349 lines
8.4 KiB
ReStructuredText
349 lines
8.4 KiB
ReStructuredText
.. testsetup:: *
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from pytorch_lightning.trainer.trainer import Trainer
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from pytorch_lightning.callbacks.base import Callback
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.. role:: hidden
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:class: hidden-section
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.. _callbacks:
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Callback
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========
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.. raw:: html
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<video width="100%" max-width="400px" controls
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poster="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/pl_docs/trainer_flags/thumb/callbacks.jpg"
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src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/pl_docs/trainer_flags/callbacks.mp4"></video>
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A callback is a self-contained program that can be reused across projects.
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Lightning has a callback system to execute callbacks when needed. Callbacks should capture NON-ESSENTIAL
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logic that is NOT required for your :ref:`lightning_module` to run.
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Here's the flow of how the callback hooks are executed:
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.. raw:: html
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<video width="100%" max-width="400px" controls autoplay muted playsinline src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/pl_docs/pt_callbacks_mov.m4v"></video>
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An overall Lightning system should have:
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1. Trainer for all engineering
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2. LightningModule for all research code.
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3. Callbacks for non-essential code.
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Example:
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.. testcode::
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from pytorch_lightning.callbacks import Callback
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class MyPrintingCallback(Callback):
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def on_init_start(self, trainer):
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print('Starting to init trainer!')
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def on_init_end(self, trainer):
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print('trainer is init now')
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def on_train_end(self, trainer, pl_module):
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print('do something when training ends')
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trainer = Trainer(callbacks=[MyPrintingCallback()])
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.. testoutput::
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Starting to init trainer!
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trainer is init now
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We successfully extended functionality without polluting our super clean
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:ref:`lightning_module` research code.
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-----------
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Examples
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--------
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You can do pretty much anything with callbacks.
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- `Add a MLP to fine-tune self-supervised networks <https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_callbacks.html#sslonlineevaluator>`_.
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- `Find how to modify an image input to trick the classification result <https://pytorch-lightning-bolts.readthedocs.io/en/latest/vision_callbacks.html#confused-logit>`_.
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- `Interpolate the latent space of any variational model <https://pytorch-lightning-bolts.readthedocs.io/en/latest/variational_callbacks.html#latent-dim-interpolator>`_.
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- `Log images to Tensorboard for any model <https://pytorch-lightning-bolts.readthedocs.io/en/latest/vision_callbacks.html#tensorboard-image-generator>`_.
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--------------
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Built-in Callbacks
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------------------
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Lightning has a few built-in callbacks.
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.. note::
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For a richer collection of callbacks, check out our
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`bolts library <https://pytorch-lightning-bolts.readthedocs.io/en/latest/callbacks.html>`_.
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.. currentmodule:: pytorch_lightning.callbacks
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.. autosummary::
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:toctree: generated
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:nosignatures:
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:template: classtemplate.rst
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BackboneLambdaFinetuningCallback
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BaseFinetuningCallback
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Callback
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EarlyStopping
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GPUStatsMonitor
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GradientAccumulationScheduler
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LambdaCallback
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LearningRateMonitor
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ModelCheckpoint
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ProgressBar
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ProgressBarBase
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----------
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Persisting State
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----------------
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Some callbacks require internal state in order to function properly. You can optionally
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choose to persist your callback's state as part of model checkpoint files using the callback hooks
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:meth:`~pytorch_lightning.callbacks.Callback.on_save_checkpoint` and :meth:`~pytorch_lightning.callbacks.Callback.on_load_checkpoint`.
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However, you must follow two constraints:
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1. Your returned state must be able to be pickled.
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2. You can only use one instance of that class in the Trainer callbacks list. We don't support persisting state for multiple callbacks of the same class.
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Best Practices
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--------------
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The following are best practices when using/designing callbacks.
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1. Callbacks should be isolated in their functionality.
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2. Your callback should not rely on the behavior of other callbacks in order to work properly.
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3. Do not manually call methods from the callback.
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4. Directly calling methods (eg. `on_validation_end`) is strongly discouraged.
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5. Whenever possible, your callbacks should not depend on the order in which they are executed.
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-----------
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.. _hooks:
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Available Callback hooks
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------------------------
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setup
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^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.setup
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:noindex:
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teardown
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^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.teardown
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:noindex:
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on_init_start
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^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_init_start
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:noindex:
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on_init_end
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^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_init_end
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:noindex:
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on_fit_start
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^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_save_checkpoint
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:noindex:
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on_fit_end
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^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_fit_end
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:noindex:
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on_sanity_check_start
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^^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_sanity_check_start
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:noindex:
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on_sanity_check_end
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^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_sanity_check_end
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:noindex:
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on_train_batch_start
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^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_train_batch_start
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:noindex:
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on_train_batch_end
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^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_train_batch_end
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:noindex:
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on_train_epoch_start
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^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_train_epoch_start
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:noindex:
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on_train_epoch_end
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^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_train_epoch_end
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:noindex:
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on_validation_epoch_start
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^^^^^^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_validation_epoch_start
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:noindex:
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on_validation_epoch_end
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^^^^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_validation_epoch_end
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:noindex:
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on_test_epoch_start
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^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_test_epoch_start
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:noindex:
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on_test_epoch_end
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^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_test_epoch_end
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:noindex:
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on_epoch_start
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^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_epoch_start
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:noindex:
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on_epoch_end
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^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_epoch_end
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:noindex:
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on_batch_start
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^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_batch_start
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:noindex:
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on_validation_batch_start
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^^^^^^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_validation_batch_start
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:noindex:
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on_validation_batch_end
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^^^^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_validation_batch_end
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:noindex:
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on_test_batch_start
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^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_test_batch_start
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:noindex:
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on_test_batch_end
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^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_test_batch_end
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:noindex:
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on_batch_end
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^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_batch_end
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:noindex:
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on_train_start
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^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_train_start
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:noindex:
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on_train_end
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^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_train_end
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:noindex:
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on_pretrain_routine_start
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^^^^^^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_pretrain_routine_start
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:noindex:
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on_pretrain_routine_end
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^^^^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_pretrain_routine_end
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:noindex:
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on_validation_start
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^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_validation_start
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:noindex:
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on_validation_end
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^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_validation_end
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:noindex:
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on_test_start
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^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_test_start
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:noindex:
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on_test_end
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^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_test_end
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:noindex:
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on_keyboard_interrupt
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^^^^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_keyboard_interrupt
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:noindex:
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on_save_checkpoint
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^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_save_checkpoint
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:noindex:
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on_load_checkpoint
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^^^^^^^^^^^^^^^^^^
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.. automethod:: pytorch_lightning.callbacks.Callback.on_load_checkpoint
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:noindex:
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