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