mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
75 lines
2.7 KiB
C++
75 lines
2.7 KiB
C++
/*
|
|
* Copyright (c) 2020-2023, 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/cudaUtils.h"
|
|
#include "tensorrt_llm/common/workspace.h"
|
|
#include "tensorrt_llm/runtime/torchUtils.h"
|
|
#include "tensorrt_llm/thop/thUtils.h"
|
|
|
|
#include <ATen/cuda/EmptyTensor.h>
|
|
|
|
#include <cuda_fp16.h>
|
|
|
|
#include <cstdint>
|
|
|
|
TRTLLM_NAMESPACE_BEGIN
|
|
|
|
namespace torch_ext
|
|
{
|
|
|
|
std::tuple<torch::Tensor, torch::Tensor> fused_topk_softmax(torch::Tensor const& router_logits, int64_t const top_k,
|
|
int64_t const num_experts_total, int64_t const start_expert, int64_t const end_expert)
|
|
{
|
|
// TODO: enable once the kernel has been added to the internal CUTLASS library.
|
|
TLLM_CHECK_WITH_INFO(false, "Fused topk/softmax op has not been enabled yet.");
|
|
|
|
CHECK_INPUT(router_logits, torch::kBFloat16);
|
|
|
|
auto const& router_logits_shape = router_logits.sizes();
|
|
auto const& rank = router_logits_shape.size();
|
|
|
|
TORCH_CHECK(rank == 2, "router_logits should be 2D tensor.");
|
|
int64_t const num_rows = router_logits_shape[0];
|
|
|
|
auto token_final_scales
|
|
= torch::empty({num_rows, top_k}, torch::dtype(torch::kFloat32).device(router_logits.device()));
|
|
auto token_selected_experts
|
|
= torch::empty({num_rows, top_k}, torch::dtype(torch::kInt32).device(router_logits.device()));
|
|
|
|
// auto stream = at::cuda::getCurrentCUDAStream(router_logits.get_device());
|
|
// tensorrt_llm::kernels::topkGatingSoftmaxKernelLauncher(
|
|
// static_cast<__nv_bfloat16 const*>(router_logits.const_data_ptr()),
|
|
// static_cast<float*>(token_final_scales.data_ptr()), static_cast<int*>(token_selected_experts.data_ptr()),
|
|
// num_rows, top_k, num_experts_total, start_expert, end_expert, stream);
|
|
return {token_final_scales, token_selected_experts};
|
|
}
|
|
} // namespace torch_ext
|
|
|
|
TRTLLM_NAMESPACE_END
|
|
|
|
TORCH_LIBRARY_FRAGMENT(trtllm, m)
|
|
{
|
|
m.def(
|
|
"fused_topk_softmax(Tensor router_logits, int top_k, "
|
|
"int num_experts_total, int start_expert, "
|
|
"int end_expert) -> (Tensor, Tensor) ");
|
|
}
|
|
|
|
TORCH_LIBRARY_IMPL(trtllm, CUDA, m)
|
|
{
|
|
m.impl("fused_topk_softmax", &tensorrt_llm::torch_ext::fused_topk_softmax);
|
|
}
|