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Callback

docs/source-pytorch/extensions/callbacks.rst

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.. role:: hidden :class: hidden-section

.. _callbacks:

######## Callback ########

Callbacks allow you to add arbitrary self-contained programs to your training. At specific points during the flow of execution (hooks), the Callback interface allows you to design programs that encapsulate a full set of functionality. It de-couples functionality that does not need to be in the :doc:lightning module <../common/lightning_module> and can be shared across projects.

Lightning has a callback system to execute them when needed. Callbacks should capture NON-ESSENTIAL logic that is NOT required for your :doc:lightning module <../common/lightning_module> to run.

A complete list of Callback hooks can be found in :class:~lightning.pytorch.callbacks.callback.Callback.

An overall Lightning system should have:

  1. Trainer for all engineering
  2. LightningModule for all research code.
  3. Callbacks for non-essential code.

|

Example:

.. testcode::

from lightning.pytorch.callbacks import Callback


class MyPrintingCallback(Callback):
    def on_train_start(self, trainer, pl_module):
        print("Training is starting")

    def on_train_end(self, trainer, pl_module):
        print("Training is ending")


trainer = Trainer(callbacks=[MyPrintingCallback()])

We successfully extended functionality without polluting our super clean :doc:lightning module <../common/lightning_module> research code.

You can do pretty much anything with callbacks.

Built-in Callbacks

Lightning has a few built-in callbacks.

.. note:: For a richer collection of callbacks, check out our bolts library <https://lightning-bolts.readthedocs.io/en/stable/index.html>_.

.. currentmodule:: lightning.pytorch.callbacks

.. autosummary:: :nosignatures: :template: classtemplate.rst

BackboneFinetuning
BaseFinetuning
BasePredictionWriter
BatchSizeFinder
Callback
DeviceStatsMonitor
EarlyStopping
GradientAccumulationScheduler
LambdaCallback
LearningRateFinder
LearningRateMonitor
ModelCheckpoint
ModelPruning
ModelSummary
ProgressBar
RichModelSummary
RichProgressBar
StochasticWeightAveraging
Timer
TQDMProgressBar
WeightAveraging

.. include:: callbacks_state.rst

Best Practices

The following are best practices when using/designing callbacks.

  1. Callbacks should be isolated in their functionality.
  2. Your callback should not rely on the behavior of other callbacks in order to work properly.
  3. Do not manually call methods from the callback.
  4. Directly calling methods (eg. on_validation_end) is strongly discouraged.
  5. Whenever possible, your callbacks should not depend on the order in which they are executed.

.. include:: entry_points.rst

.. _callback_hooks:

Callback API

Here is the full API of methods available in the Callback base class.

The :class:~lightning.pytorch.callbacks.Callback class is the base for all the callbacks in Lightning just like the :class:~lightning.pytorch.core.LightningModule is the base for all models. It defines a public interface that each callback implementation must follow, the key ones are:

Properties

state_key ^^^^^^^^^

.. autoattribute:: lightning.pytorch.callbacks.Callback.state_key :noindex:

Hooks

setup ^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.setup :noindex:

teardown ^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.teardown :noindex:

on_fit_start ^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_fit_start :noindex:

on_fit_end ^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_fit_end :noindex:

on_sanity_check_start ^^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_sanity_check_start :noindex:

on_sanity_check_end ^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_sanity_check_end :noindex:

on_train_batch_start ^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_train_batch_start :noindex:

on_train_batch_end ^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_train_batch_end :noindex:

on_train_epoch_start ^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_train_epoch_start :noindex:

on_train_epoch_end ^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_train_epoch_end :noindex:

on_validation_epoch_start ^^^^^^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_validation_epoch_start :noindex:

on_validation_epoch_end ^^^^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_validation_epoch_end :noindex:

on_test_epoch_start ^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_test_epoch_start :noindex:

on_test_epoch_end ^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_test_epoch_end :noindex:

on_predict_epoch_start ^^^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_predict_epoch_start :noindex:

on_predict_epoch_end ^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_predict_epoch_end :noindex:

on_validation_batch_start ^^^^^^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_validation_batch_start :noindex:

on_validation_batch_end ^^^^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_validation_batch_end :noindex:

on_test_batch_start ^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_test_batch_start :noindex:

on_test_batch_end ^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_test_batch_end :noindex:

on_predict_batch_start ^^^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_predict_batch_start :noindex:

on_predict_batch_end ^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_predict_batch_end :noindex:

on_train_start ^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_train_start :noindex:

on_train_end ^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_train_end :noindex:

on_validation_start ^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_validation_start :noindex:

on_validation_end ^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_validation_end :noindex:

on_test_start ^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_test_start :noindex:

on_test_end ^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_test_end :noindex:

on_predict_start ^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_predict_start :noindex:

on_predict_end ^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_predict_end :noindex:

on_exception ^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_exception :noindex:

state_dict ^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.state_dict :noindex:

on_save_checkpoint ^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_save_checkpoint :noindex:

load_state_dict ^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.load_state_dict :noindex:

on_load_checkpoint ^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_load_checkpoint :noindex:

on_before_backward ^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_before_backward :noindex:

on_after_backward ^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_after_backward :noindex:

on_before_optimizer_step ^^^^^^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_before_optimizer_step :noindex:

on_before_zero_grad ^^^^^^^^^^^^^^^^^^^

.. automethod:: lightning.pytorch.callbacks.Callback.on_before_zero_grad :noindex: