mindspore/tests/ut/cpp/dataset/profiler_test.cc

162 lines
5.3 KiB
C++

/**
* Copyright 2021 Huawei Technologies Co., Ltd
*
* 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 "common/common.h"
#include "minddata/dataset/engine/perf/profiling.h"
#include "minddata/dataset/include/dataset/datasets.h"
using namespace mindspore::dataset;
using mindspore::LogStream;
using mindspore::MsLogLevel::INFO;
namespace mindspore {
namespace dataset {
namespace test {
class MindDataTestProfiler : public UT::DatasetOpTesting {
protected:
MindDataTestProfiler() {}
Status DeleteFiles(int file_id = 0) {
std::shared_ptr<ProfilingManager> profiler_manager = GlobalContext::profiling_manager();
std::string pipeline_file = "./pipeline_profiling_" + std::to_string(file_id) + ".json";
std::string cpu_util_file = "./minddata_cpu_utilization_" + std::to_string(file_id) + ".json";
std::string dataset_iterator_file = "./dataset_iterator_profiling_" + std::to_string(file_id) + ".txt";
if (remove(pipeline_file.c_str()) == 0 && remove(cpu_util_file.c_str()) == 0 &&
remove(dataset_iterator_file.c_str()) == 0) {
return Status::OK();
} else {
RETURN_STATUS_UNEXPECTED("Error deleting profiler files");
}
}
};
/// Feature: MindData Profiling Support
/// Description: Test MindData Profiling with profiling enabled for pipeline with ImageFolder
/// Expectation: Profiling files are created.
TEST_F(MindDataTestProfiler, TestProfilerManager1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestProfilerManager1.";
// Enable profiler and check
common::SetEnv("RANK_ID", "1");
std::shared_ptr<ProfilingManager> profiler_manager = GlobalContext::profiling_manager();
EXPECT_OK(profiler_manager->Init());
EXPECT_OK(profiler_manager->Start());
EXPECT_TRUE(profiler_manager->IsProfilingEnable());
std::string folder_path = datasets_root_path_ + "/testPK/data/";
std::shared_ptr<Dataset> ds = ImageFolder(folder_path, true, std::make_shared<SequentialSampler>(0, 2));
EXPECT_NE(ds, nullptr);
ds = ds->Repeat(2);
EXPECT_NE(ds, nullptr);
ds = ds->Shuffle(4);
EXPECT_NE(ds, nullptr);
// Create objects for the tensor ops
std::shared_ptr<TensorTransform> one_hot = std::make_shared<transforms::OneHot>(10);
EXPECT_NE(one_hot, nullptr);
// Create a Map operation, this will automatically add a project after map
ds = ds->Map({one_hot}, {"label"}, {"label"}, {"label"});
EXPECT_NE(ds, nullptr);
ds = ds->Take(4);
EXPECT_NE(ds, nullptr);
ds = ds->Batch(2, true);
EXPECT_NE(ds, nullptr);
// No columns are specified, use all columns
std::shared_ptr<Iterator> iter = ds->CreateIterator();
EXPECT_NE(iter, nullptr);
// Iterate the dataset and get each row
std::vector<mindspore::MSTensor> row;
ASSERT_OK(iter->GetNextRow(&row));
uint64_t i = 0;
while (row.size() != 0) {
ASSERT_OK(iter->GetNextRow(&row));
i++;
}
EXPECT_EQ(i, 2);
// Manually terminate the pipeline
iter->Stop();
// Stop MindData Profiling and save output files to current working directory
EXPECT_OK(profiler_manager->Stop());
EXPECT_FALSE(profiler_manager->IsProfilingEnable());
EXPECT_OK(profiler_manager->Save("."));
// File_id is expected to equal RANK_ID
EXPECT_OK(DeleteFiles(1));
}
/// Feature: MindData Profiling Support
/// Description: Test MindData Profiling with profiling enabled for pipeline with Mnist
/// Expectation: Profiling files are created.
TEST_F(MindDataTestProfiler, TestProfilerManager2) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestProfilerManager2.";
// Enable profiler and check
common::SetEnv("RANK_ID", "2");
std::shared_ptr<ProfilingManager> profiler_manager = GlobalContext::profiling_manager();
EXPECT_OK(profiler_manager->Init());
EXPECT_OK(profiler_manager->Start());
EXPECT_TRUE(profiler_manager->IsProfilingEnable());
// Create a Mnist Dataset
std::string folder_path = datasets_root_path_ + "/testMnistData/";
std::shared_ptr<Dataset> ds = Mnist(folder_path, "all", std::make_shared<SequentialSampler>(0, 3));
EXPECT_NE(ds, nullptr);
ds = ds->Skip(1);
EXPECT_NE(ds, nullptr);
ds = ds->Repeat(2);
EXPECT_NE(ds, nullptr);
ds = ds->Batch(2, false);
EXPECT_NE(ds, nullptr);
// No columns are specified, use all columns
std::shared_ptr<Iterator> iter = ds->CreateIterator();
EXPECT_NE(iter, nullptr);
// Iterate the dataset and get each row
std::vector<mindspore::MSTensor> row;
ASSERT_OK(iter->GetNextRow(&row));
uint64_t i = 0;
while (row.size() != 0) {
ASSERT_OK(iter->GetNextRow(&row));
i++;
}
EXPECT_EQ(i, 2);
// Manually terminate the pipeline
iter->Stop();
// Stop MindData Profiling and save output files to current working directory
EXPECT_OK(profiler_manager->Stop());
EXPECT_FALSE(profiler_manager->IsProfilingEnable());
EXPECT_OK(profiler_manager->Save("."));
// File_id is expected to equal RANK_ID
EXPECT_OK(DeleteFiles(2));
}
} // namespace test
} // namespace dataset
} // namespace mindspore