File size: 5,542 Bytes
a89d35f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 | from typing import Sequence
import numpy as np
import pytest
import torch as th
from pandas.errors import EmptyDataError
from stable_baselines3.common.logger import (
DEBUG,
FormatUnsupportedError,
ScopedConfigure,
Video,
configure,
debug,
dump,
error,
info,
make_output_format,
read_csv,
read_json,
record,
record_dict,
record_mean,
reset,
set_level,
warn,
)
KEY_VALUES = {
"test": 1,
"b": -3.14,
"8": 9.9,
"l": [1, 2],
"a": np.array([1, 2, 3]),
"f": np.array(1),
"g": np.array([[[1]]]),
}
KEY_EXCLUDED = {}
for key in KEY_VALUES.keys():
KEY_EXCLUDED[key] = None
class LogContent:
"""
A simple wrapper class to provide a common interface to check content for emptiness and report the log format
"""
def __init__(self, _format: str, lines: Sequence):
self.format = _format
self.lines = lines
@property
def empty(self):
return len(self.lines) == 0
def __repr__(self):
return f"LogContent(_format={self.format}, lines={self.lines})"
@pytest.fixture
def read_log(tmp_path, capsys):
def read_fn(_format):
if _format == "csv":
try:
df = read_csv(tmp_path / "progress.csv")
except EmptyDataError:
return LogContent(_format, [])
return LogContent(_format, [r for _, r in df.iterrows() if not r.empty])
elif _format == "json":
try:
df = read_json(tmp_path / "progress.json")
except EmptyDataError:
return LogContent(_format, [])
return LogContent(_format, [r for _, r in df.iterrows() if not r.empty])
elif _format == "stdout":
captured = capsys.readouterr()
return LogContent(_format, captured.out.splitlines())
elif _format == "log":
return LogContent(_format, (tmp_path / "log.txt").read_text().splitlines())
elif _format == "tensorboard":
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
acc = EventAccumulator(str(tmp_path))
acc.Reload()
tb_values_logged = []
for reservoir in [acc.scalars, acc.tensors, acc.images, acc.histograms, acc.compressed_histograms]:
for k in reservoir.Keys():
tb_values_logged.append(f"{k}: {str(reservoir.Items(k))}")
content = LogContent(_format, tb_values_logged)
return content
return read_fn
def test_main(tmp_path):
"""
tests for the logger module
"""
info("hi")
debug("shouldn't appear")
set_level(DEBUG)
debug("should appear")
configure(folder=str(tmp_path))
record("a", 3)
record("b", 2.5)
dump()
record("b", -2.5)
record("a", 5.5)
dump()
info("^^^ should see a = 5.5")
record_mean("b", -22.5)
record_mean("b", -44.4)
record("a", 5.5)
dump()
with ScopedConfigure(None, None):
info("^^^ should see b = 33.3")
with ScopedConfigure(str(tmp_path / "test-logger"), ["json"]):
record("b", -2.5)
dump()
reset()
record("a", "longasslongasslongasslongasslongasslongassvalue")
dump()
warn("hey")
error("oh")
record_dict({"test": 1})
@pytest.mark.parametrize("_format", ["stdout", "log", "json", "csv", "tensorboard"])
def test_make_output(tmp_path, read_log, _format):
"""
test make output
:param _format: (str) output format
"""
if _format == "tensorboard":
# Skip if no tensorboard installed
pytest.importorskip("tensorboard")
writer = make_output_format(_format, tmp_path)
writer.write(KEY_VALUES, KEY_EXCLUDED)
assert not read_log(_format).empty
writer.close()
def test_make_output_fail(tmp_path):
"""
test value error on logger
"""
with pytest.raises(ValueError):
make_output_format("dummy_format", tmp_path)
@pytest.mark.parametrize("_format", ["stdout", "log", "json", "csv", "tensorboard"])
def test_exclude_keys(tmp_path, read_log, _format):
if _format == "tensorboard":
# Skip if no tensorboard installed
pytest.importorskip("tensorboard")
writer = make_output_format(_format, tmp_path)
writer.write(dict(some_tag=42), key_excluded=dict(some_tag=(_format)))
writer.close()
assert read_log(_format).empty
def test_report_video_to_tensorboard(tmp_path, read_log, capsys):
pytest.importorskip("tensorboard")
video = Video(frames=th.rand(1, 20, 3, 16, 16), fps=20)
writer = make_output_format("tensorboard", tmp_path)
writer.write({"video": video}, key_excluded={"video": ()})
if is_moviepy_installed():
assert not read_log("tensorboard").empty
else:
assert "moviepy" in capsys.readouterr().out
writer.close()
def is_moviepy_installed():
try:
import moviepy # noqa: F401
except ModuleNotFoundError:
return False
return True
@pytest.mark.parametrize("unsupported_format", ["stdout", "log", "json", "csv"])
def test_report_video_to_unsupported_format_raises_error(tmp_path, unsupported_format):
writer = make_output_format(unsupported_format, tmp_path)
with pytest.raises(FormatUnsupportedError) as exec_info:
video = Video(frames=th.rand(1, 20, 3, 16, 16), fps=20)
writer.write({"video": video}, key_excluded={"video": ()})
assert unsupported_format in str(exec_info.value)
writer.close()
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