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https://github.com/NVIDIA/TensorRT-LLM.git
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655524dd82
* Update TensorRT-LLM --------- Co-authored-by: Bhuvanesh Sridharan <bhuvan.sridharan@gmail.com> Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
112 lines
2.8 KiB
C++
112 lines
2.8 KiB
C++
/*
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* Copyright (c) 2022-2024, 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/assert.h"
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#include "tensorrt_llm/runtime/iTensor.h"
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#include "tensorrt_llm/runtime/torchUtils.h"
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#include <ATen/ATen.h>
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#include <torch/types.h>
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namespace tensorrt_llm::runtime
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{
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class TorchView : virtual public ITensor
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{
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public:
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static ITensor::UniquePtr of(at::Tensor&& tensor)
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{
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return ITensor::UniquePtr{new TorchView{std::move(tensor)}};
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}
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static ITensor::UniquePtr of(at::Tensor tensor)
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{
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return ITensor::UniquePtr{new TorchView{std::move(tensor)}};
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}
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void* data() override
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{
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return TLLM_LIKELY(getSize() > 0) ? mTensor.data_ptr() : nullptr;
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}
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[[nodiscard]] void const* data() const override
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{
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return TLLM_LIKELY(getSize() > 0) ? mTensor.data_ptr() : nullptr;
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}
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[[nodiscard]] size_t getSize() const override
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{
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return mTensor.numel();
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}
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[[nodiscard]] std::size_t getCapacity() const override
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{
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return mCapacity;
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}
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[[nodiscard]] DataType getDataType() const override
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{
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return TorchUtils::dataType(mTensor.scalar_type());
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}
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[[nodiscard]] MemoryType getMemoryType() const override
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{
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return mTensor.is_cuda() ? MemoryType::kGPU : mTensor.is_pinned() ? MemoryType::kPINNED : MemoryType::kCPU;
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}
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void release() override
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{
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resize(0);
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}
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[[nodiscard]] Shape const& getShape() const override
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{
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return mDims;
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}
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void reshape(Shape const& dims) override
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{
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try
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{
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mTensor.resize_(TorchUtils::shape(dims));
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}
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catch (c10::Error const& e)
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{
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TLLM_THROW("%s", e.what_without_backtrace());
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}
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mDims = dims;
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if (auto const newSize = volumeNonNegative(dims); mCapacity < newSize)
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{
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mCapacity = newSize;
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}
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}
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private:
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explicit TorchView(at::Tensor&& tensor)
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: mTensor(tensor)
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, mDims{TorchUtils::shape(mTensor.sizes())}
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, mCapacity{static_cast<std::size_t>(mTensor.numel())}
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{
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TLLM_CHECK(mTensor.is_contiguous());
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};
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at::Tensor mTensor;
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Shape mDims;
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std::size_t mCapacity;
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};
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} // namespace tensorrt_llm::runtime
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