mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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113 lines
3.6 KiB
C++
113 lines
3.6 KiB
C++
/*
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* Copyright (c) 2019-2024, NVIDIA CORPORATION. All rights reserved.
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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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#pragma once
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#include "tensorrt_llm/common/allocator.h"
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#include "tensorrt_llm/common/tensor.h"
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#include "tensorrt_llm/layers/decodingParams.h"
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#include "tensorrt_llm/runtime/common.h"
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namespace tensorrt_llm
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{
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namespace layers
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{
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class BaseLayer
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{
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public:
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using SizeType = runtime::SizeType;
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using TokenIdType = runtime::TokenIdType;
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using SizeType32 = runtime::SizeType32;
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BaseLayer(DecoderDomain const& decoderDomain, cudaStream_t stream,
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std::shared_ptr<tensorrt_llm::common::IAllocator> allocator)
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: mStream(stream)
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, mAllocator(std::move(allocator))
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, mDecoderDomain(decoderDomain)
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{
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}
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virtual ~BaseLayer() = default;
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//! @returns cuda stream associated with layer
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[[nodiscard]] cudaStream_t getStream() const noexcept
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{
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return mStream;
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}
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//! @brief set stream to the layer
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void setStream(cudaStream_t stream) noexcept
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{
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mStream = stream;
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}
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//! @returns workspace needed for this layer in bytes
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[[nodiscard]] size_t getWorkspaceSize() const noexcept
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{
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return mWorkspaceSize;
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}
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//! @returns size of memory allocated by layer in bytes
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[[nodiscard]] size_t getAllocatedSize() const noexcept
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{
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return mAllocatedSize;
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}
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// clang-format off
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//! \brief Virtual function to setup internal states of the layer with sampling params
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//! specified in setupParams for the entries specified by batchSlots.
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//! It updates data for new requests in internal tensors inplace.
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//! Thus, it must be called only once for new requests.
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//!
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//! \param batchSize current batch size configured in the system
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//! \param beamWidth current beam width configured in the system
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//! \param batchSlots input tensor [maxBatchSize], address map of the new requests, in pinned memory
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//! \param setupParams shared pointer to params inherited from BaseSetupParams
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// clang-format on
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virtual void setup(runtime::SizeType batchSize, runtime::SizeType beamWidth, runtime::SizeType const* batchSlots,
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std::shared_ptr<BaseSetupParams> setupParams)
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= 0;
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// clang-format off
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//! \brief Virtual function to execute layer.
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//!
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//! \param outputs shared pointer to params inherited from BaseOutputParams
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//! \param inputs shared pointer to params inherited from BaseForwardParams
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// clang-format on
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virtual void forward(std::shared_ptr<BaseOutputParams> outputs, std::shared_ptr<BaseInputParams> inputs) = 0;
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protected:
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// Cuda stream
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cudaStream_t mStream;
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// Memory allocator
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std::shared_ptr<tensorrt_llm::common::IAllocator> mAllocator;
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// Required workspace size in bytes
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size_t mWorkspaceSize{0};
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// Allocated memory size in bytes
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size_t mAllocatedSize{0};
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// Domain in which token decoding is computed
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DecoderDomain mDecoderDomain;
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// TODO to be deprecated
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bool mIsAllocateBuffer{false};
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};
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} // namespace layers
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} // namespace tensorrt_llm
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