184 lines
6.2 KiB
Python
184 lines
6.2 KiB
Python
import tests.base.utils as tutils
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from pytorch_lightning import Callback
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from pytorch_lightning import Trainer, LightningModule
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from pytorch_lightning.callbacks import EarlyStopping
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from tests.base import (
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LightTrainDataloader,
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LightTestMixin,
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LightValidationMixin,
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TestModelBase
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)
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def test_trainer_callback_system(tmpdir):
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"""Test the callback system."""
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class CurrentTestModel(
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LightTrainDataloader,
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LightTestMixin,
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LightValidationMixin,
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TestModelBase,
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):
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pass
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hparams = tutils.get_default_hparams()
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model = CurrentTestModel(hparams)
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def _check_args(trainer, pl_module):
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assert isinstance(trainer, Trainer)
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assert isinstance(pl_module, LightningModule)
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class TestCallback(Callback):
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def __init__(self):
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super().__init__()
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self.on_init_start_called = False
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self.on_init_end_called = False
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self.on_epoch_start_called = False
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self.on_epoch_end_called = False
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self.on_batch_start_called = False
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self.on_batch_end_called = False
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self.on_train_start_called = False
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self.on_train_end_called = False
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self.on_validation_start_called = False
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self.on_validation_end_called = False
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self.on_test_start_called = False
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self.on_test_end_called = False
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def on_init_start(self, trainer):
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assert isinstance(trainer, Trainer)
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self.on_init_start_called = True
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def on_init_end(self, trainer):
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assert isinstance(trainer, Trainer)
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self.on_init_end_called = True
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def on_epoch_start(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_epoch_start_called = True
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def on_epoch_end(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_epoch_end_called = True
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def on_batch_start(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_batch_start_called = True
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def on_batch_end(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_batch_end_called = True
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def on_train_start(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_train_start_called = True
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def on_train_end(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_train_end_called = True
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def on_validation_start(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_validation_start_called = True
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def on_validation_end(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_validation_end_called = True
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def on_test_start(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_test_start_called = True
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def on_test_end(self, trainer, pl_module):
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_check_args(trainer, pl_module)
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self.on_test_end_called = True
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test_callback = TestCallback()
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trainer_options = {
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'callbacks': [test_callback],
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'max_epochs': 1,
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'val_percent_check': 0.1,
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'train_percent_check': 0.2,
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'progress_bar_refresh_rate': 0
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}
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assert not test_callback.on_init_start_called
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assert not test_callback.on_init_end_called
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assert not test_callback.on_epoch_start_called
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assert not test_callback.on_epoch_start_called
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assert not test_callback.on_batch_start_called
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assert not test_callback.on_batch_end_called
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assert not test_callback.on_train_start_called
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assert not test_callback.on_train_end_called
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assert not test_callback.on_validation_start_called
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assert not test_callback.on_validation_end_called
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assert not test_callback.on_test_start_called
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assert not test_callback.on_test_end_called
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# fit model
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trainer = Trainer(**trainer_options)
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assert trainer.callbacks[0] == test_callback
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assert test_callback.on_init_start_called
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assert test_callback.on_init_end_called
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assert not test_callback.on_epoch_start_called
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assert not test_callback.on_epoch_start_called
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assert not test_callback.on_batch_start_called
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assert not test_callback.on_batch_end_called
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assert not test_callback.on_train_start_called
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assert not test_callback.on_train_end_called
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assert not test_callback.on_validation_start_called
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assert not test_callback.on_validation_end_called
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assert not test_callback.on_test_start_called
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assert not test_callback.on_test_end_called
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trainer.fit(model)
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assert test_callback.on_init_start_called
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assert test_callback.on_init_end_called
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assert test_callback.on_epoch_start_called
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assert test_callback.on_epoch_start_called
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assert test_callback.on_batch_start_called
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assert test_callback.on_batch_end_called
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assert test_callback.on_train_start_called
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assert test_callback.on_train_end_called
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assert test_callback.on_validation_start_called
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assert test_callback.on_validation_end_called
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assert not test_callback.on_test_start_called
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assert not test_callback.on_test_end_called
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trainer.test()
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assert test_callback.on_test_start_called
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assert test_callback.on_test_end_called
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def test_early_stopping_without_val_step(tmpdir):
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"""Test that early stopping callback falls back to training metrics when no validation defined."""
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tutils.reset_seed()
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class ModelWithoutValStep(LightTrainDataloader, TestModelBase):
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def training_step(self, *args, **kwargs):
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output = super().training_step(*args, **kwargs)
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loss = output['loss'] # could be anything else
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output.update({'my_train_metric': loss})
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return output
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hparams = tutils.get_default_hparams()
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model = ModelWithoutValStep(hparams)
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stopping = EarlyStopping(monitor='my_train_metric', min_delta=0.1)
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trainer_options = dict(
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default_save_path=tmpdir,
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early_stop_callback=stopping,
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overfit_pct=0.20,
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max_epochs=5,
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)
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trainer = Trainer(**trainer_options)
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result = trainer.fit(model)
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assert result == 1, 'training failed to complete'
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assert trainer.current_epoch < trainer.max_epochs
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