TensorRT-LLMs/cpp/tensorrt_llm/layers/samplingLayer.h
Dan Blanaru 16d2467ea8 Update TensorRT-LLM (#2755)
* Update TensorRT-LLM

---------

Co-authored-by: Denis Kayshev <topenkoff@gmail.com>
Co-authored-by: akhoroshev <arthoroshev@gmail.com>
Co-authored-by: Patrick Reiter Horn <patrick.horn@gmail.com>

Update
2025-02-11 03:01:00 +00:00

80 lines
2.5 KiB
C++

/*
* Copyright (c) 2019-2024, NVIDIA CORPORATION. All rights reserved.
* Copyright (c) 2021, NAVER Corp. Authored by CLOVA.
*
* 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.
*/
#pragma once
#include "tensorrt_llm/executor/types.h"
#include "tensorrt_llm/layers/baseLayer.h"
#include "tensorrt_llm/layers/decodingParams.h"
#include "tensorrt_llm/runtime/common.h"
#include <curand_kernel.h>
namespace tensorrt_llm::layers
{
//! \brief Top class for sampling layers.
//! It sets up and executes TopKSamplingLayer and TopPSamplingLayer samplings
template <typename T>
class SamplingLayer : public BaseLayer
{
public:
using Base = BaseLayer;
SamplingLayer(executor::DecodingMode const& mode, DecoderDomain const& decoderDomain,
std::shared_ptr<runtime::BufferManager> bufferManager);
void setup(runtime::SizeType32 batchSize, runtime::SizeType32 beamWidth, TensorConstPtr batchSlots,
std::shared_ptr<BaseSetupParams> const& setupParams,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace) override;
void forwardAsync(std::shared_ptr<BaseDecodingOutputs> const& outputs,
std::shared_ptr<BaseDecodingInputs> const& inputs,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace) override;
//! @returns workspace needed for this layer in bytes
[[nodiscard]] size_t getWorkspaceSize() const noexcept override;
private:
using Base::mDecoderDomain;
executor::DecodingMode mDecodingMode;
size_t mWorkspaceSize{0};
size_t mSetupWorkspaceSize{0};
TensorPtr mCurandStatesDevice;
TensorPtr mSkipDecodeDevice;
TensorPtr mSkipDecodeHost;
bool mSkipAny{false};
bool mOutputLogProbs{false};
bool mCumLogProbs{false};
TensorPtr mRuntimeMinPHost;
TensorPtr mRuntimeMinPDevice;
bool mUseMinP{false};
std::vector<std::unique_ptr<BaseLayer>> mSamplingLayers;
private:
void allocateBuffer(runtime::SizeType32 batchSize);
};
} // namespace tensorrt_llm::layers