lightning/tests/loggers/test_csv.py

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from argparse import Namespace
import pytest
import torch
import os
from pytorch_lightning.core.saving import load_hparams_from_yaml
from pytorch_lightning.loggers import CSVLogger
from pytorch_lightning.loggers.csv_logs import ExperimentWriter
def test_file_logger_automatic_versioning(tmpdir):
"""Verify that automatic versioning works"""
root_dir = tmpdir.mkdir("exp")
root_dir.mkdir("version_0")
root_dir.mkdir("version_1")
logger = CSVLogger(save_dir=tmpdir, name="exp")
assert logger.version == 2
def test_file_logger_manual_versioning(tmpdir):
"""Verify that manual versioning works"""
root_dir = tmpdir.mkdir("exp")
root_dir.mkdir("version_0")
root_dir.mkdir("version_1")
root_dir.mkdir("version_2")
logger = CSVLogger(save_dir=tmpdir, name="exp", version=1)
assert logger.version == 1
def test_file_logger_named_version(tmpdir):
"""Verify that manual versioning works for string versions, e.g. '2020-02-05-162402' """
exp_name = "exp"
tmpdir.mkdir(exp_name)
expected_version = "2020-02-05-162402"
logger = CSVLogger(save_dir=tmpdir, name=exp_name, version=expected_version)
logger.log_hyperparams({"a": 1, "b": 2})
logger.save()
assert logger.version == expected_version
assert os.listdir(tmpdir / exp_name) == [expected_version]
assert os.listdir(tmpdir / exp_name / expected_version)
@pytest.mark.parametrize("name", ['', None])
def test_file_logger_no_name(tmpdir, name):
"""Verify that None or empty name works"""
logger = CSVLogger(save_dir=tmpdir, name=name)
logger.save()
assert logger.root_dir == tmpdir
assert os.listdir(tmpdir / 'version_0')
@pytest.mark.parametrize("step_idx", [10, None])
def test_file_logger_log_metrics(tmpdir, step_idx):
logger = CSVLogger(tmpdir)
metrics = {
"float": 0.3,
"int": 1,
"FloatTensor": torch.tensor(0.1),
"IntTensor": torch.tensor(1)
}
logger.log_metrics(metrics, step_idx)
logger.save()
path_csv = os.path.join(logger.log_dir, ExperimentWriter.NAME_METRICS_FILE)
with open(path_csv, 'r') as fp:
lines = fp.readlines()
assert len(lines) == 2
assert all([n in lines[0] for n in metrics])
def test_file_logger_log_hyperparams(tmpdir):
logger = CSVLogger(tmpdir)
hparams = {
"float": 0.3,
"int": 1,
"string": "abc",
"bool": True,
"dict": {'a': {'b': 'c'}},
"list": [1, 2, 3],
"namespace": Namespace(foo=Namespace(bar='buzz')),
"layer": torch.nn.BatchNorm1d
}
logger.log_hyperparams(hparams)
logger.save()
path_yaml = os.path.join(logger.log_dir, ExperimentWriter.NAME_HPARAMS_FILE)
params = load_hparams_from_yaml(path_yaml)
assert all([n in params for n in hparams])