def test_make_output(_format):
"""
test make output
:param _format: (str) output format
"""
writer = make_output_format(_format, LOG_DIR)
writer.writekvs(KEY_VALUES)
if _format == "csv":
read_csv(LOG_DIR + 'progress.csv')
elif _format == 'json':
read_json(LOG_DIR + 'progress.json')
writer.close()
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
def test_make_output(tmp_path, _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)
if _format == "csv":
read_csv(tmp_path / 'progress.csv')
elif _format == 'json':
read_json(tmp_path / 'progress.json')
writer.close()
