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fix adding inputs arrays in matmul / srot

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This commit is contained in:
Awni Hannun 2025-06-20 12:56:40 -07:00
parent 72e21b7d51
commit 1a0e884036
3 changed files with 24 additions and 6 deletions
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1
mlx/backend/cuda/allocator.cpp
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@ -1,6 +1,5 @@
// Copyright © 2025 Apple Inc. // Copyright © 2025 Apple Inc.
#include "mlx/utils.h"
#include "mlx/backend/cuda/allocator.h" #include "mlx/backend/cuda/allocator.h"
#include "mlx/backend/cuda/utils.h" #include "mlx/backend/cuda/utils.h"
#include "mlx/backend/cuda/worker.h" #include "mlx/backend/cuda/worker.h"

24
mlx/backend/cuda/matmul.cpp
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@ -362,9 +362,18 @@ void Matmul::eval_gpu(const std::vector<array>& inputs, array& out) {
a_batch_strides.back(), a_batch_strides.back(),
b_batch_strides.back()); b_batch_strides.back());
encoder.set_input_array(a);
encoder.set_input_array(b);
encoder.set_output_array(out);
auto nbatch = batch_count / batch_shape.back();
if (nbatch == 1) {
matmul.run(encoder, out.data<int8_t>(), a.data<int8_t>(), b.data<int8_t>());
return;
}
ContiguousIterator a_it(batch_shape, a_batch_strides, batch_shape.size() - 1); ContiguousIterator a_it(batch_shape, a_batch_strides, batch_shape.size() - 1);
ContiguousIterator b_it(batch_shape, b_batch_strides, batch_shape.size() - 1); ContiguousIterator b_it(batch_shape, b_batch_strides, batch_shape.size() - 1);
for (size_t i = 0; i < batch_count / batch_shape.back(); ++i) { for (size_t i = 0; i < nbatch; ++i) {
matmul.run( matmul.run(
encoder, encoder,
out.data<int8_t>() + out.itemsize() * i * batch_shape.back() * M * N, out.data<int8_t>() + out.itemsize() * i * batch_shape.back() * M * N,
@ -448,10 +457,21 @@ void AddMM::eval_gpu(const std::vector<array>& inputs, array& out) {
b_batch_strides.back(), b_batch_strides.back(),
c_batch_strides.back()); c_batch_strides.back());
encoder.set_input_array(a);
encoder.set_input_array(b);
encoder.set_input_array(c);
encoder.set_output_array(out);
auto nbatch = batch_count / batch_shape.back();
if (nbatch == 1) {
matmul.run(encoder, out.data<int8_t>(), a.data<int8_t>(), b.data<int8_t>(), c.data<int8_t>(), alpha_, beta_);
return;
}
ContiguousIterator a_it(batch_shape, a_batch_strides, batch_shape.size() - 1); ContiguousIterator a_it(batch_shape, a_batch_strides, batch_shape.size() - 1);
ContiguousIterator b_it(batch_shape, b_batch_strides, batch_shape.size() - 1); ContiguousIterator b_it(batch_shape, b_batch_strides, batch_shape.size() - 1);
ContiguousIterator c_it(batch_shape, c_batch_strides, batch_shape.size() - 1); ContiguousIterator c_it(batch_shape, c_batch_strides, batch_shape.size() - 1);
for (size_t i = 0; i < batch_count / batch_shape.back(); ++i) { for (size_t i = 0; i < nbatch; ++i) {
matmul.run( matmul.run(
encoder, encoder,
out.data<int8_t>() + out.itemsize() * i * batch_shape.back() * M * N, out.data<int8_t>() + out.itemsize() * i * batch_shape.back() * M * N,

5
mlx/backend/cuda/sort.cu
View File

@ -79,9 +79,6 @@ void segmented_sort(cu::CommandEncoder& encoder, Args&&... args) {
void gpu_sort(const Stream& s, array in, array& out_, int axis, bool argsort) { void gpu_sort(const Stream& s, array in, array& out_, int axis, bool argsort) {
array out = out_; array out = out_;
auto& encoder = cu::get_command_encoder(s); auto& encoder = cu::get_command_encoder(s);
encoder.set_input_array(in);
encoder.set_output_array(out);
if (axis < 0) { if (axis < 0) {
axis += in.ndim(); axis += in.ndim();
} }
@ -106,6 +103,8 @@ void gpu_sort(const Stream& s, array in, array& out_, int axis, bool argsort) {
in.flags()); in.flags());
} }
encoder.set_input_array(in);
encoder.set_output_array(out);
encoder.launch_kernel([&](cudaStream_t stream) { encoder.launch_kernel([&](cudaStream_t stream) {
MLX_SWITCH_ALL_TYPES(in.dtype(), CTYPE, { MLX_SWITCH_ALL_TYPES(in.dtype(), CTYPE, {
if constexpr (!std::is_same_v<CTYPE, complex64_t>) { if constexpr (!std::is_same_v<CTYPE, complex64_t>) {