will be calculated by the current step. Default: False.

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adagrad.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adagrad.html index f9d97ca34..577291163 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adagrad.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adagrad.html @@ -8,7 +8,7 @@ - mlx.optimizers.Adagrad — MLX 0.18.0 documentation + mlx.optimizers.Adagrad — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.optimizers.Adagrad#

                  -class Adagrad(learning_rate: float | Callable[[array], array], eps: float = 1e-08)#
                  +class Adagrad(learning_rate: float | Callable[[array], array], eps: float = 1e-08)#

                  The Adagrad optimizer [1].

                  Our Adagrad implementation follows the original paper. In detail,

                  [1]: Duchi, J., Hazan, E. and Singer, Y., 2011. Adaptive subgradient methods @@ -883,8 +885,8 @@ w_{t+1} &= w_t - \lambda \frac{g_t}{\sqrt{v_{t+1}} + \epsilon}\end{split}\]<

                  Parameters:
                    -

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • -

                  • eps (float, optional) – The term \(\epsilon\) added to the +

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • +

                  • eps (float, optional) – The term \(\epsilon\) added to the denominator to improve numerical stability. Default: 1e-8

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adam.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adam.html index 391881959..282d5283d 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adam.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adam.html @@ -8,7 +8,7 @@ - mlx.optimizers.Adam — MLX 0.18.0 documentation + mlx.optimizers.Adam — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.optimizers.Adam#

                  -class Adam(learning_rate: float | Callable[[array], array], betas: List[float] = [0.9, 0.999], eps: float = 1e-08)#
                  +class Adam(learning_rate: float | Callable[[array], array], betas: List[float] = [0.9, 0.999], eps: float = 1e-08)#

                  The Adam optimizer [1].

                  Our Adam implementation follows the original paper and omits the bias correction in the first and second moment estimates. In detail,

                  @@ -885,11 +887,11 @@ w_{t+1} &= w_t - \lambda \frac{m_{t+1}}{\sqrt{v_{t+1} + \epsilon}}\end{split
                  Parameters:
                    -

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • -

                  • betas (Tuple[float, float], optional) – The coefficients +

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • +

                  • betas (Tuple[float, float], optional) – The coefficients \((\beta_1, \beta_2)\) used for computing running averages of the gradient and its square. Default: (0.9, 0.999)

                    • -

                  • eps (float, optional) – The term \(\epsilon\) added to the +

                  • eps (float, optional) – The term \(\epsilon\) added to the denominator to improve numerical stability. Default: 1e-8

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdamW.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdamW.html index 18f084bda..2040a8922 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdamW.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.AdamW.html @@ -8,7 +8,7 @@ - mlx.optimizers.AdamW — MLX 0.18.0 documentation + mlx.optimizers.AdamW — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.optimizers.AdamW#

                  -class AdamW(learning_rate: float | Callable[[array], array], betas: List[float] = [0.9, 0.999], eps: float = 1e-08, weight_decay: float = 0.01)#
                  +class AdamW(learning_rate: float | Callable[[array], array], betas: List[float] = [0.9, 0.999], eps: float = 1e-08, weight_decay: float = 0.01)#

                  The AdamW optimizer [1].

                  Following the above convention, in contrast with [1], we do not use bias correction in the first and second moments for AdamW. We update the weights @@ -886,13 +888,13 @@ w_{t+1} &= w_t - \alpha (\frac{m_{t+1}}{\sqrt{v_{t+1} + \epsilon}} + \lambda

                  Parameters:
                    -

                  • learning_rate (float or callable) – The learning rate \(\alpha\).

                    • -

                  • betas (Tuple[float, float], optional) – The coefficients +

                  • learning_rate (float or callable) – The learning rate \(\alpha\).

                    • +

                  • betas (Tuple[float, float], optional) – The coefficients \((\beta_1, \beta_2)\) used for computing running averages of the gradient and its square. Default: (0.9, 0.999)

                    • -

                  • eps (float, optional) – The term \(\epsilon\) added to the +

                  • eps (float, optional) – The term \(\epsilon\) added to the denominator to improve numerical stability. Default: 1e-8

                    • -

                  • weight_decay (float, optional) – The weight decay \(\lambda\). +

                  • weight_decay (float, optional) – The weight decay \(\lambda\). Default: 0.

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adamax.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adamax.html index 490914c50..e71b320e5 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adamax.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Adamax.html @@ -8,7 +8,7 @@ - mlx.optimizers.Adamax — MLX 0.18.0 documentation + mlx.optimizers.Adamax — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.optimizers.Adamax#

                  -class Adamax(learning_rate: float | Callable[[array], array], betas: List[float] = [0.9, 0.999], eps: float = 1e-08)#
                  +class Adamax(learning_rate: float | Callable[[array], array], betas: List[float] = [0.9, 0.999], eps: float = 1e-08)#

                  The Adamax optimizer, a variant of Adam based on the infinity norm [1].

                  Our Adam implementation follows the original paper and omits the bias correction in the first and second moment estimates. In detail,

                  @@ -885,11 +887,11 @@ w_{t+1} &= w_t - \lambda \frac{m_{t+1}}{v_{t+1} + \epsilon}\end{split}\]
                  Parameters:
                    -

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • -

                  • betas (Tuple[float, float], optional) – The coefficients +

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • +

                  • betas (Tuple[float, float], optional) – The coefficients \((\beta_1, \beta_2)\) used for computing running averages of the gradient and its square. Default: (0.9, 0.999)

                    • -

                  • eps (float, optional) – The term \(\epsilon\) added to the +

                  • eps (float, optional) – The term \(\epsilon\) added to the denominator to improve numerical stability. Default: 1e-8

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Lion.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Lion.html index dca4838a9..34a1fdbff 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Lion.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Lion.html @@ -8,7 +8,7 @@ - mlx.optimizers.Lion — MLX 0.18.0 documentation + mlx.optimizers.Lion — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.optimizers.Lion#

                  -class Lion(learning_rate: float | Callable[[array], array], betas: List[float] = [0.9, 0.99], weight_decay: float = 0.0)#
                  +class Lion(learning_rate: float | Callable[[array], array], betas: List[float] = [0.9, 0.99], weight_decay: float = 0.0)#

                  The Lion optimizer [1].

                  Since updates are computed through the sign operation, they tend to have larger norm than for other optimizers such as SGD and Adam. @@ -889,11 +891,11 @@ w_{t + 1} &= w_t - \eta (\text{sign}(c_t) + \lambda w_t)\end{split}\]

                  Parameters:
                    -

                  • learning_rate (float or callable) – The learning rate \(\eta\).

                    • -

                  • betas (Tuple[float, float], optional) – The coefficients +

                  • learning_rate (float or callable) – The learning rate \(\eta\).

                    • +

                  • betas (Tuple[float, float], optional) – The coefficients \((\beta_1, \beta_2)\) used for computing the gradient momentum and update direction. Default: (0.9, 0.99)

                    • -

                  • weight_decay (float, optional) – The weight decay \(\lambda\). Default: 0.0

                    • +

                  • weight_decay (float, optional) – The weight decay \(\lambda\). Default: 0.0

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html index dab3e2f5d..f5bc7b031 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.apply_gradients.html @@ -8,7 +8,7 @@ - mlx.optimizers.Optimizer.apply_gradients — MLX 0.18.0 documentation + mlx.optimizers.Optimizer.apply_gradients — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -871,7 +873,7 @@ document.write(`

                  mlx.optimizers.Optimizer.apply_gradients#

                  -Optimizer.apply_gradients(gradients: dict, parameters: dict)#
                  +Optimizer.apply_gradients(gradients: dict, parameters: dict)#

                  Apply the gradients to the parameters and return the updated parameters.

                  Can be used to update a model via model.update(opt.apply_gradients(grads, model)) which is precisely @@ -879,8 +881,8 @@ how

                  Parameters:
                    -

                  • gradients (dict) – A Python tree of gradients.

                    • -

                  • parameters (dict) – A Python tree of parameters. It can be a +

                  • gradients (dict) – A Python tree of gradients.

                    • +

                  • parameters (dict) – A Python tree of parameters. It can be a superset of the gradients. In that case the returned python tree will be of the same structure as the gradients.

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.init.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.init.html index ee65ecd12..997b30e86 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.init.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.init.html @@ -8,7 +8,7 @@ - mlx.optimizers.Optimizer.init — MLX 0.18.0 documentation + mlx.optimizers.Optimizer.init — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -871,7 +873,7 @@ document.write(`

                  mlx.optimizers.Optimizer.init#

                  -Optimizer.init(parameters: dict)#
                  +Optimizer.init(parameters: dict)#

                  Initialize the optimizer’s state

                  This function can be used to initialize optimizers which have state (like momentum in SGD). Using this method is optional as the @@ -881,7 +883,7 @@ to have access to the Optimizer.update().

                  Parameters:
                  -

                  model (dict) – A Python tree of parameters.

                  +

                  model (dict) – A Python tree of parameters.

                  Example

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html index aea35ba7c..c7a053c2f 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.state.html @@ -8,7 +8,7 @@ - mlx.optimizers.Optimizer.state — MLX 0.18.0 documentation + mlx.optimizers.Optimizer.state — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.update.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.update.html index c5ef8cf14..6b04ad214 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.update.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.Optimizer.update.html @@ -8,7 +8,7 @@ - mlx.optimizers.Optimizer.update — MLX 0.18.0 documentation + mlx.optimizers.Optimizer.update — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -871,14 +873,14 @@ document.write(`

                  mlx.optimizers.Optimizer.update#

                  -Optimizer.update(model: Module, gradients: dict)#
                  +Optimizer.update(model: Module, gradients: dict)#

                  Apply the gradients to the parameters of the model and update the model with the new parameters.

                  Parameters:

                  • model (Module) – An mlx module to be updated.

                    • -

                  • gradients (dict) – A Python tree of gradients, most likely computed +

                  • gradients (dict) – A Python tree of gradients, most likely computed via mlx.nn.value_and_grad().

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.RMSprop.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.RMSprop.html index 0821f1d14..209afd518 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.RMSprop.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.RMSprop.html @@ -8,7 +8,7 @@ - mlx.optimizers.RMSprop — MLX 0.18.0 documentation + mlx.optimizers.RMSprop — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.optimizers.RMSprop#

                  -class RMSprop(learning_rate: float | Callable[[array], array], alpha: float = 0.99, eps: float = 1e-08)#
                  +class RMSprop(learning_rate: float | Callable[[array], array], alpha: float = 0.99, eps: float = 1e-08)#

                  The RMSprop optimizer [1].

                  [1]: Tieleman, T. and Hinton, G. 2012. Lecture 6.5-rmsprop, coursera: Neural networks for machine learning

                  @@ -881,10 +883,10 @@ w_{t+1} &= w_t - \lambda \frac{g_t}{\sqrt{v_{t+1}} + \epsilon}\end{split}\]<
                  Parameters:
                    -

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • -

                  • alpha (float, optional) – The smoothing constant \(\alpha\). +

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • +

                  • alpha (float, optional) – The smoothing constant \(\alpha\). Default: 0.99

                    • -

                  • eps (float, optional) – The term \(\epsilon\) added to the denominator +

                  • eps (float, optional) – The term \(\epsilon\) added to the denominator to improve numerical stability. Default: 1e-8

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.SGD.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.SGD.html index aa35fcfb6..5fe7b106e 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.SGD.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.SGD.html @@ -8,7 +8,7 @@ - mlx.optimizers.SGD — MLX 0.18.0 documentation + mlx.optimizers.SGD — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home +
                  @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,7 +874,7 @@ document.write(`

                  mlx.optimizers.SGD#

                  -class SGD(learning_rate: float | Callable[[array], array], momentum: float = 0.0, weight_decay: float = 0.0, dampening: float = 0.0, nesterov: bool = False)#
                  +class SGD(learning_rate: float | Callable[[array], array], momentum: float = 0.0, weight_decay: float = 0.0, dampening: float = 0.0, nesterov: bool = False)#

                  The stochastic gradient descent optimizer.

                  Updates a parameter \(w\) with a gradient \(g\) as follows

                  @@ -881,11 +883,11 @@ w_{t+1} &= w_t - \lambda v_{t+1}\end{split}\]
                  Parameters:
                    -

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • -

                  • momentum (float, optional) – The momentum strength \(\mu\). Default: 0

                    • -

                  • weight_decay (float, optional) – The weight decay (L2 penalty). Default: 0

                    • -

                  • dampening (float, optional) – Dampening for momentum \(\tau\). Default: 0

                    • -

                  • nesterov (bool, optional) – Enables Nesterov momentum. Default: False

                    • +

                  • learning_rate (float or callable) – The learning rate \(\lambda\).

                    • +

                  • momentum (float, optional) – The momentum strength \(\mu\). Default: 0

                    • +

                  • weight_decay (float, optional) – The weight decay (L2 penalty). Default: 0

                    • +

                  • dampening (float, optional) – Dampening for momentum \(\tau\). Default: 0

                    • +

                  • nesterov (bool, optional) – Enables Nesterov momentum. Default: False

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.cosine_decay.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.cosine_decay.html index 7c99ee245..377a866e6 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.cosine_decay.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.cosine_decay.html @@ -8,7 +8,7 @@ - mlx.optimizers.cosine_decay — MLX 0.18.0 documentation + mlx.optimizers.cosine_decay — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -871,15 +873,15 @@ document.write(`

                  mlx.optimizers.cosine_decay#

                  -cosine_decay(init: float, decay_steps: int, end: float = 0.0) → Callable#
                  +cosine_decay(init: float, decay_steps: int, end: float = 0.0) → Callable#

                  Make a cosine decay scheduler.

                  Parameters:
                    -

                  • init (float) – Initial value.

                    • -

                  • decay_steps (int) – Number of steps to decay over. The decayed +

                  • init (float) – Initial value.

                    • +

                  • decay_steps (int) – Number of steps to decay over. The decayed value is constant for steps beyond decay_steps.

                    • -

                  • end (float, optional) – Final value to decay to. Default: 0.

                    • +

                  • end (float, optional) – Final value to decay to. Default: 0.

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html index 0f60a32f2..90fbd2b1c 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.exponential_decay.html @@ -8,7 +8,7 @@ - mlx.optimizers.exponential_decay — MLX 0.18.0 documentation + mlx.optimizers.exponential_decay — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -871,13 +873,13 @@ document.write(`

                  mlx.optimizers.exponential_decay#

                  -exponential_decay(init: float, decay_rate: float) → Callable#
                  +exponential_decay(init: float, decay_rate: float) → Callable#

                  Make an exponential decay scheduler.

                  Parameters:
                    -

                  • init (float) – Initial value.

                    • -

                  • decay_rate (float) – Multiplicative factor to decay by.

                    • +

                  • init (float) – Initial value.

                    • +

                  • decay_rate (float) – Multiplicative factor to decay by.

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.join_schedules.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.join_schedules.html index e3d72a567..1708c8562 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.join_schedules.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.join_schedules.html @@ -8,7 +8,7 @@ - mlx.optimizers.join_schedules — MLX 0.18.0 documentation + mlx.optimizers.join_schedules — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -132,8 +132,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -371,6 +371,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -426,6 +427,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -872,15 +874,15 @@ document.write(`

                  mlx.optimizers.join_schedules#

                  -join_schedules(schedules: List[Callable], boundaries: List[int]) → Callable#
                  +join_schedules(schedules: List[Callable], boundaries: List[int]) → Callable#

                  Join multiple schedules to create a new schedule.

                  Parameters:
                    -

                  • schedules (list(Callable)) – A list of schedules. Schedule \(i+1\) +

                  • schedules (list(Callable)) – A list of schedules. Schedule \(i+1\) receives a step count indicating the number of steps since the \(i\)-th boundary.

                    • -

                  • boundaries (list(int)) – A list of integers of length len(schedules) - 1 +

                  • boundaries (list(int)) – A list of integers of length len(schedules) - 1 that indicates when to transition between schedules.

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.linear_schedule.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.linear_schedule.html index 4622b438d..10125ad60 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.linear_schedule.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.linear_schedule.html @@ -8,7 +8,7 @@ - mlx.optimizers.linear_schedule — MLX 0.18.0 documentation + mlx.optimizers.linear_schedule — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -871,14 +873,14 @@ document.write(`

                  mlx.optimizers.linear_schedule#

                  -linear_schedule(init: float, end: float, steps: int) → Callable#
                  +linear_schedule(init: float, end: float, steps: int) → Callable#

                  Make a linear scheduler.

                  Parameters:
                    -

                  • init (float) – Initial value.

                    • -

                  • end (float) – Final value.

                    • -

                  • steps (int) – Number of steps to apply the schedule over. The value is +

                  • init (float) – Initial value.

                    • +

                  • end (float) – Final value.

                    • +

                  • steps (int) – Number of steps to apply the schedule over. The value is end for any steps beyond steps.

                  diff --git a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.step_decay.html b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.step_decay.html index 00d76941c..28c97dae6 100644 --- a/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.step_decay.html +++ b/docs/build/html/python/optimizers/_autosummary/mlx.optimizers.step_decay.html @@ -8,7 +8,7 @@ - mlx.optimizers.step_decay — MLX 0.18.0 documentation + mlx.optimizers.step_decay — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -871,14 +873,14 @@ document.write(`

                  mlx.optimizers.step_decay#

                  -step_decay(init: float, decay_rate: float, step_size: int) → Callable#
                  +step_decay(init: float, decay_rate: float, step_size: int) → Callable#

                  Make a step decay scheduler.

                  Parameters:
                    -

                  • init (float) – Initial value.

                    • -

                  • decay_rate (float) – Multiplicative factor to decay by.

                    • -

                  • step_size (int) – Decay every step_size steps.

                    • +

                  • init (float) – Initial value.

                    • +

                  • decay_rate (float) – Multiplicative factor to decay by.

                    • +

                  • step_size (int) – Decay every step_size steps.

                  diff --git a/docs/build/html/python/optimizers/common_optimizers.html b/docs/build/html/python/optimizers/common_optimizers.html index 8b86e38cc..b2fa6176a 100644 --- a/docs/build/html/python/optimizers/common_optimizers.html +++ b/docs/build/html/python/optimizers/common_optimizers.html @@ -8,7 +8,7 @@ - Common Optimizers — MLX 0.18.0 documentation + Common Optimizers — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
              • Transforms
              • Transforms
              • Transforms
                  @@ -915,6 +917,9 @@ we use a splittable version of Threefry, which is a counter-based PRNG.

                  laplace([shape, dtype, loc, scale, key, stream])

                  Sample numbers from a Laplace distribution.

                  +

                  permutation(x[, axis, key, stream])

                  +

                  Generate a random permutation or permute the entries of an array.

                  + diff --git a/docs/build/html/python/transforms.html b/docs/build/html/python/transforms.html index 8210e43ee..d8b7026c4 100644 --- a/docs/build/html/python/transforms.html +++ b/docs/build/html/python/transforms.html @@ -8,7 +8,7 @@ - Transforms — MLX 0.18.0 documentation + Transforms — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -44,7 +44,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
              • Transforms
              • Transforms
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2, 3, 4, 8, 78, 186, 338, 344, 378, 475, 477, 481, 482], "nan_to_num": 0, "nan": [0, 16, 82, 171, 172, 174, 221], "0f": 0, "posinf": [0, 221], "neginf": [0, 221], "replac": [0, 5, 221, 371, 372, 394, 428], "infin": [0, 173, 175, 176, 221, 350, 351, 455], "finit": [0, 172, 221], "keepdim": [0, 15, 17, 26, 27, 33, 34, 35, 36, 56, 57, 58, 59, 63, 75, 76, 80, 186, 200, 202, 204, 217, 231, 268, 275, 279, 295], "ar": [0, 1, 2, 4, 5, 6, 7, 8, 16, 18, 82, 90, 91, 93, 94, 101, 105, 112, 118, 125, 126, 136, 140, 143, 148, 149, 151, 152, 154, 155, 157, 158, 159, 164, 165, 171, 172, 173, 174, 175, 176, 177, 178, 186, 187, 191, 201, 214, 227, 228, 229, 233, 234, 236, 237, 238, 243, 244, 247, 248, 254, 260, 261, 273, 274, 282, 294, 297, 298, 302, 305, 306, 312, 323, 325, 326, 327, 328, 329, 330, 331, 332, 333, 339, 343, 345, 347, 360, 373, 376, 395, 416, 418, 419, 443, 447, 449, 456, 458, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482], "non": [0, 1, 2, 8, 205, 368, 378, 430, 447], "allclos": [0, 1, 143], "rtol": [0, 16, 171], "1e": [0, 4, 6, 16, 171, 323, 339, 343, 345, 346, 377, 417, 419, 429, 449, 450, 451, 452, 453, 454, 455, 458, 461, 463, 464, 465, 466, 467], "5": [0, 1, 2, 4, 5, 8, 186, 214, 236, 308, 321, 323, 331, 332, 333, 336, 340, 343, 350, 390, 395, 396, 399, 400, 407, 410, 428, 440, 444, 449, 461, 463, 464, 474, 476, 477], "atol": [0, 16, 171], "8": [0, 1, 2, 5, 8, 186, 233, 312, 322, 343, 351, 394, 417, 450, 451, 452, 453, 454, 455, 461, 474, 477, 480, 482], "within": [0, 3, 28, 171], "toler": [0, 16, 171], "isclos": 0, "boolean": [0, 16, 82, 171, 172, 173, 174, 175, 176, 177, 197, 198, 199, 312, 369, 477], "reduc": [0, 1, 8, 15, 17, 26, 27, 122, 200, 202, 204, 217, 231, 275, 279, 295, 308, 323, 394, 424], "output": [0, 1, 2, 5, 8, 15, 16, 17, 18, 28, 83, 90, 91, 94, 96, 97, 108, 109, 110, 111, 112, 130, 140, 142, 143, 144, 145, 146, 153, 156, 157, 158, 162, 163, 165, 168, 169, 171, 186, 190, 200, 202, 204, 205, 217, 221, 225, 226, 229, 231, 232, 236, 237, 238, 240, 241, 242, 244, 247, 248, 260, 261, 268, 273, 275, 279, 283, 289, 291, 294, 295, 296, 297, 298, 299, 300, 301, 321, 322, 323, 325, 326, 327, 328, 329, 330, 343, 347, 350, 351, 373, 376, 392, 394, 395, 397, 398, 399, 400, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 441, 444, 474, 475, 476, 477, 478, 479, 480, 481, 482], "i": [0, 1, 2, 3, 5, 6, 7, 8, 16, 18, 28, 37, 78, 83, 93, 99, 100, 101, 103, 104, 105, 108, 109, 110, 111, 112, 117, 118, 121, 122, 124, 125, 126, 127, 129, 136, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 161, 162, 163, 164, 168, 171, 172, 177, 178, 182, 183, 184, 185, 186, 187, 188, 189, 191, 196, 200, 201, 205, 211, 214, 228, 229, 232, 233, 234, 241, 242, 243, 252, 254, 257, 258, 259, 264, 268, 270, 275, 276, 281, 282, 283, 286, 289, 290, 294, 295, 296, 297, 298, 299, 302, 304, 305, 306, 307, 308, 312, 314, 319, 321, 322, 323, 325, 326, 327, 328, 329, 330, 331, 332, 333, 336, 338, 339, 343, 344, 345, 347, 350, 351, 357, 358, 364, 366, 367, 369, 370, 372, 373, 374, 376, 377, 378, 381, 386, 392, 394, 395, 399, 400, 406, 408, 416, 417, 419, 424, 425, 428, 429, 431, 436, 441, 447, 449, 451, 454, 456, 457, 458, 463, 465, 466, 471, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483], "ani": [0, 1, 2, 5, 7, 18, 94, 305, 306, 307, 308, 309, 319, 336, 353, 354, 357, 366, 376, 394, 395, 444, 466, 473, 474, 476, 478, 480, 481, 482], "sum": [0, 2, 4, 13, 111, 122, 170, 186, 200, 268, 286, 289, 319, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 475, 477, 479], "mean": [0, 1, 4, 5, 6, 144, 240, 241, 242, 294, 319, 323, 339, 358, 377, 402, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 474, 476, 479], "comput": [0, 1, 2, 4, 5, 6, 7, 8, 108, 109, 110, 111, 112, 116, 131, 139, 141, 145, 165, 178, 182, 183, 184, 185, 186, 189, 196, 204, 227, 233, 250, 268, 275, 276, 286, 294, 295, 297, 303, 319, 323, 338, 339, 343, 344, 345, 358, 371, 376, 377, 381, 394, 397, 398, 399, 400, 407, 408, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 449, 450, 451, 453, 454, 455, 456, 460, 474, 475, 476, 480, 482], "var": [0, 323, 339, 343, 345, 419], "ddof": [0, 75, 80, 275, 295], "varianc": [0, 275, 295, 323, 339, 419], "standard": [0, 1, 6, 50, 78, 201, 238, 242, 275, 394, 397, 399, 402, 475, 480], "deviat": [0, 242, 275, 397, 399, 402], "deviatoin": 0, "prod": [0, 1], "The": [0, 1, 2, 3, 5, 6, 7, 8, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 37, 47, 51, 61, 62, 68, 78, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 115, 116, 117, 118, 121, 122, 123, 125, 126, 127, 128, 129, 130, 131, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 178, 179, 180, 181, 184, 186, 187, 188, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 209, 210, 213, 214, 215, 217, 218, 219, 220, 222, 224, 225, 226, 227, 228, 229, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 246, 247, 248, 249, 250, 251, 252, 253, 254, 258, 259, 264, 265, 266, 267, 268, 269, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 312, 314, 321, 322, 323, 325, 326, 327, 328, 329, 330, 331, 332, 333, 335, 337, 338, 339, 343, 344, 345, 347, 350, 351, 353, 354, 358, 360, 364, 365, 366, 367, 370, 371, 372, 373, 375, 376, 377, 378, 381, 383, 386, 392, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 409, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 441, 444, 447, 449, 450, 451, 452, 453, 454, 455, 456, 459, 461, 462, 463, 466, 469, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483], "product": [0, 2, 14, 83, 110, 170, 178, 184, 201, 227, 231, 286, 297, 373, 480], "max": [0, 1, 2, 186, 203, 324, 350, 351, 374, 404, 411, 412, 417, 419, 420, 425, 429, 431, 433, 451, 455, 474, 476, 482], "maximum": [0, 6, 26, 38, 93, 108, 210, 214, 304, 319, 346, 379, 386, 407, 408, 413, 432, 447, 478], "min": [0, 2, 186, 218, 324, 374, 404, 411, 412, 431, 433], "minimum": [0, 27, 38, 93, 109, 386, 416, 417], "argmin": 0, "argmax": [0, 6], "sort": [0, 28, 29, 229, 288], "argsort": 0, "partit": [0, 28], "kth": [0, 28, 229], "smaller": [0, 8, 229, 456, 474], "first": [0, 1, 2, 3, 4, 5, 6, 8, 118, 121, 159, 165, 177, 179, 188, 197, 199, 201, 229, 246, 253, 280, 286, 289, 294, 305, 307, 308, 319, 322, 339, 351, 395, 417, 425, 451, 453, 454, 455, 458, 474, 476, 479, 482], "argpartit": 0, "topk": 0, "logsumexp": 0, "ab": [0, 16, 171, 186, 294, 339, 343, 345, 352, 377, 408, 430, 474], "absolut": [0, 12, 16, 171, 407, 408, 428], "neg": [0, 118, 159, 175, 221, 254, 289, 346, 350, 351, 373, 419, 427, 429, 477], "negat": [0, 222], "sign": [0, 16, 171, 312, 456], "logical_not": 0, "logic": [0, 2, 197, 198, 199], "logical_and": 0, "logical_or": 0, "reciproc": [0, 256], "subtract": [0, 38], "divid": [0, 2, 38, 161, 233, 250, 475], "divmod": 0, "quotient": [0, 128, 129, 161], "remaind": [0, 129], "floor_divid": 0, "integ": [0, 11, 161, 163, 164, 177, 186, 207, 228, 233, 234, 236, 243, 244, 270, 282, 286, 298, 312, 335, 365, 465, 477], "divis": [0, 128, 161, 233, 250], "equival": [0, 2, 31, 65, 79, 126, 129, 161, 164, 168, 282, 324, 334, 336, 340, 341, 342, 348, 349, 372, 374, 376, 379, 380, 382, 384, 387, 388, 389, 390, 391, 393], "do": [0, 2, 5, 8, 296, 319, 359, 370, 444, 447, 454, 474, 475, 476, 478], "floor": [0, 1, 161], "between": [0, 2, 7, 93, 159, 394, 417, 420, 421, 424, 465, 475, 478, 479, 482], "ceil": 0, "exp": [0, 1, 139, 143, 196, 200, 238, 268, 324, 334, 385, 404, 405, 422, 434, 435, 439, 474, 482], "exponenti": [0, 137, 139, 324, 334, 382, 404, 405, 434, 464], "sin": [0, 112, 386, 476, 480], "sine": [0, 21, 22, 266, 267, 476], "co": [0, 2, 112, 386, 476], "cosin": [0, 19, 20, 106, 107, 417, 463, 465, 476], "tan": 0, "tangent": [0, 2, 23, 24, 25, 112, 178, 284, 285, 393, 442], "arcsin": 0, "arc": 0, "arcco": 0, "arctan": 0, "arctan2": 0, "invers": [0, 19, 20, 21, 22, 23, 24, 25, 135, 150, 151, 152, 153, 154, 155, 183, 185, 189], "ratio": [0, 24], "sinh": 0, "hyperbol": [0, 20, 22, 25, 107, 267, 285, 393, 442], "cosh": [0, 424], "tanh": [0, 319, 336, 338, 344, 352, 378, 407, 430], "arcsinh": 0, "arccosh": 0, "arctanh": 0, "degre": [0, 235, 429], "radian": [0, 115], "log": [0, 194, 196, 200, 348, 349, 414, 415, 416, 419, 422, 424, 427, 439], "natur": [0, 192, 194, 478], "logarithm": [0, 192, 193, 194, 195], "log2": 0, "base": [0, 2, 145, 186, 193, 195, 230, 381, 394, 447, 449, 455, 469, 471, 474, 477], "2": [0, 1, 2, 4, 5, 6, 38, 99, 103, 117, 118, 134, 148, 151, 153, 154, 155, 156, 157, 158, 159, 168, 177, 182, 183, 184, 185, 186, 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319, 377, 395, 449, 479, 481], "assign": [0, 2, 38, 447], "henc": [0, 2, 233, 474], "If": [0, 1, 2, 5, 8, 15, 16, 17, 18, 26, 27, 28, 29, 78, 82, 83, 93, 95, 105, 108, 109, 110, 111, 117, 118, 121, 122, 123, 125, 126, 127, 136, 142, 145, 156, 157, 158, 161, 162, 165, 171, 182, 183, 184, 186, 191, 200, 201, 202, 204, 205, 213, 214, 217, 221, 225, 228, 229, 231, 232, 237, 241, 243, 251, 254, 268, 269, 270, 275, 279, 281, 282, 283, 286, 288, 289, 294, 295, 298, 300, 302, 306, 308, 323, 325, 326, 327, 328, 329, 330, 339, 345, 347, 358, 360, 370, 376, 378, 381, 383, 386, 395, 416, 418, 429, 451, 474, 475, 476, 478, 481, 482, 483], "provid": [0, 2, 5, 83, 116, 141, 165, 243, 254, 286, 294, 306, 308, 314, 319, 353, 358, 360, 370, 371, 372, 375, 376, 394, 395, 443, 447, 475, 481, 483], "rank": [0, 125, 126, 127, 425, 475], "must": [0, 1, 2, 3, 8, 90, 93, 145, 162, 164, 186, 236, 237, 241, 244, 247, 248, 299, 395, 479], "In": [0, 1, 2, 5, 6, 38, 201, 233, 306, 319, 332, 339, 447, 450, 452, 453, 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[[0, "_CPPv44sortRK5array14StreamOrDevice"], [0, "_CPPv44sortRK5arrayi14StreamOrDevice"]], "split (c++ function)": [[0, "_CPPv45splitRK5arrayRKNSt6vectorIiEE14StreamOrDevice"], [0, "_CPPv45splitRK5arrayRKNSt6vectorIiEEi14StreamOrDevice"], [0, "_CPPv45splitRK5arrayi14StreamOrDevice"], [0, "_CPPv45splitRK5arrayii14StreamOrDevice"]], "sqrt (c++ function)": [[0, "_CPPv44sqrtRK5array14StreamOrDevice"]], "square (c++ function)": [[0, "_CPPv46squareRK5array14StreamOrDevice"]], "squeeze (c++ function)": [[0, "_CPPv47squeezeRK5array14StreamOrDevice"], [0, "_CPPv47squeezeRK5arrayRKNSt6vectorIiEE14StreamOrDevice"], [0, "_CPPv47squeezeRK5arrayi14StreamOrDevice"]], "stack (c++ function)": [[0, "_CPPv45stackRKNSt6vectorI5arrayEE14StreamOrDevice"], [0, "_CPPv45stackRKNSt6vectorI5arrayEEi14StreamOrDevice"]], "std (c++ function)": [[0, "_CPPv4StRK5array14StreamOrDevice"], [0, "_CPPv4StRK5arrayRKNSt6vectorIiEEbi14StreamOrDevice"], [0, "_CPPv4StRK5arraybi14StreamOrDevice"], [0, "_CPPv4StRK5arrayibi14StreamOrDevice"]], "stop_gradient (c++ function)": [[0, "_CPPv413stop_gradientRK5array14StreamOrDevice"]], "subtract (c++ function)": [[0, "_CPPv48subtractRK5arrayRK5array14StreamOrDevice"]], "sum (c++ function)": [[0, "_CPPv43sumRK5array14StreamOrDevice"], [0, "_CPPv43sumRK5arrayRKNSt6vectorIiEEb14StreamOrDevice"], [0, "_CPPv43sumRK5arrayb14StreamOrDevice"], [0, "_CPPv43sumRK5arrayib14StreamOrDevice"]], "swapaxes (c++ function)": [[0, "_CPPv48swapaxesRK5arrayii14StreamOrDevice"]], "take (c++ function)": [[0, "_CPPv44takeRK5arrayRK5array14StreamOrDevice"], [0, "_CPPv44takeRK5arrayRK5arrayi14StreamOrDevice"], [0, "_CPPv44takeRK5arrayi14StreamOrDevice"], [0, "_CPPv44takeRK5arrayii14StreamOrDevice"]], "take_along_axis (c++ function)": [[0, "_CPPv415take_along_axisRK5arrayRK5arrayi14StreamOrDevice"]], "tan (c++ function)": [[0, "_CPPv43tanRK5array14StreamOrDevice"]], "tanh (c++ function)": [[0, "_CPPv44tanhRK5array14StreamOrDevice"]], "tensordot (c++ function)": [[0, 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mlx.core)": [[12, "mlx.core.abs"]], "add() (in module mlx.core)": [[13, "mlx.core.add"]], "addmm() (in module mlx.core)": [[14, "mlx.core.addmm"]], "all() (in module mlx.core)": [[15, "mlx.core.all"]], "allclose() (in module mlx.core)": [[16, "mlx.core.allclose"]], "any() (in module mlx.core)": [[17, "mlx.core.any"]], "arange() (in module mlx.core)": [[18, "mlx.core.arange"]], "arccos() (in module mlx.core)": [[19, "mlx.core.arccos"]], "arccosh() (in module mlx.core)": [[20, "mlx.core.arccosh"]], "arcsin() (in module mlx.core)": [[21, "mlx.core.arcsin"]], "arcsinh() (in module mlx.core)": [[22, "mlx.core.arcsinh"]], "arctan() (in module mlx.core)": [[23, "mlx.core.arctan"]], "arctan2() (in module mlx.core)": [[24, "mlx.core.arctan2"]], "arctanh() (in module mlx.core)": [[25, "mlx.core.arctanh"]], "argmax() (in module mlx.core)": [[26, "mlx.core.argmax"]], "argmin() (in module mlx.core)": [[27, "mlx.core.argmin"]], "argpartition() (in module mlx.core)": [[28, "mlx.core.argpartition"]], "argsort() (in module mlx.core)": [[29, "mlx.core.argsort"]], "__init__() (array method)": [[30, "mlx.core.array.__init__"]], "array (class in mlx.core)": [[30, "mlx.core.array"]], "t (array property)": [[31, "mlx.core.array.T"]], "abs() (array method)": [[32, "mlx.core.array.abs"]], "all() (array method)": [[33, "mlx.core.array.all"]], "any() (array method)": [[34, "mlx.core.array.any"]], "argmax() (array method)": [[35, "mlx.core.array.argmax"]], "argmin() (array method)": [[36, "mlx.core.array.argmin"]], "astype() (array method)": [[37, "mlx.core.array.astype"]], "at (array property)": [[38, "mlx.core.array.at"]], "conj() (array method)": [[39, "mlx.core.array.conj"]], "cos() (array method)": [[40, "mlx.core.array.cos"]], "cummax() (array method)": [[41, "mlx.core.array.cummax"]], "cummin() (array method)": [[42, "mlx.core.array.cummin"]], "cumprod() (array method)": [[43, "mlx.core.array.cumprod"]], "cumsum() (array method)": [[44, "mlx.core.array.cumsum"]], "diag() (array 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mlx.core.distributed)": [[121, "mlx.core.distributed.all_gather"]], "all_sum() (in module mlx.core.distributed)": [[122, "mlx.core.distributed.all_sum"]], "init() (in module mlx.core.distributed)": [[123, "mlx.core.distributed.init"]], "is_available() (in module mlx.core.distributed)": [[124, "mlx.core.distributed.is_available"]], "recv() (in module mlx.core.distributed)": [[125, "mlx.core.distributed.recv"]], "recv_like() (in module mlx.core.distributed)": [[126, "mlx.core.distributed.recv_like"]], "send() (in module mlx.core.distributed)": [[127, "mlx.core.distributed.send"]], "divide() (in module mlx.core)": [[128, "mlx.core.divide"]], "divmod() (in module mlx.core)": [[129, "mlx.core.divmod"]], "einsum() (in module mlx.core)": [[130, "mlx.core.einsum"]], "einsum_path() (in module mlx.core)": [[131, "mlx.core.einsum_path"]], "enable_compile() (in module mlx.core)": [[132, "mlx.core.enable_compile"]], "equal() (in module mlx.core)": [[133, "mlx.core.equal"]], "erf() (in module mlx.core)": [[134, "mlx.core.erf"]], "erfinv() (in module mlx.core)": [[135, "mlx.core.erfinv"]], "eval() (in module mlx.core)": [[136, "mlx.core.eval"]], "exp() (in module mlx.core)": [[137, "mlx.core.exp"]], "expand_dims() (in module mlx.core)": [[138, "mlx.core.expand_dims"]], "expm1() (in module mlx.core)": [[139, "mlx.core.expm1"]], "eye() (in module mlx.core)": [[140, "mlx.core.eye"]], "affine_quantize() (in module mlx.core.fast)": [[141, "mlx.core.fast.affine_quantize"]], "layer_norm() (in module mlx.core.fast)": [[142, "mlx.core.fast.layer_norm"]], "metal_kernel() (in module mlx.core.fast)": [[143, "mlx.core.fast.metal_kernel"]], "rms_norm() (in module mlx.core.fast)": [[144, "mlx.core.fast.rms_norm"]], "rope() (in module mlx.core.fast)": [[145, "mlx.core.fast.rope"]], "scaled_dot_product_attention() (in module mlx.core.fast)": [[146, "mlx.core.fast.scaled_dot_product_attention"]], "fft() (in module mlx.core.fft)": [[147, "mlx.core.fft.fft"]], "fft2() (in module mlx.core.fft)": 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--git a/docs/build/html/structmlx_1_1core_1_1_contiguous_iterator-members.html b/docs/build/html/structmlx_1_1core_1_1_contiguous_iterator-members.html deleted file mode 100644 index 0b2a5134f..000000000 --- a/docs/build/html/structmlx_1_1core_1_1_contiguous_iterator-members.html +++ /dev/null @@ -1,93 +0,0 @@ - - - - - - - -MLX: Member List - - - - - - - - - - - -
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                  mlx::core::ContiguousIterator< StrideT > Member List
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                  This is the complete list of members for mlx::core::ContiguousIterator< StrideT >, including all inherited members.

                  - - - - -
                  ContiguousIterator(const std::vector< int > &shape, const std::vector< StrideT > &strides, int dims)mlx::core::ContiguousIterator< StrideT >inlineexplicit
                  locmlx::core::ContiguousIterator< StrideT >
                  step()mlx::core::ContiguousIterator< StrideT >inline
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                  mlx::core::ContiguousIterator< StrideT > Struct Template Reference
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                  #include <utils.h>

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                  -Public Member Functions

                  void step ()
                   
                   ContiguousIterator (const std::vector< int > &shape, const std::vector< StrideT > &strides, int dims)
                   
                  - - - -

                  -Public Attributes

                  StrideT loc {0}
                   
                  -

                  Constructor & Destructor Documentation

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                  ◆ ContiguousIterator()

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                  -template<typename StrideT >
                  - - - - - -
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                  mlx::core::ContiguousIterator< StrideT >::ContiguousIterator (const std::vector< int > & shape,
                  const std::vector< StrideT > & strides,
                  int dims )
                  -                   		-inlineexplicit
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                  ◆ loc

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                  StrideT mlx::core::ContiguousIterator< StrideT >::loc {0}
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                  - - diff --git a/docs/build/html/usage/compile.html b/docs/build/html/usage/compile.html index 020f25cb7..9b9dd771d 100644 --- a/docs/build/html/usage/compile.html +++ b/docs/build/html/usage/compile.html @@ -8,7 +8,7 @@ - Compilation — MLX 0.18.0 documentation + Compilation — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
              • Transforms
              • Transforms
              • Transforms
                  @@ -873,7 +875,7 @@ document.write(`

                  For the most part, indexing an MLX array works the same as indexing a NumPy numpy.ndarray. See the NumPy documentation for more details on how that works.

                  -

                  For example, you can use regular integers and slices (slice) to index arrays:

                  +

                  For example, you can use regular integers and slices (slice) to index arrays:

                  >>> arr = mx.arange(10)
 >>> arr[3]
 array(3, dtype=int32)
@@ -883,7 +885,7 @@ array(8, ([2, 4, 6], dtype=int32)
                  -

                  For multi-dimensional arrays, the ... or Ellipsis syntax works as in NumPy:

                  +

                  For multi-dimensional arrays, the ... or Ellipsis syntax works as in NumPy:

                  >>> arr = mx.arange(8).reshape(2, 2, 2)
 >>> arr[:, :, 0]
 array(3, dtype=int32)
@@ -909,7 +911,7 @@ array([[0, 
 array([5, 7], dtype=int32)
                  -

                  Mixing and matching integers, slice, ..., and array indices +

                  Mixing and matching integers, slice, ..., and array indices works just as in NumPy.

                  Other functions which may be useful for indexing arrays are take() and take_along_axis().

                  diff --git a/docs/build/html/usage/lazy_evaluation.html b/docs/build/html/usage/lazy_evaluation.html index 8e10d4981..725552850 100644 --- a/docs/build/html/usage/lazy_evaluation.html +++ b/docs/build/html/usage/lazy_evaluation.html @@ -8,7 +8,7 @@ - Lazy Evaluation — MLX 0.18.0 documentation + Lazy Evaluation — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@
                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -958,7 +960,7 @@ stochastic gradient descent). A natural and usually efficient place to use

                  An important behavior to be aware of is when the graph will be implicitly evaluated. Anytime you print an array, convert it to an -numpy.ndarray, or otherwise access it’s memory via memoryview, +numpy.ndarray, or otherwise access it’s memory via memoryview, the graph will be evaluated. Saving arrays via save() (or any other MLX saving functions) will also evaluate the array.

                  Calling array.item() on a scalar array will also evaluate it. In the diff --git a/docs/build/html/usage/numpy.html b/docs/build/html/usage/numpy.html index 889a18ad8..156381858 100644 --- a/docs/build/html/usage/numpy.html +++ b/docs/build/html/usage/numpy.html @@ -8,7 +8,7 @@ - Conversion to NumPy and Other Frameworks — MLX 0.18.0 documentation + Conversion to NumPy and Other Frameworks — MLX 0.18.1 documentation @@ -36,7 +36,7 @@ - + @@ -131,8 +131,8 @@ - MLX 0.18.0 documentation - Home - + MLX 0.18.1 documentation - Home + @@ -370,6 +370,7 @@

                • mlx.core.repeat
                • mlx.core.reshape
                • mlx.core.right_shift
                  • +
                • mlx.core.roll
                • mlx.core.round
                • mlx.core.rsqrt
                • mlx.core.save
                  • @@ -425,6 +426,7 @@
                • mlx.core.random.truncated_normal
                • mlx.core.random.uniform
                • mlx.core.random.laplace
                  • +
                • mlx.core.random.permutation
              • Transforms
                  @@ -925,10 +927,10 @@ even though no in-place operations on MLX memory are executed.

                  PyTorch#

                  Warning

                  -

                  PyTorch Support for memoryview is experimental and can break for +

                  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
 
@@ -953,7 +955,7 @@ 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 60c37651f..7e427ee26 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 0.18.0 documentation
+    Quick Start Guide — MLX 0.18.1 documentation
   
   
   
@@ -36,7 +36,7 @@
 
   
 
-    
+    
     
     
     
@@ -131,8 +131,8 @@
       
     
     
-    MLX 0.18.0 documentation - Home
-    
+    MLX 0.18.1 documentation - Home
+    
   
   
 
                  
@@ -370,6 +370,7 @@
 
                • mlx.core.repeat
                  • 
 
                • mlx.core.reshape
                  • 
 
                • mlx.core.right_shift
                  • 
+
                • mlx.core.roll
                  • 
 
                • mlx.core.round
                  • 
 
                • mlx.core.rsqrt
                  • 
 
                • mlx.core.save
                  • 
@@ -425,6 +426,7 @@
 
                • mlx.core.random.truncated_normal
                  • 
 
                • mlx.core.random.uniform
                  • 
 
                • mlx.core.random.laplace
                  • 
+
                • mlx.core.random.permutation
                  •
              • Transforms
              • Transforms
              • Transforms
              • Transforms