TensorRT-LLMs/cpp/tensorrt_llm/kernels/mlaKernels.h
Kaiyu Xie 3aa6b11d13
Update TensorRT-LLM (#2936)
* Update TensorRT-LLM

---------

Co-authored-by: changcui <cuichang147@gmail.com>
2025-03-18 21:25:19 +08:00

81 lines
2.3 KiB
C++

/*
* Copyright (c) 2019-2023, 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.
*/
#pragma once
#include "tensorrt_llm/common/cudaUtils.h"
#include "tensorrt_llm/kernels/unfusedAttentionKernels.h"
#include <assert.h>
#include <cstdint>
#include <cuda_fp16.h>
#include <cuda_runtime.h>
namespace tensorrt_llm
{
namespace kernels
{
struct MlaMetaParams
{
int32_t q_lora_rank = 0;
int32_t kv_lora_rank = 0;
int32_t qk_nope_head_dim = 0;
int32_t qk_rope_head_dim = 0;
int32_t v_head_dim = 0;
int32_t predicted_tokens_per_seq = 1;
int32_t num_layers = 0;
auto data() const
{
return std::make_tuple(q_lora_rank, kv_lora_rank, qk_nope_head_dim, qk_rope_head_dim, v_head_dim,
predicted_tokens_per_seq, num_layers);
}
};
template <typename T>
struct MlaParams
{
T const* latent_cache; // cKV + k_pe
T* attention_input_buf; // [b, s, 3, h, d_h + r]
T* context_buf;
T* q_pe; // [b, h, d_r], strided
float2 const* cos_sin_cache; // [s, rope]
int32_t batch_size;
int32_t acc_q_len;
int32_t head_num; // h
void* workspace;
int32_t const* cache_seq_lens;
int* seqQOffset;
uint32_t* fmha_tile_counter;
int32_t max_input_seq_len;
int* cu_q_seqlens;
int* cu_kv_seqlens;
int32_t q_pe_ld;
int32_t q_pe_stride;
MlaMetaParams meta;
int const* block_ids_per_seq;
};
template <typename T, typename KVCacheBuffer>
void invokeMLARopeContext(MlaParams<T>& params, KVCacheBuffer kv_cache_buffer, cudaStream_t stream);
template <typename T, typename KVCacheBuffer>
void invokeMLARopeGeneration(MlaParams<T>& params, KVCacheBuffer kv_cache_buffer, cudaStream_t stream);
} // namespace kernels
} // namespace tensorrt_llm