from unittest import mock import os import pytest import tempfile import unittest import time from mlagents.trainers.stats import ( StatsReporter, TensorboardWriter, StatsSummary, GaugeWriter, ConsoleWriter, StatsPropertyType, StatsAggregationMethod, ) def test_stat_reporter_add_summary_write(): # Test add_writer StatsReporter.writers.clear() mock_writer1 = mock.Mock() mock_writer2 = mock.Mock() StatsReporter.add_writer(mock_writer1) StatsReporter.add_writer(mock_writer2) assert len(StatsReporter.writers) == 2 # Test add_stats and summaries statsreporter1 = StatsReporter("category1") statsreporter2 = StatsReporter("category2") for i in range(10): statsreporter1.add_stat("key1", float(i)) statsreporter2.add_stat("key2", float(i)) statssummary1 = statsreporter1.get_stats_summaries("key1") statssummary2 = statsreporter2.get_stats_summaries("key2") assert statssummary1.num == 10 assert statssummary2.num == 10 assert statssummary1.mean == 4.5 assert statssummary2.mean == 4.5 assert statssummary1.std == pytest.approx(2.9, abs=0.1) assert statssummary2.std == pytest.approx(2.9, abs=0.1) # Test write_stats step = 10 statsreporter1.write_stats(step) mock_writer1.write_stats.assert_called_once_with( "category1", {"key1": statssummary1}, step ) mock_writer2.write_stats.assert_called_once_with( "category1", {"key1": statssummary1}, step ) def test_stat_reporter_property(): # Test add_writer mock_writer = mock.Mock() StatsReporter.writers.clear() StatsReporter.add_writer(mock_writer) assert len(StatsReporter.writers) == 1 statsreporter1 = StatsReporter("category1") # Test add_property statsreporter1.add_property("key", "this is a text") mock_writer.add_property.assert_called_once_with( "category1", "key", "this is a text" ) @mock.patch("mlagents.trainers.stats.SummaryWriter") def test_tensorboard_writer(mock_summary): # Test write_stats category = "category1" with tempfile.TemporaryDirectory(prefix="unittest-") as base_dir: tb_writer = TensorboardWriter(base_dir, clear_past_data=False) statssummary1 = StatsSummary( full_dist=[1.0], aggregation_method=StatsAggregationMethod.AVERAGE ) tb_writer.write_stats("category1", {"key1": statssummary1}, 10) # Test that the filewriter has been created and the directory has been created. filewriter_dir = "{basedir}/{category}".format( basedir=base_dir, category=category ) assert os.path.exists(filewriter_dir) mock_summary.assert_called_once_with(filewriter_dir) # Test that the filewriter was written to and the summary was added. mock_summary.return_value.add_scalar.assert_called_once_with("key1", 1.0, 10) mock_summary.return_value.flush.assert_called_once() # Test hyperparameter writing - no good way to parse the TB string though. tb_writer.add_property( "category1", StatsPropertyType.HYPERPARAMETERS, {"example": 1.0} ) assert mock_summary.return_value.add_text.call_count >= 1 def test_tensorboard_writer_clear(tmp_path): tb_writer = TensorboardWriter(tmp_path, clear_past_data=False) statssummary1 = StatsSummary( full_dist=[1.0], aggregation_method=StatsAggregationMethod.AVERAGE ) tb_writer.write_stats("category1", {"key1": statssummary1}, 10) # TB has some sort of timeout before making a new file time.sleep(1.0) assert len(os.listdir(os.path.join(tmp_path, "category1"))) > 0 # See if creating a new one doesn't delete it tb_writer = TensorboardWriter(tmp_path, clear_past_data=False) tb_writer.write_stats("category1", {"key1": statssummary1}, 10) assert len(os.listdir(os.path.join(tmp_path, "category1"))) > 1 time.sleep(1.0) # See if creating a new one deletes old ones tb_writer = TensorboardWriter(tmp_path, clear_past_data=True) tb_writer.write_stats("category1", {"key1": statssummary1}, 10) assert len(os.listdir(os.path.join(tmp_path, "category1"))) == 1 def test_gauge_stat_writer_sanitize(): assert GaugeWriter.sanitize_string("Policy/Learning Rate") == "Policy.LearningRate" assert ( GaugeWriter.sanitize_string("Very/Very/Very Nested Stat") == "Very.Very.VeryNestedStat" ) class ConsoleWriterTest(unittest.TestCase): def test_console_writer(self): # Test write_stats with self.assertLogs("mlagents.trainers", level="INFO") as cm: category = "category1" console_writer = ConsoleWriter() statssummary1 = StatsSummary( full_dist=[1.0], aggregation_method=StatsAggregationMethod.AVERAGE ) console_writer.write_stats( category, { "Environment/Cumulative Reward": statssummary1, "Is Training": statssummary1, }, 10, ) statssummary2 = StatsSummary( full_dist=[0.0], aggregation_method=StatsAggregationMethod.AVERAGE ) console_writer.write_stats( category, { "Environment/Cumulative Reward": statssummary2, "Is Training": statssummary2, }, 10, ) # Test hyperparameter writing console_writer.add_property( "category1", StatsPropertyType.HYPERPARAMETERS, {"example": 1.0} ) self.assertIn( "Mean Reward: 1.000. Std of Reward: 0.000. Training.", cm.output[0] ) self.assertIn("Not Training.", cm.output[1]) self.assertIn("Hyperparameters for behavior name", cm.output[2]) self.assertIn("example:\t1.0", cm.output[2]) def test_selfplay_console_writer(self): with self.assertLogs("mlagents.trainers", level="INFO") as cm: category = "category1" console_writer = ConsoleWriter() console_writer.add_property(category, StatsPropertyType.SELF_PLAY, True) statssummary1 = StatsSummary( full_dist=[1.0], aggregation_method=StatsAggregationMethod.AVERAGE ) console_writer.write_stats( category, { "Environment/Cumulative Reward": statssummary1, "Is Training": statssummary1, "Self-play/ELO": statssummary1, }, 10, ) self.assertIn( "Mean Reward: 1.000. Std of Reward: 0.000. Training.", cm.output[0] )