TensorRT-LLMs/cpp/tensorrt_llm/batch_manager/updateDecoderBuffers.cpp
Robin Kobus a8141a4513
refactor: Speculative decoding buffers part 2 (#5316)
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
2025-06-27 17:41:48 +02:00

79 lines
3.4 KiB
C++

/*
* SPDX-FileCopyrightText: Copyright (c) 2025 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 "tensorrt_llm/batch_manager/updateDecoderBuffers.h"
#include "tensorrt_llm/batch_manager/decoderBuffers.h"
#include "tensorrt_llm/common/nvtxUtils.h"
#include "tensorrt_llm/runtime/decoderState.h"
#include "tensorrt_llm/runtime/iTensor.h"
namespace tensorrt_llm::batch_manager
{
using BufferManager = tensorrt_llm::runtime::BufferManager;
using TensorPtr = runtime::ITensor::SharedPtr;
using ITensor = runtime::ITensor;
using SizeType32 = tensorrt_llm::runtime::SizeType32;
runtime::CudaEvent UpdateDecoderBuffers::operator()(runtime::ModelConfig const& modelConfig,
DecoderOutputBuffers& decoderOutputBuffers, runtime::BufferManager const& copyBufferManager,
runtime::decoder::DecoderState const& decoderState, bool returnLogProbs,
runtime::CudaEvent const& decoderFinishEvent) const
{
TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);
NVTX3_SCOPED_RANGE(updateDecoderBuffers);
// Chain copy after decoder event, using a different stream
copyBufferManager.getStream().wait(decoderFinishEvent);
copyBufferManager.copy(*decoderState.getAllNewTokens(), *decoderOutputBuffers.newOutputTokensHost);
copyBufferManager.copy(*decoderState.getSequenceLengths(), *decoderOutputBuffers.sequenceLengthsHost);
auto const finishedSumDevice = decoderState.getFinishedSum();
copyBufferManager.copy(*finishedSumDevice, *decoderOutputBuffers.finishedSumHost);
auto const finishReasonsDevice = decoderState.getFinishReasons();
copyBufferManager.copy(*finishReasonsDevice, *decoderOutputBuffers.finishReasonsHost);
if (returnLogProbs)
{
copyBufferManager.copy(*decoderState.getCumLogProbs(), *decoderOutputBuffers.cumLogProbsHost);
copyBufferManager.copy(*decoderState.getLogProbs(), *decoderOutputBuffers.logProbsHost);
}
if (modelConfig.getSpeculativeDecodingMode().predictsDraftTokens())
{
// TODO: keep data on device for next iteration
copyBufferManager.copy(*decoderState.getNextDraftTokens(), *decoderOutputBuffers.nextDraftTokensHost);
if (modelConfig.getSpeculativeDecodingMode().variableDraftLength())
{
copyBufferManager.copy(
*decoderState.getNextDraftTokensLengths(), *decoderOutputBuffers.nextDraftTokensLengthsHost);
copyBufferManager.copy(
*decoderState.getPrevDraftTokensLengths(), *decoderOutputBuffers.prevDraftTokensLengthsHost);
}
}
runtime::CudaEvent copyEvent{};
copyBufferManager.getStream().record(copyEvent);
// Store the event for later sync. Sync stream before calling next decoder. Sync host before updating requests.
TLLM_LOG_TRACE("%s stop", __PRETTY_FUNCTION__);
return copyEvent;
}
} // namespace tensorrt_llm::batch_manager