!28055 Test Profiler on C++ UT
Merge pull request !28055 from zetongzhao/profiler_test
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f25d230d57
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@ -13,6 +13,8 @@
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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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*/
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#include <chrono>
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#include <thread>
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#include "common/common.h"
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#include "minddata/dataset/engine/perf/profiling.h"
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#include "minddata/dataset/include/dataset/datasets.h"
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@ -39,6 +41,37 @@ class MindDataTestProfiler : public UT::DatasetOpTesting {
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RETURN_STATUS_UNEXPECTED("Error deleting profiler files");
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}
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}
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std::shared_ptr<Dataset> set_dataset(int32_t op_input) {
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std::string folder_path = datasets_root_path_ + "/testPK/data/";
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int64_t num_samples = 2;
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std::shared_ptr<Dataset> ds = ImageFolder(folder_path, true, std::make_shared<SequentialSampler>(0, num_samples));
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EXPECT_NE(ds, nullptr);
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ds = ds->Repeat(op_input);
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EXPECT_NE(ds, nullptr);
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ds = ds->Shuffle(op_input);
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EXPECT_NE(ds, nullptr);
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// Create objects for the tensor ops
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std::shared_ptr<TensorTransform> one_hot = std::make_shared<transforms::OneHot>(op_input);
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EXPECT_NE(one_hot, nullptr);
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// Create a Map operation, this will automatically add a project after map
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ds = ds->Map({one_hot}, {"label"}, {"label"}, {"label"});
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EXPECT_NE(ds, nullptr);
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ds = ds->Take(op_input);
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EXPECT_NE(ds, nullptr);
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ds = ds->Batch(op_input, true);
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EXPECT_NE(ds, nullptr);
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ds = ds->Repeat(op_input);
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EXPECT_NE(ds, nullptr);
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return ds;
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}
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};
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/// Feature: MindData Profiling Support
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@ -156,6 +189,266 @@ TEST_F(MindDataTestProfiler, TestProfilerManager2) {
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// File_id is expected to equal RANK_ID
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EXPECT_OK(DeleteFiles(2));
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}
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/// Feature: MindData Profiling Support
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/// Description: Test MindData Profiling GetByEpoch Methods
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/// Expectation: Results are successfully outputted.
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TEST_F(MindDataTestProfiler, TestProfilerManagerByEpoch) {
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MS_LOG(INFO) << "Doing MindDataTestPipeline-TestProfilerManagerByEpoch.";
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// Enable profiler and check
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common::SetEnv("RANK_ID", "2");
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GlobalContext::config_manager()->set_monitor_sampling_interval(100);
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std::shared_ptr<ProfilingManager> profiler_manager = GlobalContext::profiling_manager();
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EXPECT_OK(profiler_manager->Init());
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EXPECT_OK(profiler_manager->Start());
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EXPECT_TRUE(profiler_manager->IsProfilingEnable());
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std::shared_ptr<Dataset> ds = set_dataset(2);
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// No columns are specified, use all columns
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std::vector<std::string> columns = {};
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std::shared_ptr<Iterator> iter = ds->CreateIterator(columns, 3);
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EXPECT_NE(iter, nullptr);
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std::vector<uint8_t> cpu_result;
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std::vector<uint16_t> op_result;
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std::vector<int32_t> connector_result;
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std::vector<int32_t> time_result;
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float_t queue_result;
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// Note: These Get* calls fail since epoch number cannot be 0.
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EXPECT_ERROR(profiler_manager->GetUserCpuUtilByEpoch(0, &cpu_result));
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EXPECT_ERROR(profiler_manager->GetBatchTimeByEpoch(0, &time_result));
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std::vector<mindspore::MSTensor> row;
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for (int i = 0; i < 3; i++) {
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// Iterate the dataset and get each row
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ASSERT_OK(iter->GetNextRow(&row));
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while (row.size() != 0) {
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ASSERT_OK(iter->GetNextRow(&row));
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}
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}
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// Check iteration failure after finishing the num_epochs
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EXPECT_ERROR(iter->GetNextRow(&row));
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// Manually terminate the pipeline
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iter->Stop();
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for (int i = 1; i < 4; i++) {
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ASSERT_OK(profiler_manager->GetUserCpuUtilByEpoch(i, &cpu_result));
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ASSERT_OK(profiler_manager->GetUserCpuUtilByEpoch(i - 1, i, &op_result));
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ASSERT_OK(profiler_manager->GetSysCpuUtilByEpoch(i, &cpu_result));
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ASSERT_OK(profiler_manager->GetSysCpuUtilByEpoch(i - 1, i, &op_result));
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// Epoch is 1 for each iteration and 2 steps for each epoch, so the output size are expected to be 2
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ASSERT_OK(profiler_manager->GetBatchTimeByEpoch(i, &time_result));
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EXPECT_EQ(time_result.size(), 2);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetPipelineTimeByEpoch(i, &time_result));
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EXPECT_EQ(time_result.size(), 2);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetPushTimeByEpoch(i, &time_result));
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EXPECT_EQ(time_result.size(), 2);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorSizeByEpoch(i, &connector_result));
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EXPECT_EQ(connector_result.size(), 2);
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorCapacityByEpoch(i, &connector_result));
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EXPECT_EQ(connector_result.size(), 2);
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorSizeByEpoch(i - 1, i, &connector_result));
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EXPECT_GT(connector_result.size(), 0); // Connector size is expected to be greater than 0
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetEmptyQueueFrequencyByEpoch(i, &queue_result));
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EXPECT_GE(queue_result, 0);
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EXPECT_LE(queue_result, 1);
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}
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ASSERT_ERROR(profiler_manager->GetUserCpuUtilByEpoch(4, &cpu_result)); // Check there is no epoch 4
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int num = profiler_manager->GetNumOfProfiledEpochs();
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EXPECT_EQ(num, 3);
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// Stop MindData Profiling and save output files to current working directory
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EXPECT_OK(profiler_manager->Stop());
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EXPECT_FALSE(profiler_manager->IsProfilingEnable());
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EXPECT_OK(profiler_manager->Save("."));
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// File_id is expected to equal RANK_ID
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EXPECT_OK(DeleteFiles(2));
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}
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/// Feature: MindData Profiling Support
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/// Description: Test MindData Profiling GetByStep Methods
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/// Expectation: Results are successfully outputted.
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TEST_F(MindDataTestProfiler, TestProfilerManagerByStep) {
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MS_LOG(INFO) << "Doing MindDataTestPipeline-TestProfilerManagerByStep.";
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// Enable profiler and check
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common::SetEnv("RANK_ID", "2");
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GlobalContext::config_manager()->set_monitor_sampling_interval(100);
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std::shared_ptr<ProfilingManager> profiler_manager = GlobalContext::profiling_manager();
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EXPECT_OK(profiler_manager->Init());
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EXPECT_OK(profiler_manager->Start());
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EXPECT_TRUE(profiler_manager->IsProfilingEnable());
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std::shared_ptr<Dataset> ds = set_dataset(10);
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// No columns are specified, use all columns
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std::vector<std::string> columns = {};
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std::shared_ptr<Iterator> iter = ds->CreateIterator(columns, 3);
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EXPECT_NE(iter, nullptr);
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std::vector<uint8_t> cpu_result;
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std::vector<uint16_t> op_result;
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std::vector<int32_t> connector_result;
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std::vector<int32_t> time_result;
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float_t queue_result;
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uint64_t i = 0;
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ASSERT_ERROR(
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profiler_manager->GetUserCpuUtilByStep(i, i, &cpu_result)); // Fail in TimeIntervalForStepRange for start_step = 0
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ASSERT_ERROR(profiler_manager->GetBatchTimeByStep(
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i, i + 2, &time_result)); // Fail in GetRecordEntryFieldValue for end_step > total_steps
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ASSERT_ERROR(profiler_manager->GetPipelineTimeByStep(
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i + 2, i, &time_result)); // Fail in GetRecordEntryFieldValue for start_step > total_steps
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ASSERT_ERROR(profiler_manager->GetPushTimeByStep(
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i + 1, i, &time_result)); // Fail in GetRecordEntryFieldValue for start_step > end_steps
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std::vector<mindspore::MSTensor> row;
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for (int i = 0; i < 3; i++) {
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// Iterate the dataset and get each row
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ASSERT_OK(iter->GetNextRow(&row));
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while (row.size() != 0) {
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ASSERT_OK(iter->GetNextRow(&row));
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}
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}
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// Manually terminate the pipeline
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iter->Stop();
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// There are 3 epochs and 3 samplers for each epoch, 3x3=9 steps in total
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for (int i = 1; i < 10; i++) {
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ASSERT_OK(profiler_manager->GetUserCpuUtilByStep(i, i, &cpu_result));
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ASSERT_OK(profiler_manager->GetUserCpuUtilByStep(i - 1, i, i, &op_result));
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ASSERT_OK(profiler_manager->GetSysCpuUtilByStep(i, i, &cpu_result));
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ASSERT_OK(profiler_manager->GetSysCpuUtilByStep(i - 1, i, i, &op_result));
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// Step is 1 for each iteration, so the output size is expected to be 1
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ASSERT_OK(profiler_manager->GetBatchTimeByStep(i, i, &time_result));
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EXPECT_EQ(time_result.size(), 1);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetPipelineTimeByStep(i, i, &time_result));
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EXPECT_EQ(time_result.size(), 1);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetPushTimeByStep(i, i, &time_result));
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EXPECT_EQ(time_result.size(), 1);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorSizeByStep(i, i, &connector_result));
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EXPECT_EQ(connector_result.size(), 1);
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorCapacityByStep(i, i, &connector_result));
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EXPECT_EQ(connector_result.size(), 1);
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorSizeByStep(i - 1, i, i, &connector_result));
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EXPECT_GE(connector_result.size(), 0); // Connector size is expected to be greater than 0
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetEmptyQueueFrequencyByStep(i, i, &queue_result));
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EXPECT_GE(queue_result, 0);
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EXPECT_LE(queue_result, 1);
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ASSERT_OK(
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profiler_manager->GetEmptyQueueFrequencyByStep(i - 1, i, &queue_result)); // Check when start_step < end_step
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}
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ASSERT_ERROR(profiler_manager->GetUserCpuUtilByStep(10, 9, 9, &op_result)); // Check there is no op_id=10
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int num = profiler_manager->GetNumOfProfiledEpochs();
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EXPECT_EQ(num, 3);
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// Stop MindData Profiling and save output files to current working directory
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EXPECT_OK(profiler_manager->Stop());
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EXPECT_FALSE(profiler_manager->IsProfilingEnable());
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EXPECT_OK(profiler_manager->Save("."));
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// File_id is expected to equal RANK_ID
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EXPECT_OK(DeleteFiles(2));
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}
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/// Feature: MindData Profiling Support
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/// Description: Test MindData Profiling GetByTime Methods
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/// Expectation: Results are successfully outputted.
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TEST_F(MindDataTestProfiler, TestProfilerManagerByTime) {
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MS_LOG(INFO) << "Doing MindDataTestPipeline-TestProfilerManagerByTime.";
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// Enable profiler and check
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common::SetEnv("RANK_ID", "2");
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GlobalContext::config_manager()->set_monitor_sampling_interval(100);
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std::shared_ptr<ProfilingManager> profiler_manager = GlobalContext::profiling_manager();
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EXPECT_OK(profiler_manager->Init());
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EXPECT_OK(profiler_manager->Start());
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EXPECT_TRUE(profiler_manager->IsProfilingEnable());
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std::shared_ptr<Dataset> ds = set_dataset(5);
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// No columns are specified, use all columns
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std::vector<std::string> columns = {};
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std::shared_ptr<Iterator> iter = ds->CreateIterator(columns, 5);
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EXPECT_NE(iter, nullptr);
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std::vector<uint8_t> cpu_result;
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std::vector<uint16_t> op_result;
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std::vector<int32_t> connector_result;
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std::vector<int32_t> time_result;
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float_t queue_result;
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std::vector<uint64_t> ts = {};
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std::vector<mindspore::MSTensor> row;
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for (int i = 0; i < 5; i++) {
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ts.push_back(ProfilingTime::GetCurMilliSecond());
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// Iterate the dataset and get each row
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ASSERT_OK(iter->GetNextRow(&row));
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while (row.size() != 0) {
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ASSERT_OK(iter->GetNextRow(&row));
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}
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}
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ts.push_back(ProfilingTime::GetCurMilliSecond());
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// Manually terminate the pipeline
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iter->Stop();
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for (int i = 1; i < 6; i++) {
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uint64_t start_ts = ts[i - 1];
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uint64_t end_ts = ts[i];
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ASSERT_OK(profiler_manager->GetUserCpuUtilByTime(start_ts, end_ts, &cpu_result));
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ASSERT_OK(profiler_manager->GetUserCpuUtilByTime(i - 1, start_ts, end_ts, &op_result));
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ASSERT_OK(profiler_manager->GetSysCpuUtilByTime(start_ts, end_ts, &cpu_result));
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ASSERT_OK(profiler_manager->GetSysCpuUtilByTime(i - 1, start_ts, end_ts, &op_result));
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ASSERT_OK(profiler_manager->GetBatchTimeByTime(start_ts, end_ts, &time_result));
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EXPECT_GT(time_result.size(), 0);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetPipelineTimeByTime(start_ts, end_ts, &time_result));
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EXPECT_GT(time_result.size(), 0);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetPushTimeByTime(start_ts, end_ts, &time_result));
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EXPECT_GT(time_result.size(), 0);
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time_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorSizeByTime(start_ts, end_ts, &connector_result));
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EXPECT_GT(connector_result.size(), 0);
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorCapacityByTime(start_ts, end_ts, &connector_result));
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EXPECT_GT(connector_result.size(), 0);
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetConnectorSizeByTime(i - 1, start_ts, end_ts, &connector_result));
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EXPECT_GT(connector_result.size(), 0); // Connector size is expected to be greater than 0
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connector_result.clear();
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ASSERT_OK(profiler_manager->GetEmptyQueueFrequencyByTime(start_ts, end_ts, &queue_result));
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EXPECT_GE(queue_result, 0);
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EXPECT_LE(queue_result, 1);
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}
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int num = profiler_manager->GetNumOfProfiledEpochs();
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EXPECT_EQ(num, 5);
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// Stop MindData Profiling and save output files to current working directory
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EXPECT_OK(profiler_manager->Stop());
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EXPECT_FALSE(profiler_manager->IsProfilingEnable());
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EXPECT_OK(profiler_manager->Save("."));
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// File_id is expected to equal RANK_ID
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EXPECT_OK(DeleteFiles(2));
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}
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} // namespace test
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} // namespace dataset
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} // namespace mindspore
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