36 lines
943 B
Python
36 lines
943 B
Python
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import torch
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from tests.base.boring_model import BoringModel, RandomDataset
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from pytorch_lightning import Trainer
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def test_overfit_multiple_val_loaders(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 TestModel(BoringModel):
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def validation_step(self, batch, batch_idx, dataloader_idx):
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output = self.layer(batch[0])
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loss = self.loss(batch, output)
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return {"x": loss}
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def validation_epoch_end(self, outputs) -> None:
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pass
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def val_dataloader(self):
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dl1 = torch.utils.data.DataLoader(RandomDataset(32, 64))
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dl2 = torch.utils.data.DataLoader(RandomDataset(32, 64))
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return [dl1, dl2]
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model = TestModel()
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trainer = Trainer(
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default_root_dir=tmpdir,
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max_epochs=2,
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overfit_batches=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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