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89 lines
2.8 KiB
C++
89 lines
2.8 KiB
C++
// Copyright © 2023-2024 Apple Inc.
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#include <algorithm>
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#include "mlx/backend/gpu/copy.h"
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#include "mlx/backend/metal/device.h"
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#include "mlx/backend/metal/kernels.h"
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#include "mlx/backend/metal/kernels/defines.h"
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#include "mlx/backend/metal/utils.h"
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#include "mlx/primitives.h"
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namespace mlx::core {
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constexpr int SOFTMAX_LOOPED_LIMIT = 4096;
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void Softmax::eval_gpu(const std::vector<array>& inputs, array& out) {
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assert(inputs.size() == 1);
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if (!issubdtype(out.dtype(), floating)) {
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throw std::runtime_error(
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"[softmax] Does not support non-floating point types.");
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}
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auto& s = stream();
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auto& d = metal::device(s.device);
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// Make sure that the last dimension is contiguous
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auto set_output = [&s, &out](const array& x) {
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if (x.flags().contiguous && x.strides()[x.ndim() - 1] == 1) {
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if (x.is_donatable()) {
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out.copy_shared_buffer(x);
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} else {
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out.set_data(
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allocator::malloc(x.data_size() * x.itemsize()),
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x.data_size(),
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x.strides(),
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x.flags());
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}
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return x;
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} else {
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auto x_copy = array(x.shape(), x.dtype(), nullptr, {});
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copy_gpu(x, x_copy, CopyType::General, s);
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out.copy_shared_buffer(x_copy);
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return x_copy;
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}
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};
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const array in = set_output(inputs[0]);
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int axis_size = in.shape().back();
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int n_rows = in.data_size() / axis_size;
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const int simd_size = 32;
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const int n_reads = SOFTMAX_N_READS;
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const int looped_limit = SOFTMAX_LOOPED_LIMIT;
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std::string kernel_name = (axis_size > looped_limit) ? "looped_" : "block_";
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kernel_name += "softmax_";
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if (in.dtype() != float32 && precise_) {
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kernel_name += "precise_";
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}
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kernel_name += type_to_name(out);
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auto kernel = get_softmax_kernel(d, kernel_name, precise_, out);
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auto& compute_encoder = d.get_command_encoder(s.index);
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{
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MTL::Size grid_dims, group_dims;
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if (axis_size <= looped_limit) {
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size_t threadgroup_needed = (axis_size + n_reads - 1) / n_reads;
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size_t simds_needed = (threadgroup_needed + simd_size - 1) / simd_size;
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size_t threadgroup_size = simd_size * simds_needed;
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assert(threadgroup_size <= kernel->maxTotalThreadsPerThreadgroup());
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size_t n_threads = n_rows * threadgroup_size;
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grid_dims = MTL::Size(n_threads, 1, 1);
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group_dims = MTL::Size(threadgroup_size, 1, 1);
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} else {
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size_t threadgroup_size = kernel->maxTotalThreadsPerThreadgroup();
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size_t n_threads = n_rows * threadgroup_size;
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grid_dims = MTL::Size(n_threads, 1, 1);
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group_dims = MTL::Size(threadgroup_size, 1, 1);
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}
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compute_encoder.set_compute_pipeline_state(kernel);
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compute_encoder.set_input_array(in, 0);
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compute_encoder.set_output_array(out, 1);
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compute_encoder.set_bytes(axis_size, 2);
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compute_encoder.dispatch_threads(grid_dims, group_dims);
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}
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}
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} // namespace mlx::core
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