# Copyright The PyTorch Lightning team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from argparse import Namespace import pytest import torch 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])