96 lines
3.6 KiB
Python
96 lines
3.6 KiB
Python
from unittest.mock import patch, MagicMock
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import torch
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from pytorch_lightning import Trainer
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from pytorch_lightning.loggers import NeptuneLogger
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from tests.base import EvalModelTemplate
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@patch('pytorch_lightning.loggers.neptune.neptune')
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def test_neptune_online(neptune):
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logger = NeptuneLogger(api_key='test', project_name='project')
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created_experiment = neptune.Session.with_default_backend().get_project().create_experiment()
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# It's important to check if the internal variable _experiment was initialized in __init__.
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# Calling logger.experiment would cause a side-effect of initializing _experiment,
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# if it wasn't already initialized.
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assert logger._experiment == created_experiment
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assert logger.name == created_experiment.name
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assert logger.version == created_experiment.id
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@patch('pytorch_lightning.loggers.neptune.neptune')
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def test_neptune_offline(neptune):
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logger = NeptuneLogger(offline_mode=True)
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neptune.Session.assert_called_once_with(backend=neptune.OfflineBackend())
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assert logger.experiment == neptune.Session().get_project().create_experiment()
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@patch('pytorch_lightning.loggers.neptune.neptune')
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def test_neptune_additional_methods(neptune):
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logger = NeptuneLogger(api_key='test', project_name='project')
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created_experiment = neptune.Session.with_default_backend().get_project().create_experiment()
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logger.log_metric('test', torch.ones(1))
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created_experiment.log_metric.assert_called_once_with('test', torch.ones(1))
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created_experiment.log_metric.reset_mock()
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logger.log_metric('test', 1.0)
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created_experiment.log_metric.assert_called_once_with('test', 1.0)
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created_experiment.log_metric.reset_mock()
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logger.log_metric('test', 1.0, step=2)
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created_experiment.log_metric.assert_called_once_with('test', x=2, y=1.0)
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created_experiment.log_metric.reset_mock()
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logger.log_text('test', 'text')
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created_experiment.log_metric.assert_called_once_with('test', 'text')
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created_experiment.log_metric.reset_mock()
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logger.log_image('test', 'image file')
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created_experiment.log_image.assert_called_once_with('test', 'image file')
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created_experiment.log_image.reset_mock()
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logger.log_image('test', 'image file', step=2)
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created_experiment.log_image.assert_called_once_with('test', x=2, y='image file')
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created_experiment.log_image.reset_mock()
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logger.log_artifact('file')
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created_experiment.log_artifact.assert_called_once_with('file', None)
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logger.set_property('property', 10)
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created_experiment.set_property.assert_called_once_with('property', 10)
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logger.append_tags('one tag')
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created_experiment.append_tags.assert_called_once_with('one tag')
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created_experiment.append_tags.reset_mock()
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logger.append_tags(['two', 'tags'])
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created_experiment.append_tags.assert_called_once_with('two', 'tags')
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def test_neptune_leave_open_experiment_after_fit(tmpdir):
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"""Verify that neptune experiment was closed after training"""
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model = EvalModelTemplate()
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def _run_training(logger):
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logger._experiment = MagicMock()
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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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limit_train_batches=0.05,
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logger=logger,
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)
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trainer.fit(model)
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return logger
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logger_close_after_fit = _run_training(NeptuneLogger(offline_mode=True))
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assert logger_close_after_fit._experiment.stop.call_count == 1
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logger_open_after_fit = _run_training(NeptuneLogger(offline_mode=True, close_after_fit=False))
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assert logger_open_after_fit._experiment.stop.call_count == 0
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