TensorRT-LLMs/cpp/tensorrt_llm/kernels/moeUtilOp.h
Li Min 6021a439ab
Make moe permute and final as custom op (#5412)
Signed-off-by: Mindy Li <11663212+limin2021@users.noreply.github.com>
2025-06-27 15:48:33 -07:00

57 lines
3.1 KiB
C++

/*
* Copyright (c) 2019-2025, 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.
*/
#pragma once
#include "cutlass_kernels/include/moe_kernels.h"
#include "tensorrt_llm/common/cudaUtils.h"
#include <cuda_bf16.h>
#include <cuda_fp16.h>
namespace tensorrt_llm::kernels
{
bool fusedBuildExpertMapsSortFirstToken(int const* token_selected_experts, int* unpermuted_token_selected_experts,
int* permuted_source_token_ids, int64_t* expert_first_token_offset, int64_t const num_tokens,
int const num_experts_per_node, int const experts_per_token, int const start_expert, int const end_expert,
cudaStream_t stream);
void buildExpertMaps(int const* token_selected_experts, int* unpermuted_token_selected_experts,
int* unpermuted_source_token_ids, int64_t const num_tokens, int const num_experts_per_node,
int const experts_per_token, int const start_expert, int const end_expert, cudaStream_t stream);
void generateTokenPermutation(int const* unpermuted_token_selected_experts, int const* unpermuted_source_token_ids,
int* permuted_token_selected_experts, int* permuted_source_token_ids, int64_t* expert_first_token_offset,
int64_t num_rows, int64_t num_experts_per_node, int64_t k, cutlass_kernels::CubKeyValueSorter& sorter,
void* sorter_ws, cudaStream_t stream);
template <class InputActivationsType, class ExpandedActivationsType>
void expandInputRowsKernelLauncher(InputActivationsType const* unpermuted_input,
ExpandedActivationsType* permuted_output, float const* unpermuted_scales, float* permuted_scales,
int const* expanded_dest_row_to_expanded_source_row, int* expanded_source_row_to_expanded_dest_row,
int64_t const num_rows, int64_t const* num_valid_tokens_ptr, int64_t const cols, int const k,
int const num_experts_per_node, float const* fc1_act_global_scale, int64_t* expert_first_token_offset,
cutlass_kernels::TmaWarpSpecializedGroupedGemmInput::ElementSF* fc1_act_sf_flat,
cutlass_kernels::TmaWarpSpecializedGroupedGemmInput::ElementSF const* input_sf, cudaStream_t stream);
template <class OutputType, class GemmOutputType, class ScaleBiasType>
void finalizeMoeRoutingKernelLauncher(GemmOutputType const* expanded_permuted_rows,
OutputType* reduced_unpermuted_output, ScaleBiasType const* bias, float const* final_scales,
int const* expanded_source_row_to_expanded_dest_row, int const* expert_for_source_row, int64_t const num_rows,
int64_t const cols, int64_t const experts_per_token, int64_t const* num_valid_ptr,
cutlass_kernels::MOEParallelismConfig parallelism_config, cudaStream_t stream);
} // namespace tensorrt_llm::kernels