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Source code for pytorch_lightning.callbacks.base

# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
r"""
Base class used to build new callbacks.

"""

from typing import Any, Dict, List, Optional, Type

import torch
from torch.optim import Optimizer

import pytorch_lightning as pl
from pytorch_lightning.utilities.types import STEP_OUTPUT


[docs]class Callback: r""" Abstract base class used to build new callbacks. Subclass this class and override any of the relevant hooks """ @property def state_key(self) -> str: """Identifier for the state of the callback. Used to store and retrieve a callback's state from the checkpoint dictionary by ``checkpoint["callbacks"][state_key]``. Implementations of a callback need to provide a unique state key if 1) the callback has state and 2) it is desired to maintain the state of multiple instances of that callback. """ return self.__class__.__qualname__ @property def _legacy_state_key(self) -> Type["Callback"]: """State key for checkpoints saved prior to version 1.5.0.""" return type(self) def _generate_state_key(self, **kwargs: Any) -> str: """Formats a set of key-value pairs into a state key string with the callback class name prefixed. Useful for defining a :attr:`state_key`. Args: **kwargs: A set of key-value pairs. Must be serializable to :class:`str`. """ return f"{self.__class__.__qualname__}{repr(kwargs)}"
[docs] def on_configure_sharded_model(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Use `setup()` instead. Called before configure sharded model. """
[docs] def on_before_accelerator_backend_setup(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``setup()`` instead. Called before accelerator is being setup. """
[docs] def setup(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", stage: Optional[str] = None) -> None: """Called when fit, validate, test, predict, or tune begins."""
[docs] def teardown(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", stage: Optional[str] = None) -> None: """Called when fit, validate, test, predict, or tune ends."""
[docs] def on_init_start(self, trainer: "pl.Trainer") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Called when the trainer initialization begins, model has not yet been set. """
[docs] def on_init_end(self, trainer: "pl.Trainer") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Called when the trainer initialization ends, model has not yet been set. """
[docs] def on_fit_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when fit begins."""
[docs] def on_fit_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when fit ends."""
[docs] def on_sanity_check_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the validation sanity check starts."""
[docs] def on_sanity_check_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the validation sanity check ends."""
[docs] def on_train_batch_start( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int, unused: int = 0, ) -> None: """Called when the train batch begins."""
[docs] def on_train_batch_end( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: STEP_OUTPUT, batch: Any, batch_idx: int, unused: int = 0, ) -> None: """Called when the train batch ends."""
[docs] def on_train_epoch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the train epoch begins."""
[docs] def on_train_epoch_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the train epoch ends. To access all batch outputs at the end of the epoch, either: 1. Implement `training_epoch_end` in the `LightningModule` and access outputs via the module OR 2. Cache data across train batch hooks inside the callback implementation to post-process in this hook. """
[docs] def on_validation_epoch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the val epoch begins."""
[docs] def on_validation_epoch_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the val epoch ends."""
[docs] def on_test_epoch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the test epoch begins."""
[docs] def on_test_epoch_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the test epoch ends."""
[docs] def on_predict_epoch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the predict epoch begins."""
[docs] def on_predict_epoch_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: List[Any]) -> None: """Called when the predict epoch ends."""
[docs] def on_epoch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``on_<train/validation/test>_epoch_start`` instead. Called when either of train/val/test epoch begins. """
[docs] def on_epoch_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``on_<train/validation/test>_epoch_end`` instead. Called when either of train/val/test epoch ends. """
[docs] def on_batch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``on_train_batch_start`` instead. Called when the training batch begins. """
[docs] def on_batch_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``on_train_batch_end`` instead. Called when the training batch ends. """
[docs] def on_validation_batch_start( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int, dataloader_idx: int ) -> None: """Called when the validation batch begins."""
[docs] def on_validation_batch_end( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: Optional[STEP_OUTPUT], batch: Any, batch_idx: int, dataloader_idx: int, ) -> None: """Called when the validation batch ends."""
[docs] def on_test_batch_start( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int, dataloader_idx: int ) -> None: """Called when the test batch begins."""
[docs] def on_test_batch_end( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: Optional[STEP_OUTPUT], batch: Any, batch_idx: int, dataloader_idx: int, ) -> None: """Called when the test batch ends."""
[docs] def on_predict_batch_start( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int, dataloader_idx: int ) -> None: """Called when the predict batch begins."""
[docs] def on_predict_batch_end( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: Any, batch: Any, batch_idx: int, dataloader_idx: int, ) -> None: """Called when the predict batch ends."""
[docs] def on_train_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the train begins."""
[docs] def on_train_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the train ends."""
[docs] def on_pretrain_routine_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``on_fit_start`` instead. Called when the pretrain routine begins. """
[docs] def on_pretrain_routine_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.6 This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``on_fit_start`` instead. Called when the pretrain routine ends. """
[docs] def on_validation_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the validation loop begins."""
[docs] def on_validation_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the validation loop ends."""
[docs] def on_test_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the test begins."""
[docs] def on_test_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the test ends."""
[docs] def on_predict_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when the predict begins."""
[docs] def on_predict_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called when predict ends."""
[docs] def on_keyboard_interrupt(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: r""" .. deprecated:: v1.5 This callback hook was deprecated in v1.5 in favor of `on_exception` and will be removed in v1.7. Called when any trainer execution is interrupted by KeyboardInterrupt. """
[docs] def on_exception(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", exception: BaseException) -> None: """Called when any trainer execution is interrupted by an exception."""
[docs] def state_dict(self) -> Dict[str, Any]: """Called when saving a checkpoint, implement to generate callback's ``state_dict``. Returns: A dictionary containing callback state. """ return {}
[docs] def load_state_dict(self, state_dict: Dict[str, Any]) -> None: """Called when loading a checkpoint, implement to reload callback state given callback's ``state_dict``. Args: state_dict: the callback state returned by ``state_dict``. """ pass
[docs] def on_save_checkpoint( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", checkpoint: Dict[str, Any] ) -> Optional[dict]: r""" Called when saving a checkpoint to give you a chance to store anything else you might want to save. Args: trainer: the current :class:`~pytorch_lightning.trainer.Trainer` instance. pl_module: the current :class:`~pytorch_lightning.core.lightning.LightningModule` instance. checkpoint: the checkpoint dictionary that will be saved. Returns: None or the callback state. Support for returning callback state will be removed in v1.8. .. deprecated:: v1.6 Returning a value from this method was deprecated in v1.6 and will be removed in v1.8. Implement ``Callback.state_dict`` instead to return state. In v1.8 ``Callback.on_save_checkpoint`` can only return None. """
[docs] def on_load_checkpoint( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", callback_state: Dict[str, Any] ) -> None: r""" Called when loading a model checkpoint, use to reload state. Args: trainer: the current :class:`~pytorch_lightning.trainer.Trainer` instance. pl_module: the current :class:`~pytorch_lightning.core.lightning.LightningModule` instance. callback_state: the callback state returned by ``on_save_checkpoint``. Note: The ``on_load_checkpoint`` won't be called with an undefined state. If your ``on_load_checkpoint`` hook behavior doesn't rely on a state, you will still need to override ``on_save_checkpoint`` to return a ``dummy state``. .. deprecated:: v1.6 This callback hook will change its signature and behavior in v1.8. If you wish to load the state of the callback, use ``Callback.load_state_dict`` instead. In v1.8 ``Callback.on_load_checkpoint(checkpoint)`` will receive the entire loaded checkpoint dictionary instead of only the callback state from the checkpoint. """
[docs] def on_before_backward(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", loss: torch.Tensor) -> None: """Called before ``loss.backward()``."""
[docs] def on_after_backward(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None: """Called after ``loss.backward()`` and before optimizers are stepped."""
[docs] def on_before_optimizer_step( self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", optimizer: Optimizer, opt_idx: int ) -> None: """Called before ``optimizer.step()``."""
[docs] def on_before_zero_grad(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", optimizer: Optimizer) -> None: """Called before ``optimizer.zero_grad()``."""

© Copyright Copyright (c) 2018-2022, William Falcon et al... Revision a64e1dfd.

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