/* 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 #include "glog/logging.h" #include "gtest/gtest.h" #include "paddle/framework/mixed_vector.h" #include "paddle/platform/gpu_info.h" template using vec = paddle::framework::Vector; TEST(mixed_vector, CPU_VECTOR) { vec tmp; for (int i = 0; i < 10; ++i) { tmp.push_back(i); } ASSERT_EQ(tmp.size(), 10); vec tmp2; tmp2 = tmp; ASSERT_EQ(tmp2.size(), 10); for (int i = 0; i < 10; ++i) { ASSERT_EQ(tmp2[i], i); ASSERT_EQ(tmp2[i], tmp[i]); } int cnt = 0; for (auto& t : tmp2) { ASSERT_EQ(t, cnt); ++cnt; } } static __global__ void multiply_10(int* ptr) { for (int i = 0; i < 10; ++i) { ptr[i] *= 10; } } cudaStream_t GetCUDAStream(paddle::platform::CUDAPlace place) { return reinterpret_cast( paddle::platform::DeviceContextPool::Instance().Get(place)) ->stream(); } TEST(mixed_vector, GPU_VECTOR) { vec tmp; for (int i = 0; i < 10; ++i) { tmp.push_back(i); } ASSERT_EQ(tmp.size(), 10); paddle::platform::CUDAPlace gpu(0); multiply_10<<<1, 1, 0, GetCUDAStream(gpu)>>>(tmp.MutableData(gpu)); for (int i = 0; i < 10; ++i) { ASSERT_EQ(tmp[i], i * 10); } } TEST(mixed_vector, MultiGPU) { if (paddle::platform::GetCUDADeviceCount() < 2) { LOG(WARNING) << "Skip mixed_vector.MultiGPU since there are not multiple " "GPUs in your machine."; return; } vec tmp; for (int i = 0; i < 10; ++i) { tmp.push_back(i); } ASSERT_EQ(tmp.size(), 10); paddle::platform::CUDAPlace gpu0(0); multiply_10<<<1, 1, 0, GetCUDAStream(gpu0)>>>(tmp.MutableData(gpu0)); paddle::platform::CUDAPlace gpu1(1); multiply_10<<<1, 1, 0, GetCUDAStream(gpu1)>>>(tmp.MutableData(gpu1)); for (int i = 0; i < 10; ++i) { ASSERT_EQ(tmp[i], i * 100); } }