mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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132 lines
6.2 KiB
C++
132 lines
6.2 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: Apache-2.0
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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 "llmRequest.h"
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#include "tensorrt_llm/batch_manager/llmRequest.h"
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#include "tensorrt_llm/pybind/common/bindTypes.h"
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#include "tensorrt_llm/runtime/torch.h"
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#include "tensorrt_llm/runtime/torchUtils.h"
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#include "tensorrt_llm/runtime/torchView.h"
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#include <ATen/ATen.h>
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#include <torch/extension.h>
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#include <memory>
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namespace tb = tensorrt_llm::batch_manager;
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namespace tr = tensorrt_llm::runtime;
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namespace tle = tensorrt_llm::executor;
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using namespace tensorrt_llm::pybind::batch_manager;
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using LlmRequestPtr = std::shared_ptr<tb::LlmRequest>;
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using RequestList = std::list<LlmRequestPtr>;
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namespace
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{
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std::optional<tb::LlmRequest::TensorPtr> from_torch(std::optional<LlmRequest::TensorPtr> torchPtr)
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{
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if (torchPtr)
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{
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return tr::TorchView::of(torchPtr.value());
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}
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return std::nullopt;
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}
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} // namespace
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std::optional<tb::LlmRequest::LogitsPostProcessor> LlmRequest::callbackAdapter(
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std::optional<LlmRequest::LogitsPostProcessor> callback)
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{
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if (!callback)
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{
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return std::nullopt;
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}
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return [callback](RequestIdType reqId, tr::ITensor::SharedPtr& tensor, tb::LlmRequest::BeamTokens const& tokens,
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tr::BufferManager::CudaStreamPtr stream, std::optional<RequestIdType> clientId)
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{
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at::Tensor atTensor = tr::Torch::tensor(tensor);
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callback.value()(reqId, atTensor, tokens, runtime::TorchUtils::stream(*stream).unwrap(), clientId);
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};
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}
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std::shared_ptr<tb::LlmRequest> LlmRequest::toTrtLlm() const
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{
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auto const draftTokens = std::make_shared<std::vector<TokenIdType>>(*mDraftTokens.get());
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auto const optDraftTokens = std::optional<std::shared_ptr<std::vector<TokenIdType>>>(draftTokens);
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auto const encoderInputTokens = mEncoderTokens.has_value()
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? std::make_shared<std::vector<TokenIdType>>(*mEncoderTokens.value().get())
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: nullptr;
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auto const optEncoderInputTokens = std::optional<std::shared_ptr<std::vector<TokenIdType>>>(encoderInputTokens);
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return std::make_shared<tb::LlmRequest>( //
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mRequestId, //
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mMaxNewTokens, //
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std::make_shared<std::vector<TokenIdType>>(mTokens.at(0)), //
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mSamplingConfig, //
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mIsStreaming, //
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mEndId, //
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mPadId, //
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from_torch(mEmbeddingBias), //
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from_torch(mBadWordsList), //
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from_torch(mStopWordsList), //
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mPositionIds, //
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from_torch(mPromptEmbeddingTable), //
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mPromptVocabSize, //
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mMultimodalHashes, //
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mMultimodalPositions, //
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mMultimodalLengths, //
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from_torch(mMultimodalEmbedding), //
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from_torch(mMropeRotaryCosSin), //
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mMropePositionDeltas, //
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mLoraTaskId, //
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from_torch(mLoraWeights), //
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from_torch(mLoraConfig), //
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mLookaheadConfig, //
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mKvCacheRetentionConfig, //
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mReturnLogProbs, //
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mReturnContextLogits, //
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mReturnGenerationLogits, //
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optDraftTokens, //
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from_torch(mDraftLogits), //
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mExcludeInputFromOutput, //
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callbackAdapter(mLogitsPostProcessor), //
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mApplyLogitsPostProcessorBatched, //
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optEncoderInputTokens, //
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mReturnEncoderOutput, //
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mClientId, //
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mPriority, //
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from_torch(mEncoderInputFeatures), //
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mEncoderOutputLength, //
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from_torch(mCrossAttentionMask), //
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getLlmRequestType(), //
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std::nullopt, // inputTokenExtraIds
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mNumReturnSequences, //
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mEagleConfig, //
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from_torch(mSkipCrossAttnBlocks), //
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false, // returnPerfMetrics
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mGuidedDecodingParams, //
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mLanguageAdapterUid, //
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mAllottedTimeMs, //
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mContextPhaseParams, //
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mCacheSaltID, //
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mPerfMetrics.timingMetrics.arrivalTime //
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);
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}
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