def test_dataloader(self, *args: Any,
**kwargs: Any) -> Union[DataLoader, List[DataLoader]]:
"""The test dataloader"""
assert some(
self, "datamodule.test_dataloader"
), f"{name(self)} should either have a `self.datamodule: pl.LightningDataModule` or overload the `test_dataloader` function."
return self.datamodule.test_dataloader
def validate_attributes(self):
assert is_shape(
getattr(self, "input_shape", None)
), "RideDataset should define an `input_shape` of type int, list, tuple, or namedtuple."
assert is_shape(
getattr(self, "output_shape", None)
), "RideDataset should define `output_shape` of type int, list, tuple, or namedtuple."
for n in RideDataset.configs().names:
assert some(
self, f"hparams.{n}"
), "`self.hparams.{n}` not found in Dataset. Did you forget to include its `configs`?"
def validate_attributes(self):
RideDataset.validate_attributes(self)
for attr in DummyRegressionDataLoader.configs().names:
assert some(
self, f"hparams.{attr}"
), f"ClassificationLifecycle should define `hparams.{attr}` but none was found."
def train_dataloader(self, *args: Any, **kwargs: Any) -> DataLoader:
"""The train dataloader"""
assert some(
self, "datamodule.train_dataloader"
), f"{name(self)} should either have a `self.datamodule: pl.LightningDataModule` or overload the `train_dataloader` function."
return self.datamodule.train_dataloader