TensorRT-LLMs/cpp/tensorrt_llm/thop/moeAlignOp.cpp
Yihan Wang 9df4dad3b6
[None][fix] Introduce inline namespace to avoid symbol collision (#9541)
Signed-off-by: Yihan Wang <yihwang@nvidia.com>
2025-12-12 23:32:15 +08:00

65 lines
2.2 KiB
C++

/*
* Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "tensorrt_llm/common/config.h"
#include "tensorrt_llm/kernels/moeAlignKernels.h"
#include "thUtils.h"
#include <torch/extension.h>
namespace tk = tensorrt_llm::kernels;
TRTLLM_NAMESPACE_BEGIN
namespace torch_ext
{
void moeAlignBlockSizeOp(torch::Tensor topk_ids, int64_t num_experts, int64_t block_size,
torch::Tensor sorted_token_ids, torch::Tensor expert_ids, torch::Tensor num_tokens_post_pad)
{
// Validate inputs
CHECK_TH_CUDA(topk_ids);
CHECK_CONTIGUOUS(topk_ids);
CHECK_INPUT(sorted_token_ids, torch::kInt32);
CHECK_INPUT(expert_ids, torch::kInt32);
CHECK_INPUT(num_tokens_post_pad, torch::kInt32);
TORCH_CHECK(topk_ids.scalar_type() == torch::kInt32 || topk_ids.scalar_type() == torch::kInt64,
"topk_ids must be int32 or int64");
auto stream = at::cuda::getCurrentCUDAStream();
tk::invokeMoeAlignBlockSize(topk_ids.data_ptr(), topk_ids.element_size(), sorted_token_ids.data_ptr<int32_t>(),
expert_ids.data_ptr<int32_t>(), num_tokens_post_pad.data_ptr<int32_t>(), static_cast<int32_t>(num_experts),
static_cast<int32_t>(block_size), static_cast<int32_t>(topk_ids.numel()),
static_cast<int32_t>(sorted_token_ids.size(0)), stream);
}
} // namespace torch_ext
TRTLLM_NAMESPACE_END
TORCH_LIBRARY_FRAGMENT(trtllm, m)
{
m.def(
"moe_align_block_size(Tensor topk_ids, int num_experts, int block_size, "
"Tensor(a!) sorted_token_ids, Tensor(a!) expert_ids, Tensor(a!) num_tokens_post_pad) -> ()");
}
TORCH_LIBRARY_IMPL(trtllm, CUDA, m)
{
m.impl("moe_align_block_size", &tensorrt_llm::torch_ext::moeAlignBlockSizeOp);
}