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https://github.com/PaddlePaddle/FastDeploy.git
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43d86114d8
* TRT backend use pinned memory * refine fd tensor pinned memory logic * TRT enable pinned memory configurable * paddle inference support pinned memory * pinned memory pybindings Co-authored-by: Jason <jiangjiajun@baidu.com>
46 lines
1.3 KiB
C++
46 lines
1.3 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. 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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#ifdef WITH_GPU
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#include <cuda_runtime_api.h>
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#endif
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#include "fastdeploy/core/allocate.h"
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namespace fastdeploy {
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bool FDHostAllocator::operator()(void** ptr, size_t size) const {
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*ptr = malloc(size);
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return *ptr != nullptr;
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}
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void FDHostFree::operator()(void* ptr) const { free(ptr); }
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#ifdef WITH_GPU
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bool FDDeviceAllocator::operator()(void** ptr, size_t size) const {
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return cudaMalloc(ptr, size) == cudaSuccess;
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}
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void FDDeviceFree::operator()(void* ptr) const { cudaFree(ptr); }
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bool FDDeviceHostAllocator::operator()(void** ptr, size_t size) const {
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return cudaMallocHost(ptr, size) == cudaSuccess;
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}
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void FDDeviceHostFree::operator()(void* ptr) const { cudaFreeHost(ptr); }
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#endif
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} // namespace fastdeploy
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