TensorRT-LLMs/cpp/tensorrt_llm/pybind/batch_manager/llmRequest.cpp
2024-12-16 21:50:47 -08:00

95 lines
3.7 KiB
C++

/*
* SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* 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.
*/
#include "llmRequest.h"
#include "tensorrt_llm/batch_manager/llmRequest.h"
#include "tensorrt_llm/pybind/common/bindTypes.h"
#include "tensorrt_llm/runtime/torch.h"
#include "tensorrt_llm/runtime/torchUtils.h"
#include "tensorrt_llm/runtime/torchView.h"
#include <ATen/ATen.h>
#include <torch/extension.h>
#include <memory>
namespace tb = tensorrt_llm::batch_manager;
namespace tr = tensorrt_llm::runtime;
namespace tle = tensorrt_llm::executor;
using namespace tensorrt_llm::pybind::batch_manager;
using LlmRequestPtr = std::shared_ptr<tb::LlmRequest>;
using RequestList = std::list<LlmRequestPtr>;
namespace
{
std::optional<tb::LlmRequest::TensorPtr> from_torch(std::optional<LlmRequest::TensorPtr> torchPtr)
{
if (torchPtr)
{
return tr::TorchView::of(torchPtr.value());
}
return std::nullopt;
}
} // namespace
std::optional<tb::LlmRequest::LogitsPostProcessor> LlmRequest::callbackAdapter(
std::optional<LlmRequest::LogitsPostProcessor> callback)
{
if (!callback)
{
return std::nullopt;
}
return [callback](RequestIdType reqId, tensorrt_llm::runtime::ITensor::SharedPtr& tensor,
tensorrt_llm::batch_manager::LlmRequest::BeamTokens const& tokens,
tensorrt_llm::runtime::BufferManager::CudaStreamPtr stream, std::optional<RequestIdType> clientId)
{
at::Tensor atTensor = tr::Torch::tensor(tensor);
callback.value()(reqId, atTensor, tokens, runtime::TorchUtils::stream(*stream).unwrap(), clientId);
};
}
std::shared_ptr<tb::LlmRequest> LlmRequest::toTrtLlm() const
{
auto embeddingBias = from_torch(mEmbeddingBias);
auto badWordsList = from_torch(mBadWordsList);
auto stopWordsList = from_torch(mStopWordsList);
auto promptEmbeddingTable = from_torch(mPromptEmbeddingTable);
auto mropeRotaryCosSin = from_torch(mMropeRotaryCosSin);
auto loraWeights = from_torch(mLoraWeights);
auto loraConfig = from_torch(mLoraConfig);
auto draftLogits = from_torch(mDraftLogits);
auto encoderInputFeatures = from_torch(mEncoderInputFeatures);
auto crossAttentionMask = from_torch(mCrossAttentionMask);
auto skipCrossAttnBlocks = from_torch(mSkipCrossAttnBlocks);
return std::make_shared<tb::LlmRequest>(mRequestId, mMaxNewTokens,
std::make_shared<std::vector<TokenIdType>>(mTokens.at(0)), mSamplingConfig, mIsStreaming, mEndId, mPadId,
embeddingBias, badWordsList, stopWordsList, mPositionIds, promptEmbeddingTable, mPromptVocabSize,
mropeRotaryCosSin, mMropePositionDeltas, mLoraTaskId, loraWeights, loraConfig, mLookaheadConfig,
mKvCacheRetentionConfig, returnLogProbs(), mReturnContextLogits, mReturnGenerationLogits, mDraftTokens,
draftLogits, mExcludeInputFromOutput, callbackAdapter(mLogitsPostProcessor), mApplyLogitsPostProcessorBatched,
mEncoderTokens, mReturnEncoderOutput, mClientId, mPriority, encoderInputFeatures, mEncoderOutputLength,
crossAttentionMask, tb::LlmRequestType::LLMREQUEST_TYPE_CONTEXT_AND_GENERATION, mInputTokenExtraIds,
mNumReturnSequences, std::nullopt, skipCrossAttnBlocks);
}