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This commit is contained in:
Josh Soref
@@ -26,7 +26,7 @@ namespace mlx::core {
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///////////////////////////////////////////////////////////////////////////////
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/**
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* Scale and sum two vectors elementwise
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* Scale and sum two vectors element-wise
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* z = alpha * x + beta * y
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*
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* Follow numpy style broadcasting between x and y
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@@ -91,21 +91,21 @@ void axpby_impl(
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T alpha = static_cast<T>(alpha_);
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T beta = static_cast<T>(beta_);
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// Do the elementwise operation for each output
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// Do the element-wise operation for each output
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for (size_t out_idx = 0; out_idx < out.size(); out_idx++) {
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// Map linear indices to offsets in x and y
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auto x_offset = elem_to_loc(out_idx, x.shape(), x.strides());
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auto y_offset = elem_to_loc(out_idx, y.shape(), y.strides());
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// We allocate the output to be contiguous and regularly strided
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// (defaults to row major) and hence it doesn't need additonal mapping
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// (defaults to row major) and hence it doesn't need additional mapping
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out_ptr[out_idx] = alpha * x_ptr[x_offset] + beta * y_ptr[y_offset];
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}
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}
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/** Fall back implementation for evaluation on CPU */
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void Axpby::eval(const std::vector<array>& inputs, array& out) {
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// Check the inputs (registered in the op while contructing the out array)
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// Check the inputs (registered in the op while constructing the out array)
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assert(inputs.size() == 2);
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auto& x = inputs[0];
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auto& y = inputs[1];
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@@ -192,7 +192,7 @@ void Axpby::eval_cpu(const std::vector<array>& inputs, array& out) {
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eval(inputs, out);
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}
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#else // Accelerate not avaliable
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#else // Accelerate not available
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/** Evaluate primitive on CPU falling back to common backend */
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void Axpby::eval_cpu(const std::vector<array>& inputs, array& out) {
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@@ -254,7 +254,7 @@ void Axpby::eval_gpu(const std::vector<array>& inputs, array& out) {
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compute_encoder->setComputePipelineState(kernel);
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// Kernel parameters are registered with buffer indices corresponding to
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// those in the kernel decelaration at axpby.metal
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// those in the kernel declaration at axpby.metal
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int ndim = out.ndim();
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size_t nelem = out.size();
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@@ -287,7 +287,7 @@ void Axpby::eval_gpu(const std::vector<array>& inputs, array& out) {
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// Fix the 3D size of the launch grid (in terms of threads)
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MTL::Size grid_dims = MTL::Size(nelem, 1, 1);
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// Launch the grid with the given number of threads divded among
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// Launch the grid with the given number of threads divided among
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// the given threadgroups
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compute_encoder->dispatchThreads(grid_dims, group_dims);
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}
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@@ -311,8 +311,8 @@ array Axpby::jvp(
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const std::vector<array>& tangents,
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const std::vector<int>& argnums) {
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// Forward mode diff that pushes along the tangents
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// The jvp transform on the the primitive can built with ops
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// that are scheduled on the same stream as the primtive
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// The jvp transform on the primitive can built with ops
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// that are scheduled on the same stream as the primitive
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// If argnums = {0}, we only push along x in which case the
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// jvp is just the tangent scaled by alpha
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@@ -345,7 +345,7 @@ std::vector<array> Axpby::vjp(
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return vjps;
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}
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/** Vectorize primitve along given axis */
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/** Vectorize primitive along given axis */
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std::pair<array, int> Axpby::vmap(
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const std::vector<array>& inputs,
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const std::vector<int>& axes) {
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