Lightning-AI/pytorch-lightning · error · ValueError

`setup_dataloaders` requires at least one dataloader as inpu

Error message

`setup_dataloaders` requires at least one dataloader as input.

What it means

Raised by `_validate_setup_dataloaders` when `fabric.setup_dataloaders()` is called with an empty sequence. Fabric needs at least one dataloader to wrap it in `_FabricDataLoader` and prepare it for the distributed strategy.

Source

Thrown at src/lightning/fabric/fabric.py:1247

            )

        if not optimizers:
            raise ValueError("`setup_optimizers` requires at least one optimizer as input.")

        if any(isinstance(opt, _FabricOptimizer) for opt in optimizers):
            raise ValueError("An optimizer should be passed only once to the `setup_optimizers` method.")

        if any(_has_meta_device_parameters_or_buffers(optimizer) for optimizer in optimizers):
            raise RuntimeError(
                "The optimizer has references to the model's meta-device parameters. Materializing them is"
                " is currently not supported. Create the optimizer after setting up the model, then call"
                " `fabric.setup_optimizers(optimizer)`."
            )

    def _validate_setup_dataloaders(self, dataloaders: Sequence[DataLoader]) -> None:
        self._validate_launched()
        if not dataloaders:
            raise ValueError("`setup_dataloaders` requires at least one dataloader as input.")

        if any(isinstance(dl, _FabricDataLoader) for dl in dataloaders):
            raise ValueError("A dataloader should be passed only once to the `setup_dataloaders` method.")

        if any(not isinstance(dl, DataLoader) for dl in dataloaders):
            raise TypeError("Only PyTorch DataLoader are currently supported in `setup_dataloaders`.")

    @staticmethod
    def _configure_callbacks(callbacks: Optional[Union[list[Any], Any]]) -> list[Any]:
        callbacks = callbacks if callbacks is not None else []
        callbacks = callbacks if isinstance(callbacks, list) else [callbacks]
        callbacks.extend(_load_external_callbacks("lightning.fabric.callbacks_factory"))
        return callbacks

View on GitHub (pinned to 9fed5c27d2)

Solutions

1. Pass at least one `torch.utils.data.DataLoader`, e.g. `train_dl = fabric.setup_dataloaders(DataLoader(train_ds, batch_size=32))`
2. Guard the call: only invoke setup_dataloaders when the dataloader list is non-empty
3. Check upstream logic that builds the dataloader list for bugs that empty it

Example fix

# before
loaders = [dl for dl in maybe_dataloaders if dl is not None]
fabric.setup_dataloaders(*loaders)  # may be empty

# after
if loaders:
    loaders = fabric.setup_dataloaders(*loaders)

if dataloaders:
    dataloaders = fabric.setup_dataloaders(*dataloaders)

When it happens

Trigger: Calling `fabric.setup_dataloaders()` with no args, or with an empty list, e.g. when building dataloaders conditionally and the list is empty at runtime.

Common situations: Evaluation-only or inference scripts adapted from training scripts where the val/test dataloader list may be empty; loops constructing dataloaders per split.

Related errors

• `setup_optimizers` requires at least one optimizer as input.
• A dataloader should be passed only once to the `setup_datalo
• Only PyTorch DataLoader are currently supported in `setup_da
• `val_dataloader` must be implemented to be used with the Lig
• `self.log_dict({dictionary})` was called, but nested diction

AI-assisted analysis of Lightning-AI/pytorch-lightning@9fed5c27d2 (2026-08-28). Data as JSON: /api/errors/559be418b9cd682e. Report an issue: GitHub.