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97 lines
3.1 KiB
97 lines
3.1 KiB
// Copyright (c) 2019 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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#include <cstring>
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#include <random>
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#include "gflags/gflags.h"
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/framework/tensor_util.h"
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DECLARE_bool(use_system_allocator);
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namespace paddle {
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namespace framework {
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static std::vector<platform::Place> CreatePlaceList() {
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std::vector<platform::Place> places;
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places.emplace_back(platform::CPUPlace());
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#ifdef PADDLE_WITH_CUDA
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places.emplace_back(platform::CUDAPlace(0));
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#endif
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return places;
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}
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template <typename T>
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static bool CopySameTensorTestMain(const DDim &dims,
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const platform::Place &src_place,
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const platform::Place &dst_place,
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bool sync_copy) {
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FLAGS_use_system_allocator = true; // force to use system allocator
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// Step 1: create a cpu tensor and initialize it with random value;
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Tensor src_cpu_tensor;
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{
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src_cpu_tensor.Resize(dims);
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auto *src_ptr_cpu = src_cpu_tensor.mutable_data<T>(platform::CPUPlace());
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int64_t num = src_cpu_tensor.numel();
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std::random_device rd;
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std::mt19937 gen(rd());
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std::uniform_real_distribution<T> dist(-1000, 1000);
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for (int64_t i = 0; i < num; ++i) {
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src_ptr_cpu[i] = dist(gen);
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}
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}
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// Step 2: copy the source tensor to dst place
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Tensor dst_cpu_tensor;
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{
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Tensor src_tensor;
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TensorCopySync(src_cpu_tensor, src_place, &src_tensor);
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// The source tensor and dst_tensor is the same
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if (sync_copy) {
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TensorCopySync(src_tensor, dst_place, &src_tensor);
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} else {
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TensorCopy(src_tensor, dst_place, &src_tensor);
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platform::DeviceContextPool::Instance().Get(src_place)->Wait();
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platform::DeviceContextPool::Instance().Get(dst_place)->Wait();
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}
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// Get the result cpu tensor
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TensorCopySync(src_tensor, platform::CPUPlace(), &dst_cpu_tensor);
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}
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const void *ground_truth_ptr = src_cpu_tensor.data<void>();
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const void *result_ptr = dst_cpu_tensor.data<void>();
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size_t byte_num = product(dims) * sizeof(T);
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return std::memcmp(ground_truth_ptr, result_ptr, byte_num) == 0;
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}
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TEST(test_tensor_copy, test_copy_same_tensor) {
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using DataType = float;
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auto dims = make_ddim({3, 4, 5});
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auto places = CreatePlaceList();
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for (auto &src_p : places) {
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for (auto &dst_p : places) {
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ASSERT_TRUE(CopySameTensorTestMain<DataType>(dims, src_p, dst_p, true));
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ASSERT_TRUE(CopySameTensorTestMain<DataType>(dims, src_p, dst_p, false));
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}
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}
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}
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} // namespace framework
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} // namespace paddle
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