99 lines
3.2 KiB
Python
99 lines
3.2 KiB
Python
import os
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import pickle
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from unittest import mock
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from pytorch_lightning import Trainer
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from pytorch_lightning.loggers import WandbLogger
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from tests.base import EvalModelTemplate
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@mock.patch('pytorch_lightning.loggers.wandb.wandb')
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def test_wandb_logger(wandb):
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"""Verify that basic functionality of wandb logger works.
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Wandb doesn't work well with pytest so we have to mock it out here."""
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logger = WandbLogger(anonymous=True, offline=True)
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logger.log_metrics({'acc': 1.0})
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wandb.init().log.assert_called_once_with({'acc': 1.0})
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wandb.init().log.reset_mock()
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logger.log_metrics({'acc': 1.0}, step=3)
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wandb.init().log.assert_called_once_with({'global_step': 3, 'acc': 1.0})
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logger.log_hyperparams({'test': None, 'nested': {'a': 1}, 'b': [2, 3, 4]})
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wandb.init().config.update.assert_called_once_with(
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{'test': 'None', 'nested/a': 1, 'b': [2, 3, 4]},
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allow_val_change=True,
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)
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logger.watch('model', 'log', 10)
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wandb.init().watch.assert_called_once_with('model', log='log', log_freq=10)
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assert logger.name == wandb.init().project_name()
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assert logger.version == wandb.init().id
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@mock.patch('pytorch_lightning.loggers.wandb.wandb')
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def test_wandb_pickle(wandb, tmpdir):
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"""
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Verify that pickling trainer with wandb logger works.
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Wandb doesn't work well with pytest so we have to mock it out here.
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"""
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class Experiment:
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""" """
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id = 'the_id'
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def project_name(self):
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return 'the_project_name'
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wandb.init.return_value = Experiment()
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logger = WandbLogger(id='the_id', offline=True)
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trainer = Trainer(
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default_root_dir=tmpdir,
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max_epochs=1,
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logger=logger,
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)
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# Access the experiment to ensure it's created
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assert trainer.logger.experiment, 'missing experiment'
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pkl_bytes = pickle.dumps(trainer)
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trainer2 = pickle.loads(pkl_bytes)
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assert os.environ['WANDB_MODE'] == 'dryrun'
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assert trainer2.logger.__class__.__name__ == WandbLogger.__name__
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assert trainer2.logger.experiment, 'missing experiment'
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wandb.init.assert_called()
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assert 'id' in wandb.init.call_args[1]
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assert wandb.init.call_args[1]['id'] == 'the_id'
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del os.environ['WANDB_MODE']
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@mock.patch('pytorch_lightning.loggers.wandb.wandb')
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def test_wandb_logger_dirs_creation(wandb, tmpdir):
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""" Test that the logger creates the folders and files in the right place. """
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logger = WandbLogger(save_dir=str(tmpdir), offline=True)
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assert logger.version is None
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assert logger.name is None
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# mock return values of experiment
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logger.experiment.id = '1'
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logger.experiment.project_name.return_value = 'project'
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for _ in range(2):
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_ = logger.experiment
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assert logger.version == '1'
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assert logger.name == 'project'
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assert str(tmpdir) == logger.save_dir
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assert not os.listdir(tmpdir)
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version = logger.version
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model = EvalModelTemplate()
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trainer = Trainer(default_root_dir=tmpdir, logger=logger, max_epochs=1, limit_val_batches=3)
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trainer.fit(model)
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assert trainer.checkpoint_callback.dirpath == str(tmpdir / 'project' / version / 'checkpoints')
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assert set(os.listdir(trainer.checkpoint_callback.dirpath)) == {'epoch=0.ckpt'}
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