TensorRT-LLMs/cpp/tensorrt_llm/layers/baseLayer.h
2024-09-03 12:14:23 +02:00

110 lines
4.1 KiB
C++

/*
* Copyright (c) 2019-2024, NVIDIA CORPORATION. All rights reserved.
*
* 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 <utility>
#include "tensorrt_llm/layers/decodingParams.h"
#include "tensorrt_llm/runtime/bufferManager.h"
#include "tensorrt_llm/runtime/common.h"
#include "tensorrt_llm/runtime/decodingLayerWorkspace.h"
namespace tensorrt_llm::layers
{
class BaseLayer
{
public:
using SizeType32 = runtime::SizeType32;
using TokenIdType = runtime::TokenIdType;
using BufferConstPtr = runtime::IBuffer::SharedConstPtr;
using BufferPtr = runtime::IBuffer::SharedPtr;
using TensorConstPtr = runtime::ITensor::SharedConstPtr;
using TensorPtr = runtime::ITensor::SharedPtr;
BaseLayer(DecoderDomain decoderDomain, std::shared_ptr<runtime::BufferManager> bufferManager)
: mBufferManager(std::move(bufferManager))
, mDecoderDomain(std::move(decoderDomain))
{
}
virtual ~BaseLayer() = default;
//! @returns cuda stream associated with layer
[[nodiscard]] cudaStream_t getStream() const noexcept
{
return mBufferManager->getStream().get();
}
//! @returns workspace needed for this layer in bytes
[[nodiscard]] virtual size_t getWorkspaceSize() const noexcept
{
return 0;
};
// clang-format off
//! \brief Virtual function to setup internal states of the layer with sampling params
//! specified in setupParams for the entries specified by batchSlots.
//! It updates data for new requests in internal tensors inplace.
//! Thus, it must be called only once for new requests.
//!
//! \param batchSize current batch size configured in the system
//! \param beamWidth current beam width configured in the system
//! \param batchSlots input buffer [maxBatchSize], address map of the new requests, in pinned memory
//! \param setupParams shared pointer to params inherited from BaseSetupParams
// clang-format on
virtual void setup(runtime::SizeType32 batchSize, runtime::SizeType32 beamWidth, TensorConstPtr batchSlots,
std::shared_ptr<BaseSetupParams> const& setupParams,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace)
= 0;
// clang-format off
//! \brief Virtual function to execute layer async on GPU.
//! There must be no stream synchronization inside this function.
//!
//! \param outputs shared pointer to params inherited from BaseDecodingOutputs
//! \param inputs shared pointer to params inherited from BaseForwardParams
// clang-format on
virtual void forwardAsync(std::shared_ptr<BaseDecodingOutputs> const& outputs,
std::shared_ptr<BaseDecodingInputs> const& inputs,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace)
= 0;
// clang-format off
//! \brief Virtual function to execute layer synchronously on CPU / GPU.
//! It is allowed (but not necassary) to synchronize on stream inside this function.
//! It is targeted mainly for prototyping.
//!
//! \param outputs shared pointer to params inherited from BaseDecodingOutputs
//! \param inputs shared pointer to params inherited from BaseForwardParams
// clang-format on
virtual void forwardSync(std::shared_ptr<BaseDecodingOutputs> const& outputs,
std::shared_ptr<BaseDecodingInputs> const& inputs,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace)
{
}
protected:
// Buffer Manager
std::shared_ptr<runtime::BufferManager> mBufferManager;
// Domain in which token decoding is computed
DecoderDomain mDecoderDomain;
};
} // namespace tensorrt_llm::layers