/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/framework/tensor_util.h" #include #include namespace paddle { namespace framework { TEST(CopyFrom, Tensor) { Tensor src_tensor; Tensor dst_tensor; platform::CPUDeviceContext cpu_ctx((platform::CPUPlace())); int* src_ptr = src_tensor.mutable_data(make_ddim({3, 3}), platform::CPUPlace()); int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9}; memcpy(src_ptr, arr, 9 * sizeof(int)); src_tensor.set_layout(DataLayout::kAnyLayout); auto cpu_place = new platform::CPUPlace(); CopyFrom(src_tensor, *cpu_place, &dst_tensor); const int* dst_ptr = dst_tensor.data(); ASSERT_NE(src_ptr, dst_ptr); for (size_t i = 0; i < 9; ++i) { EXPECT_EQ(src_ptr[i], dst_ptr[i]); } EXPECT_TRUE(dst_tensor.layout() == src_tensor.layout()); Tensor slice_tensor = src_tensor.Slice(1, 2); CopyFrom(slice_tensor, *cpu_place, &dst_tensor); const int* slice_ptr = slice_tensor.data(); dst_ptr = dst_tensor.data(); ASSERT_NE(dst_ptr, slice_ptr); for (size_t i = 0; i < 3; ++i) { EXPECT_EQ(dst_ptr[i], slice_ptr[i]); } EXPECT_TRUE(dst_tensor.layout() == src_tensor.layout()); #ifdef PADDLE_WITH_CUDA { Tensor src_tensor; Tensor gpu_tensor; Tensor dst_tensor; int* src_ptr = src_tensor.mutable_data(make_ddim({3, 3}), platform::CPUPlace()); int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9}; memcpy(src_ptr, arr, 9 * sizeof(int)); // CPU Tensor to GPU Tensor auto gpu_place = new platform::CUDAPlace(0); platform::CUDADeviceContext gpu_ctx(*gpu_place); CopyFrom(src_tensor, *gpu_place, gpu_ctx, &gpu_tensor); // GPU Tensor to CPU Tensor auto cpu_place = new platform::CPUPlace(); CopyFrom(gpu_tensor, *cpu_place, gpu_ctx, &dst_tensor); // Sync before Compare Tensors gpu_ctx.Wait(); const int* dst_ptr = dst_tensor.data(); ASSERT_NE(src_ptr, dst_ptr); for (size_t i = 0; i < 9; ++i) { EXPECT_EQ(src_ptr[i], dst_ptr[i]); } Tensor slice_tensor = src_tensor.Slice(1, 2); // CPU Slice Tensor to GPU Tensor CopyFrom(slice_tensor, *gpu_place, gpu_ctx, &gpu_tensor); // GPU Tensor to CPU Tensor CopyFrom(gpu_tensor, *cpu_place, gpu_ctx, &dst_tensor); // Sync before Compare Slice Tensors gpu_ctx.Wait(); const int* slice_ptr = slice_tensor.data(); dst_ptr = dst_tensor.data(); ASSERT_NE(dst_ptr, slice_ptr); for (size_t i = 0; i < 3; ++i) { EXPECT_EQ(dst_ptr[i], slice_ptr[i]); } EXPECT_TRUE(dst_tensor.layout() == src_tensor.layout()); } #endif } TEST(CopyFromVector, Tensor) { using namespace paddle::framework; using namespace paddle::platform; { std::vector src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9}; Tensor cpu_tensor; // Copy to CPU Tensor cpu_tensor.Resize(make_ddim({3, 3})); auto cpu_place = new paddle::platform::CPUPlace(); CopyFromVector(src_vec, &cpu_tensor); // Compare Tensors const int* cpu_ptr = cpu_tensor.data(); const int* src_ptr = src_vec.data(); ASSERT_NE(src_ptr, cpu_ptr); for (size_t i = 0; i < 9; ++i) { EXPECT_EQ(src_ptr[i], cpu_ptr[i]); } src_vec.erase(src_vec.begin(), src_vec.begin() + 5); cpu_tensor.Resize(make_ddim({2, 2})); CopyFromVector(src_vec, &cpu_tensor); cpu_ptr = cpu_tensor.data(); src_ptr = src_vec.data(); ASSERT_NE(src_ptr, cpu_ptr); for (size_t i = 0; i < 5; ++i) { EXPECT_EQ(src_ptr[i], cpu_ptr[i]); } delete cpu_place; } #ifdef PADDLE_WITH_CUDA { std::vector src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9}; Tensor cpu_tensor; Tensor gpu_tensor; Tensor dst_tensor; // Copy to CPU Tensor cpu_tensor.Resize(make_ddim({3, 3})); auto cpu_place = new paddle::platform::CPUPlace(); CPUDeviceContext cpu_ctx(*cpu_place); CopyFromVector(src_vec, cpu_ctx, &cpu_tensor); // Copy to GPUTensor gpu_tensor.Resize(make_ddim({3, 3})); auto gpu_place = new paddle::platform::CUDAPlace(); CUDADeviceContext gpu_ctx(*gpu_place); CopyFromVector(src_vec, gpu_ctx, &gpu_tensor); // Copy from GPU to CPU tensor for comparison CopyFrom(gpu_tensor, *cpu_place, gpu_ctx, &dst_tensor); // Sync before Compare Tensors gpu_ctx.Wait(); const int* src_ptr = src_vec.data(); const int* cpu_ptr = cpu_tensor.data(); const int* dst_ptr = dst_tensor.data(); ASSERT_NE(src_ptr, cpu_ptr); ASSERT_NE(src_ptr, dst_ptr); for (size_t i = 0; i < 9; ++i) { EXPECT_EQ(src_ptr[i], cpu_ptr[i]); EXPECT_EQ(src_ptr[i], dst_ptr[i]); } src_vec.erase(src_vec.begin(), src_vec.begin() + 5); cpu_tensor.Resize(make_ddim({2, 2})); CopyFromVector(src_vec, cpu_ctx, &cpu_tensor); gpu_tensor.Resize(make_ddim({2, 2})); CopyFromVector(src_vec, gpu_ctx, &gpu_tensor); CopyFrom(gpu_tensor, *cpu_place, gpu_ctx, &dst_tensor); // Sync before Compare Tensors gpu_ctx.Wait(); src_ptr = src_vec.data(); cpu_ptr = cpu_tensor.data(); dst_ptr = dst_tensor.data(); ASSERT_NE(src_ptr, cpu_ptr); ASSERT_NE(src_ptr, dst_ptr); for (size_t i = 0; i < 5; ++i) { EXPECT_EQ(src_ptr[i], cpu_ptr[i]); EXPECT_EQ(src_ptr[i], dst_ptr[i]); } delete cpu_place; delete gpu_place; } #endif } TEST(CopyToVector, Tensor) { using namespace paddle::framework; using namespace paddle::platform; { Tensor src; int* src_ptr = src.mutable_data({3, 3}, CPUPlace()); for (int i = 0; i < 3 * 3; ++i) { src_ptr[i] = i; } CPUPlace place; std::vector dst; CopyToVector(src, &dst); for (int i = 0; i < 3 * 3; ++i) { EXPECT_EQ(src_ptr[i], dst[i]); } } #ifdef PADDLE_WITH_CUDA { std::vector src_vec = {1, 2, 3, 4, 5, 6, 7, 8, 9}; Tensor gpu_tensor; CUDAPlace place; CUDADeviceContext gpu_ctx(place); CopyFromVector(src_vec, gpu_ctx, &gpu_tensor); std::vector dst; CopyToVector(gpu_tensor, gpu_ctx, &dst); for (int i = 0; i < 3 * 3; ++i) { EXPECT_EQ(src_vec[i], dst[i]); } } #endif } } // namespace framework } // namespace paddle