53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
from pytorch_lightning import Trainer, Callback
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from tests.base.boring_model import BoringModel
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def test_train_step_no_return(tmpdir):
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"""
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Tests that only training_step can be used
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"""
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class CB(Callback):
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def on_train_batch_end(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx):
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d = outputs[0][0]
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assert 'minimize' in d
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def on_validation_batch_end(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx):
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assert 'x' in outputs
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def on_test_batch_end(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx):
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assert 'x' in outputs
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def on_train_epoch_end(self, trainer, pl_module, outputs):
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d = outputs[0]
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assert len(d) == trainer.num_training_batches
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class TestModel(BoringModel):
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def on_train_batch_end(self, outputs, batch, batch_idx: int, dataloader_idx: int) -> None:
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d = outputs[0][0]
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assert 'minimize' in d
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def on_validation_batch_end(self, outputs, batch, batch_idx: int, dataloader_idx: int) -> None:
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assert 'x' in outputs
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def on_test_batch_end(self, outputs, batch, batch_idx: int, dataloader_idx: int) -> None:
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assert 'x' in outputs
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def on_train_epoch_end(self, outputs) -> None:
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d = outputs[0]
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assert len(d) == self.trainer.num_training_batches
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model = TestModel()
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trainer = Trainer(
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callbacks=[CB()],
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default_root_dir=tmpdir,
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limit_train_batches=2,
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limit_val_batches=2,
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max_epochs=1,
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row_log_interval=1,
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weights_summary=None,
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)
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trainer.fit(model)
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