Lightning-AI/pytorch-lightning · error · MisconfigurationException

In tuner with `method`={method!r}, `train_dataloaders` and `

Error message

In tuner with `method`={method!r}, `train_dataloaders` and `val_dataloaders` arguments should be None, please consider setting `dataloaders` instead.

What it means

For tuner calls with method != 'fit' (validate/test/predict), the train_dataloaders and val_dataloaders arguments must be None; only the unified `dataloaders` argument is accepted. Violating this raises MisconfigurationException.

Source

Thrown at src/lightning/pytorch/tuner/tuning.py:223

def _check_tuner_configuration(
    train_dataloaders: Optional[Union[TRAIN_DATALOADERS, "pl.LightningDataModule"]] = None,
    val_dataloaders: Optional[EVAL_DATALOADERS] = None,
    dataloaders: Optional[EVAL_DATALOADERS] = None,
    method: Literal["fit", "validate", "test", "predict"] = "fit",
) -> None:
    supported_methods = ("fit", "validate", "test", "predict")
    if method not in supported_methods:
        raise ValueError(f"method {method!r} is invalid. Should be one of {supported_methods}.")

    if method == "fit":
        if dataloaders is not None:
            raise MisconfigurationException(
                f"In tuner with method={method!r}, `dataloaders` argument should be None,"
                " please consider setting `train_dataloaders` and `val_dataloaders` instead."
            )
    else:
        if train_dataloaders is not None or val_dataloaders is not None:
            raise MisconfigurationException(
                f"In tuner with `method`={method!r}, `train_dataloaders` and `val_dataloaders`"
                " arguments should be None, please consider setting `dataloaders` instead."
            )


def _check_lr_find_configuration(trainer: "pl.Trainer") -> None:
    # local import to avoid circular import
    from lightning.pytorch.callbacks.lr_finder import LearningRateFinder

    configured_callbacks = [cb for cb in trainer.callbacks if isinstance(cb, LearningRateFinder)]
    if configured_callbacks:
        raise ValueError(
            "Trainer is already configured with a `LearningRateFinder` callback."
            "Please remove it if you want to use the Tuner."
        )


def _check_scale_batch_size_configuration(trainer: "pl.Trainer") -> None:

View on GitHub (pinned to 9fed5c27d2)

Solutions

1. Remove train_dataloaders/val_dataloaders and pass dataloaders=... instead
2. Check you actually meant a non-fit method; use 'fit' if you want train/val loaders

Example fix

# before
trainer.tuner.lr_find(model, method="test", train_dataloaders=dl)
# after
trainer.tuner.lr_find(model, method="test", dataloaders=dl)

if method != "fit":
    assert train_dataloaders is None and val_dataloaders is None
    assert dataloaders is not None

When it happens

Trigger: trainer.tuner.lr_find(model, method='validate', train_dataloaders=dl) or scale_batch_size with train/val loaders and a non-fit method.

Common situations: Reusing a fit-style call signature while switching the method to validate/test/predict.

Understand the failure class

Background: "Must be a positive integer", "Invalid value", "Unsupported": the invalid-argument-value error family, when a library rejects the value you pass — this error's family across 35 libraries.

Related errors

• In tuner with method={method!r}, `dataloaders` argument shou
• method='fit' is the only valid configuration to run lr finde
• Device should be CPU, got {device} instead.
• Trying to inject custom `Sampler` into the `{dataloader_cls_
• You are trying to `self.log()` but the loop's result collect

AI-assisted analysis of Lightning-AI/pytorch-lightning@9fed5c27d2 (2026-08-28). Data as JSON: /api/errors/bab6bf720482f3d1. Report an issue: GitHub.