mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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79 lines
3.0 KiB
C++
79 lines
3.0 KiB
C++
/*
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* Copyright (c) 2020-2023, NVIDIA CORPORATION. All rights reserved.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "fmhaRunner.h"
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#include "tensorrt_llm/common/cudaUtils.h"
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#include "tensorrt_llm/kernels/contextFusedMultiHeadAttention/fused_multihead_attention_common.h"
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#include "tensorrt_llm/kernels/multiHeadAttentionCommon.h"
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////////////////////////////////////////////////////////////////////////////////////////////////////
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namespace tensorrt_llm
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{
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namespace kernels
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{
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TllmGenFmhaRunner::TllmGenFmhaRunner(Data_type dtypeQ, Data_type dtypeKv, Data_type dtypeOut)
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: mSM(tensorrt_llm::common::getSMVersion())
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, mDtypeQ(dtypeQ)
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, mDtypeKv(dtypeKv)
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, mDtypeOut(dtypeOut)
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{
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TLLM_CHECK_WITH_INFO(mSM == kSM_100, "Unsupported architecture");
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TLLM_CHECK_WITH_INFO(
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mDtypeQ == DATA_TYPE_E4M3 || mDtypeQ == DATA_TYPE_FP16 || mDtypeQ == DATA_TYPE_BF16, "Unsupported Q data type");
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TLLM_CHECK_WITH_INFO(mDtypeKv == DATA_TYPE_E4M3 || mDtypeKv == DATA_TYPE_FP16 || mDtypeKv == DATA_TYPE_BF16,
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"Unsupported Kv data type");
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TLLM_CHECK_WITH_INFO(mDtypeOut == DATA_TYPE_E2M1 || mDtypeOut == DATA_TYPE_E4M3 || mDtypeOut == DATA_TYPE_FP16
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|| mDtypeOut == DATA_TYPE_BF16,
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"Unsupported Output data type");
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auto const [freeMemory, totalMemory] = tensorrt_llm::common::getDeviceMemoryInfo(false);
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mTotalDeviceMemory = totalMemory;
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TLLM_CHECK_WITH_INFO(mTotalDeviceMemory > 0, "Total device memory is invalid");
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mKernel = getTllmFmhaKernels(mDtypeQ, mDtypeKv, mDtypeOut, mSM);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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void TllmGenFmhaRunner::run(TllmGenFmhaRunnerParams const& runnerParams)
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{
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mKernel->run(runnerParams);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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bool TllmGenFmhaRunner::isSupported(TllmGenFmhaRunnerParams const& runnerParams) const
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{
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return mKernel->checkIfKernelExist(runnerParams).first;
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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std::pair<bool, std::string> TllmGenFmhaRunner::isSupportedWithInfo(TllmGenFmhaRunnerParams const& runnerParams) const
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{
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return mKernel->checkIfKernelExist(runnerParams);
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}
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size_t TllmGenFmhaRunner::getTotalDeviceMemory() const
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{
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return mTotalDeviceMemory;
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}
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} // namespace kernels
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} // namespace tensorrt_llm
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