mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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73 lines
2.6 KiB
C++
73 lines
2.6 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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#pragma once
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#include "tensorrt_llm/kernels/decoderMaskedMultiheadAttention/decoderXQAImpl.h"
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#include "compileEngine.h"
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#include "cubinObjRegistry.h"
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#include "tensorrt_llm/kernels/decoderMaskedMultiheadAttention/decoderXQAImplCommon.h"
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#include "tensorrt_llm/kernels/trtllmGenKernels/fmha/fmhaRunner.h"
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#include "tensorrt_llm/plugins/common/plugin.h"
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#include <unordered_set>
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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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class DecoderXQAImplJIT : public DecoderXQAImpl
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{
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public:
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DecoderXQAImplJIT(DecoderXQARunner* runner);
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bool shouldUse(XQAParams const& xqaParams, bool forConfigurePlugin) override;
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void prepare(XQAParams const& xqaParams) override;
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~DecoderXQAImplJIT() override = default;
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protected:
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void runWithKVLinearBuffer(
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XQAParams const& xqaParams, KVLinearBuffer const& kv_linear_buffer, cudaStream_t const& stream) override;
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void runWithKVBlockArray(
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XQAParams const& xqaParams, KVBlockArray const& kv_block_array, cudaStream_t const& stream) override;
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private:
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std::shared_ptr<tensorrt_llm::common::CUDADriverWrapper> mDriver;
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//! Whether DecoderXQAImplJIT supports xqaParams.
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bool supportConfig(XQAParams const& xqaParams, bool forConfigurePlugin) const;
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//! Whether DecoderXQAImplJIT has perf gain over the default (non-XQA-optimized) implementation.
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bool mayHavePerfGain(XQAParams const& xqaParams) const;
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void prepareForActualXQAParams(XQAParams const& xqaParams);
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template <typename T, typename KVCacheBuffer>
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void runImpl(XQAParams const& xqaParams, KVCacheBuffer const& kv_cache_buffer, int multiprocessor_count,
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cudaStream_t const& stream);
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template <typename KVCacheBuffer>
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void runDispatchKVCacheBuffer(
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XQAParams const& xqa_params, KVCacheBuffer const& kv_cache_buffer, cudaStream_t const& stream);
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bool mForceXQA;
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int mSM;
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jit::CubinObjKey getCubinObjKeyFromXQAParams(XQAParams const& xqaParams) const;
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};
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} // namespace kernels
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} // namespace tensorrt_llm
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