mlx/mlx/backend/metal/indexing.cpp

294 lines
8.8 KiB
C++

// Copyright © 2023-2024 Apple Inc.
#include <algorithm>
#include <cassert>
#include <numeric>
#include <sstream>
#include "mlx/backend/common/binary.h"
#include "mlx/backend/metal/copy.h"
#include "mlx/backend/metal/device.h"
#include "mlx/backend/metal/kernels/defines.h"
#include "mlx/backend/metal/utils.h"
#include "mlx/primitives.h"
#include "mlx/utils.h"
namespace mlx::core {
namespace {
constexpr int METAL_MAX_INDEX_ARRAYS = 10;
} // namespace
void Gather::eval_gpu(const std::vector<array>& inputs, array& out) {
auto& src = inputs[0];
int nidx = inputs.size() - 1;
if (nidx > METAL_MAX_INDEX_ARRAYS) {
std::ostringstream msg;
msg << "[Gather::eval_gpu] Gathering with more than "
<< METAL_MAX_INDEX_ARRAYS << " index arrays not yet supported.";
throw std::runtime_error(msg.str());
}
out.set_data(allocator::malloc_or_wait(out.nbytes()));
if (out.size() == 0) {
return;
}
auto& s = stream();
auto& d = metal::device(s.device);
int idx_ndim = nidx ? inputs[1].ndim() : 0;
size_t ndim = src.ndim();
std::ostringstream kname;
std::string idx_type_name = nidx ? type_to_name(inputs[1]) : "";
kname << "gather" << type_to_name(src) << idx_type_name << "_" << nidx;
if (idx_ndim <= 1) {
kname << "_" << idx_ndim;
}
auto& compute_encoder = d.get_command_encoder(s.index);
auto kernel = d.get_kernel(kname.str());
compute_encoder->setComputePipelineState(kernel);
size_t slice_size = 1;
for (auto s : slice_sizes_) {
slice_size *= s;
}
// Launch 2D grid of threads: indices x slice
size_t dim0 = out.size() / slice_size;
size_t dim1 = slice_size;
auto group_dims = get_block_dims(dim0, dim1, 1);
MTL::Size grid_dims = MTL::Size(dim0, dim1, 1);
// Collect all idx shapes and strides into one place
std::vector<int> idx_shapes;
std::vector<size_t> idx_strides;
for (int i = 0; i < nidx; ++i) {
idx_shapes.insert(
idx_shapes.end(),
inputs[i + 1].shape().begin(),
inputs[i + 1].shape().end());
idx_strides.insert(
idx_strides.end(),
inputs[i + 1].strides().begin(),
inputs[i + 1].strides().end());
}
// Set all the buffers
compute_encoder.set_input_array(src, 0);
compute_encoder.set_output_array(out, 1);
// Set source info
compute_encoder->setBytes(src.shape().data(), ndim * sizeof(int), 2);
compute_encoder->setBytes(src.strides().data(), ndim * sizeof(size_t), 3);
compute_encoder->setBytes(&ndim, sizeof(size_t), 4);
compute_encoder->setBytes(slice_sizes_.data(), ndim * sizeof(int), 5);
compute_encoder->setBytes(axes_.data(), nidx * sizeof(int), 6);
// Set index info
//
// We don't need to check for empty idx_shapes because gather has a
// idx_ndim == 0 specialization
compute_encoder->setBytes(
idx_shapes.data(), idx_shapes.size() * sizeof(int), 7);
compute_encoder->setBytes(
idx_strides.data(), idx_strides.size() * sizeof(size_t), 8);
compute_encoder->setBytes(&idx_ndim, sizeof(int), 9);
// Set index buffers
for (int i = 1; i < nidx + 1; ++i) {
compute_encoder.set_input_array(inputs[i], 20 + i);
}
// Launch grid
compute_encoder->dispatchThreads(grid_dims, group_dims);
}
void Scatter::eval_gpu(const std::vector<array>& inputs, array& out) {
if (size_of(out.dtype()) == 8) {
std::ostringstream msg;
msg << "[Scatter::eval_gpu] Does not support " << out.dtype();
throw std::invalid_argument(msg.str());
}
int nidx = axes_.size();
if (nidx > METAL_MAX_INDEX_ARRAYS) {
std::ostringstream msg;
msg << "[Scatter::eval_gpu] Gathering with more than "
<< METAL_MAX_INDEX_ARRAYS << " index arrays not yet supported.";
throw std::runtime_error(msg.str());
}
// Copy src into out
auto copy_type =
inputs[0].data_size() == 1 ? CopyType::Scalar : CopyType::General;
copy_gpu(inputs[0], out, copy_type);
// Empty update
if (inputs.back().size() == 0) {
return;
}
// Get stream
auto& s = stream();
auto& d = metal::device(s.device);
// Get kernel name
std::ostringstream kname;
std::string idx_type_name = nidx ? type_to_name(inputs[1]) : "";
int idx_ndim = nidx ? inputs[1].ndim() : 0;
bool index_nd1_specialization = (idx_ndim == 1);
// Bail from fast path (1d index specialization) if scatter dims aren't
// the outermost dims and contiguous since update access won't be raster
// order.
for (auto i = 0; i < axes_.size() && index_nd1_specialization; i++) {
index_nd1_specialization &= (axes_[i] == i);
}
// Bail from fast path (1d index specialization) if any of the dims are
// broadcasted, since we can't rely on linear indexing in that case.
for (int i = 1; i < inputs.size() && index_nd1_specialization; i++) {
index_nd1_specialization &= inputs[i].flags().row_contiguous;
}
if (index_nd1_specialization) {
kname << "scatter_1d_index" << type_to_name(out) << idx_type_name;
} else {
kname << "scatter" << type_to_name(out) << idx_type_name;
}
switch (reduce_type_) {
case Scatter::None:
kname << "_none";
break;
case Scatter::Sum:
kname << "_sum";
break;
case Scatter::Prod:
kname << "_prod";
break;
case Scatter::Max:
kname << "_max";
break;
case Scatter::Min:
kname << "_min";
break;
}
kname << "_" << nidx;
auto& compute_encoder = d.get_command_encoder(s.index);
auto kernel = d.get_kernel(kname.str());
auto& upd = inputs.back();
size_t nthreads = upd.size();
compute_encoder->setComputePipelineState(kernel);
// Set all the buffers
compute_encoder.set_input_array(upd, 1);
compute_encoder.set_output_array(out, 2);
// Set update info
uint upd_ndim = upd.ndim();
size_t upd_size = 1;
for (int i = idx_ndim; i < upd.ndim(); ++i) {
upd_size *= upd.shape(i);
}
if (index_nd1_specialization) {
compute_encoder->setBytes(
out.shape().data(), out.shape().size() * sizeof(int), 3);
compute_encoder->setBytes(
out.strides().data(), out.strides().size() * sizeof(size_t), 4);
compute_encoder->setBytes(&upd_size, sizeof(size_t), 5);
// Set index buffers
for (int i = 1; i < nidx + 1; ++i) {
compute_encoder.set_input_array(inputs[i], 20 + i);
}
// Launch grid
MTL::Size grid_dims = MTL::Size(upd_size, nthreads / upd_size, 1);
MTL::Size group_dims = get_block_dims(upd_size, nthreads / upd_size, 1);
compute_encoder->dispatchThreads(grid_dims, group_dims);
} else {
// Collect all idx shapes and strides into one place
std::vector<int> idx_shapes;
std::vector<size_t> idx_strides;
for (int i = 0; i < nidx; ++i) {
idx_shapes.insert(
idx_shapes.end(),
inputs[i + 1].shape().begin(),
inputs[i + 1].shape().end());
idx_strides.insert(
idx_strides.end(),
inputs[i + 1].strides().begin(),
inputs[i + 1].strides().end());
}
if (upd_ndim == 0) {
// Need placeholders so Metal doesn't compalain
int shape_ = 0;
size_t stride_ = 0;
compute_encoder->setBytes(&shape_, sizeof(int), 3);
compute_encoder->setBytes(&stride_, sizeof(size_t), 4);
} else {
compute_encoder->setBytes(upd.shape().data(), upd_ndim * sizeof(int), 3);
compute_encoder->setBytes(
upd.strides().data(), upd_ndim * sizeof(size_t), 4);
}
compute_encoder->setBytes(&upd_ndim, sizeof(size_t), 5);
compute_encoder->setBytes(&upd_size, sizeof(size_t), 6);
// Set output info
size_t out_ndim = out.ndim();
if (out_ndim == 0) {
// Need placeholders so Metal doesn't compalain
int shape_ = 0;
size_t stride_ = 0;
compute_encoder->setBytes(&shape_, sizeof(int), 7);
compute_encoder->setBytes(&stride_, sizeof(size_t), 8);
} else {
compute_encoder->setBytes(out.shape().data(), out_ndim * sizeof(int), 7);
compute_encoder->setBytes(
out.strides().data(), out_ndim * sizeof(size_t), 8);
}
compute_encoder->setBytes(&out_ndim, sizeof(size_t), 9);
compute_encoder->setBytes(axes_.data(), axes_.size() * sizeof(int), 10);
// Set index info
if (idx_ndim == 0) {
// Add a 0 in idx_shapes and strides to avoid the missing buffer binding
// error in the metal API.
idx_shapes.push_back(0);
idx_strides.push_back(0);
}
compute_encoder->setBytes(
idx_shapes.data(), idx_shapes.size() * sizeof(int), 11);
compute_encoder->setBytes(
idx_strides.data(), idx_strides.size() * sizeof(size_t), 12);
compute_encoder->setBytes(&idx_ndim, sizeof(int), 13);
// Set index buffers
for (int i = 1; i < nidx + 1; ++i) {
compute_encoder.set_input_array(inputs[i], 20 + i);
}
// Launch grid
MTL::Size grid_dims = MTL::Size(upd_size, nthreads / upd_size, 1);
MTL::Size group_dims = get_block_dims(upd_size, nthreads / upd_size, 1);
compute_encoder->dispatchThreads(grid_dims, group_dims);
}
}
} // namespace mlx::core