# 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"""
Abstract base class used to build new callbacks.
"""
import abc
from typing import Any, Dict
from pytorch_lightning.core.lightning import LightningModule
[docs]class Callback(abc.ABC):
r"""
Abstract base class used to build new callbacks.
Subclass this class and override any of the relevant hooks
"""
[docs] def on_before_accelerator_backend_setup(self, trainer, pl_module: LightningModule) -> None:
"""Called before accelerator is being setup"""
pass
[docs] def setup(self, trainer, pl_module: LightningModule, stage: str) -> None:
"""Called when fit or test begins"""
pass
[docs] def teardown(self, trainer, pl_module: LightningModule, stage: str) -> None:
"""Called when fit or test ends"""
pass
[docs] def on_init_start(self, trainer) -> None:
"""Called when the trainer initialization begins, model has not yet been set."""
pass
[docs] def on_init_end(self, trainer) -> None:
"""Called when the trainer initialization ends, model has not yet been set."""
pass
[docs] def on_fit_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when fit begins"""
pass
[docs] def on_fit_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when fit ends"""
pass
[docs] def on_sanity_check_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the validation sanity check starts."""
pass
[docs] def on_sanity_check_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when the validation sanity check ends."""
pass
[docs] def on_train_batch_start(
self, trainer, pl_module: LightningModule, batch: Any, batch_idx: int, dataloader_idx: int
) -> None:
"""Called when the train batch begins."""
pass
[docs] def on_train_batch_end(
self, trainer, pl_module: LightningModule, outputs: Any, batch: Any, batch_idx: int, dataloader_idx: int
) -> None:
"""Called when the train batch ends."""
pass
[docs] def on_train_epoch_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the train epoch begins."""
pass
[docs] def on_train_epoch_end(self, trainer, pl_module: LightningModule, outputs: Any) -> None:
"""Called when the train epoch ends."""
pass
[docs] def on_validation_epoch_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the val epoch begins."""
pass
[docs] def on_validation_epoch_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when the val epoch ends."""
pass
[docs] def on_test_epoch_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the test epoch begins."""
pass
[docs] def on_test_epoch_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when the test epoch ends."""
pass
[docs] def on_epoch_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when either of train/val/test epoch begins."""
pass
[docs] def on_epoch_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when either of train/val/test epoch ends."""
pass
[docs] def on_batch_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the training batch begins."""
pass
[docs] def on_validation_batch_start(
self, trainer, pl_module: LightningModule, batch: Any, batch_idx: int, dataloader_idx: int
) -> None:
"""Called when the validation batch begins."""
pass
[docs] def on_validation_batch_end(
self, trainer, pl_module: LightningModule, outputs: Any, batch: Any, batch_idx: int, dataloader_idx: int
) -> None:
"""Called when the validation batch ends."""
pass
[docs] def on_test_batch_start(
self, trainer, pl_module: LightningModule, batch: Any, batch_idx: int, dataloader_idx: int
) -> None:
"""Called when the test batch begins."""
pass
[docs] def on_test_batch_end(
self, trainer, pl_module: LightningModule, outputs: Any, batch: Any, batch_idx: int, dataloader_idx: int
) -> None:
"""Called when the test batch ends."""
pass
[docs] def on_batch_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when the training batch ends."""
pass
[docs] def on_train_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the train begins."""
pass
[docs] def on_train_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when the train ends."""
pass
[docs] def on_pretrain_routine_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the pretrain routine begins."""
pass
[docs] def on_pretrain_routine_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when the pretrain routine ends."""
pass
[docs] def on_validation_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the validation loop begins."""
pass
[docs] def on_validation_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when the validation loop ends."""
pass
[docs] def on_test_start(self, trainer, pl_module: LightningModule) -> None:
"""Called when the test begins."""
pass
[docs] def on_test_end(self, trainer, pl_module: LightningModule) -> None:
"""Called when the test ends."""
pass
[docs] def on_keyboard_interrupt(self, trainer, pl_module: LightningModule) -> None:
"""Called when the training is interrupted by ``KeyboardInterrupt``."""
pass
[docs] def on_save_checkpoint(self, trainer, pl_module: LightningModule, checkpoint: Dict[str, Any]) -> dict:
"""
Called when saving a model checkpoint, use to persist state.
Args:
trainer: the current Trainer instance.
pl_module: the current LightningModule instance.
checkpoint: the checkpoint dictionary that will be saved.
Returns:
The callback state.
"""
pass
[docs] def on_load_checkpoint(self, callback_state: Dict[str, Any]) -> None:
"""Called when loading a model checkpoint, use to reload state.
Args:
callback_state: the callback state returned by ``on_save_checkpoint``.
"""
pass
[docs] def on_after_backward(self, trainer, pl_module: LightningModule) -> None:
"""Called after ``loss.backward()`` and before optimizers do anything."""
pass
[docs] def on_before_zero_grad(self, trainer, pl_module: LightningModule, optimizer) -> None:
"""Called after ``optimizer.step()`` and before ``optimizer.zero_grad()``."""
pass
