mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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75 lines
2.2 KiB
C++
75 lines
2.2 KiB
C++
/*
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* Copyright (c) 2022-2023, 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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#include "torchAllocator.h"
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#include "tensorrt_llm/common/assert.h"
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#include "tensorrt_llm/common/cudaUtils.h"
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#include "tensorrt_llm/thop/thUtils.h"
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using namespace tensorrt_llm::thop;
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using namespace tensorrt_llm::common;
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ReallocType TorchAllocator::reallocType(void const* ptr, size_t size) const
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{
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TLLM_CHECK(contains(ptr));
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size_t currentSize = 1;
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at::Tensor const& tensor{mPointerMapping.at(ptr)};
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for (int i = 0; i < tensor.dim(); i++)
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{
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currentSize *= tensor.size(i);
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}
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TLLM_LOG_DEBUG("current_buffer_size: %d, original buffer: %p, new buffer: %d", currentSize, ptr, size);
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if (currentSize < size)
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{
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return ReallocType::INCREASE;
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}
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else if (currentSize == size)
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{
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return ReallocType::REUSE;
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}
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else
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{
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return ReallocType::DECREASE;
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}
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}
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void* TorchAllocator::malloc(size_t size, bool const setZero)
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{
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TLLM_LOG_DEBUG(__PRETTY_FUNCTION__);
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auto const bufSize = static_cast<int64_t>(size);
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torch::Tensor buf = torch::empty({bufSize}, torch::dtype(torch::kUInt8).device(torch::kCUDA));
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void* ptr{buf.data_ptr()};
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if (setZero)
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{
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memSet(ptr, 0, size);
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}
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TLLM_LOG_DEBUG("malloc buffer %p with size %ld", ptr, size);
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mPointerMapping.insert({ptr, buf});
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return ptr;
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}
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void TorchAllocator::free(void** ptr)
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{
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TLLM_LOG_DEBUG(__PRETTY_FUNCTION__);
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mPointerMapping.erase(*ptr);
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*ptr = nullptr;
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}
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void TorchAllocator::memSet(void* ptr, int const val, size_t const size)
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{
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check_cuda_error(cudaMemsetAsync(ptr, val, size, mStream));
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}
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