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61 lines
2.1 KiB
61 lines
2.1 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include "paddle/fluid/memory/malloc.h"
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#include <string>
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#include <vector>
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#include "paddle/fluid/memory/allocation/allocator_facade.h"
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#include "paddle/fluid/memory/allocation/allocator_strategy.h"
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#ifdef PADDLE_WITH_CUDA
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#include "paddle/fluid/memory/allocation/cuda_device_context_allocator_pool.h"
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#endif
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#include "paddle/fluid/platform/device_context.h"
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#include "paddle/fluid/platform/place.h"
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namespace paddle {
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namespace memory {
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std::shared_ptr<Allocation> AllocShared(const platform::Place &place,
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size_t size) {
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return allocation::AllocatorFacade::Instance().AllocShared(place, size);
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}
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AllocationPtr Alloc(const platform::Place &place, size_t size) {
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return allocation::AllocatorFacade::Instance().Alloc(place, size);
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}
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AllocationPtr Alloc(const platform::DeviceContext &dev_ctx, size_t size) {
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auto place = dev_ctx.GetPlace();
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#ifdef PADDLE_WITH_CUDA
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if (size == 0 || !platform::is_gpu_place(place)) {
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return Alloc(place, size);
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}
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auto *default_dev_ctx = static_cast<platform::CUDADeviceContext *>(
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platform::DeviceContextPool::Instance().Get(place));
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auto &desired_dev_ctx =
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static_cast<const platform::CUDADeviceContext &>(dev_ctx);
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if (default_dev_ctx->stream() == desired_dev_ctx.stream()) {
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return Alloc(place, size);
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} else {
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return allocation::CUDADeviceContextAllocatorPool::Instance().Alloc(
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desired_dev_ctx, size);
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}
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#else
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return Alloc(place, size);
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#endif
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}
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} // namespace memory
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} // namespace paddle
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