Early stopping
==============

Stopping an epoch early
-----------------------
You can stop an epoch early by overriding :meth:`~pytorch_lightning.core.lightning.LightningModule.on_batch_start` to return `-1` when some condition is met.

If you do this repeatedly, for every epoch you had originally requested, then this will stop your entire run.

Default Epoch End Callback Behavior
-----------------------------------
By default early stopping will be enabled if `'val_loss'`
is found in :meth:`~pytorch_lightning.core.lightning.LightningModule.validation_epoch_end`'s
return dict. Otherwise training will proceed with early stopping disabled.

Enable Early Stopping using Callbacks on epoch end
--------------------------------------------------
There are two ways to enable early stopping using callbacks on epoch end.

.. doctest::

    >>> from pytorch_lightning import Trainer
    >>> from pytorch_lightning.callbacks import EarlyStopping

    # A) Set early_stop_callback to True. Will look for 'val_loss'
    # in validation_epoch_end() return dict. If it is not found an error is raised.
    >>> trainer = Trainer(early_stop_callback=True)
    # B) Or configure your own callback
    >>> early_stop_callback = EarlyStopping(
    ...    monitor='val_loss',
    ...    min_delta=0.00,
    ...    patience=3,
    ...    verbose=False,
    ...    mode='min'
    ... )
    >>> trainer = Trainer(early_stop_callback=early_stop_callback)

In any case, the callback will fall back to the training metrics (returned in
:meth:`~pytorch_lightning.core.lightning.LightningModule.training_step`,
:meth:`~pytorch_lightning.core.lightning.LightningModule.training_step_end`)
looking for a key to monitor if validation is disabled or
:meth:`~pytorch_lightning.core.lightning.LightningModule.validation_epoch_end`
is not defined.

.. seealso::
    :class:`~pytorch_lightning.trainer.trainer.Trainer`

Disable Early Stopping with callbacks on epoch end
--------------------------------------------------
To disable early stopping pass ``False`` to the
:paramref:`~pytorch_lightning.trainer.trainer.Trainer.early_stop_callback`.
Note that ``None`` will not disable early stopping but will lead to the
default behaviour.

.. seealso::
    :class:`~pytorch_lightning.trainer.trainer.Trainer`