212 lines
8.2 KiB
Python
212 lines
8.2 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from abc import ABC
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from copy import deepcopy
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from typing import Callable, List
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from pytorch_lightning.callbacks import Callback
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class TrainerCallbackHookMixin(ABC):
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# this is just a summary on variables used in this abstract class,
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# the proper values/initialisation should be done in child class
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callbacks: List[Callback] = []
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get_model: Callable
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def setup(self, stage: str):
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"""Called in the beginning of fit and test"""
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for callback in self.callbacks:
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callback.setup(self, self.get_model(), stage)
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def teardown(self, stage: str):
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"""Called at the end of fit and test"""
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for callback in self.callbacks:
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callback.teardown(self, self.get_model(), stage)
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def on_init_start(self):
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"""Called when the trainer initialization begins, model has not yet been set."""
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for callback in self.callbacks:
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callback.on_init_start(self)
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def on_init_end(self):
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"""Called when the trainer initialization ends, model has not yet been set."""
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for callback in self.callbacks:
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callback.on_init_end(self)
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def on_fit_start(self):
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"""Called when the trainer initialization begins, model has not yet been set."""
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for callback in self.callbacks:
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callback.on_fit_start(self, self.get_model())
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def on_fit_end(self):
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"""Called when the trainer initialization begins, model has not yet been set."""
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for callback in self.callbacks:
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callback.on_fit_end(self, self.get_model())
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def on_sanity_check_start(self):
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"""Called when the validation sanity check starts."""
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for callback in self.callbacks:
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callback.on_sanity_check_start(self, self.get_model())
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def on_sanity_check_end(self):
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"""Called when the validation sanity check ends."""
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for callback in self.callbacks:
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callback.on_sanity_check_end(self, self.get_model())
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def on_train_epoch_start(self):
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"""Called when the epoch begins."""
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for callback in self.callbacks:
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callback.on_train_epoch_start(self, self.get_model())
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def on_train_epoch_end(self):
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"""Called when the epoch ends."""
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for callback in self.callbacks:
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callback.on_train_epoch_end(self, self.get_model())
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def on_validation_epoch_start(self):
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"""Called when the epoch begins."""
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for callback in self.callbacks:
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callback.on_validation_epoch_start(self, self.get_model())
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def on_validation_epoch_end(self):
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"""Called when the epoch ends."""
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for callback in self.callbacks:
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callback.on_validation_epoch_end(self, self.get_model())
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def on_test_epoch_start(self):
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"""Called when the epoch begins."""
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for callback in self.callbacks:
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callback.on_test_epoch_start(self, self.get_model())
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def on_test_epoch_end(self):
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"""Called when the epoch ends."""
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for callback in self.callbacks:
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callback.on_test_epoch_end(self, self.get_model())
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def on_epoch_start(self):
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"""Called when the epoch begins."""
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for callback in self.callbacks:
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callback.on_epoch_start(self, self.get_model())
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def on_epoch_end(self):
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"""Called when the epoch ends."""
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for callback in self.callbacks:
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callback.on_epoch_end(self, self.get_model())
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def on_train_start(self):
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"""Called when the train begins."""
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for callback in self.callbacks:
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callback.on_train_start(self, self.get_model())
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def on_train_end(self):
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"""Called when the train ends."""
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for callback in self.callbacks:
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callback.on_train_end(self, self.get_model())
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def on_pretrain_routine_start(self, model):
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"""Called when the train begins."""
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for callback in self.callbacks:
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callback.on_pretrain_routine_start(self, model)
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def on_pretrain_routine_end(self, model):
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"""Called when the train ends."""
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for callback in self.callbacks:
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callback.on_pretrain_routine_end(self, model)
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def on_batch_start(self):
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"""Called when the training batch begins."""
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for callback in self.callbacks:
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callback.on_batch_start(self, self.get_model())
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def on_batch_end(self):
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"""Called when the training batch ends."""
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for callback in self.callbacks:
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callback.on_batch_end(self, self.get_model())
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def on_train_batch_start(self, batch, batch_idx, dataloader_idx):
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"""Called when the training batch begins."""
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for callback in self.callbacks:
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callback.on_train_batch_start(self, self.get_model(), batch, batch_idx, dataloader_idx)
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def on_train_batch_end(self, batch, batch_idx, dataloader_idx):
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"""Called when the training batch ends."""
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for callback in self.callbacks:
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callback.on_train_batch_end(self, self.get_model(), batch, batch_idx, dataloader_idx)
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def on_validation_batch_start(self, batch, batch_idx, dataloader_idx):
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"""Called when the validation batch begins."""
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for callback in self.callbacks:
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callback.on_validation_batch_start(self, self.get_model(), batch, batch_idx, dataloader_idx)
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def on_validation_batch_end(self, batch, batch_idx, dataloader_idx):
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"""Called when the validation batch ends."""
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for callback in self.callbacks:
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callback.on_validation_batch_end(self, self.get_model(), batch, batch_idx, dataloader_idx)
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def on_test_batch_start(self, batch, batch_idx, dataloader_idx):
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"""Called when the test batch begins."""
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for callback in self.callbacks:
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callback.on_test_batch_start(self, self.get_model(), batch, batch_idx, dataloader_idx)
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def on_test_batch_end(self, batch, batch_idx, dataloader_idx):
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"""Called when the test batch ends."""
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for callback in self.callbacks:
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callback.on_test_batch_end(self, self.get_model(), batch, batch_idx, dataloader_idx)
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def on_validation_start(self):
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"""Called when the validation loop begins."""
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for callback in self.callbacks:
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callback.on_validation_start(self, self.get_model())
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def on_validation_end(self):
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"""Called when the validation loop ends."""
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for callback in self.callbacks:
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callback.on_validation_end(self, self.get_model())
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def on_test_start(self):
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"""Called when the test begins."""
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for callback in self.callbacks:
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callback.on_test_start(self, self.get_model())
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def on_test_end(self):
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"""Called when the test ends."""
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for callback in self.callbacks:
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callback.on_test_end(self, self.get_model())
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def on_keyboard_interrupt(self):
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"""Called when the training is interrupted by KeyboardInterrupt."""
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for callback in self.callbacks:
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callback.on_keyboard_interrupt(self, self.get_model())
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def on_save_checkpoint(self):
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"""Called when saving a model checkpoint."""
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callback_states = {}
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for callback in self.callbacks:
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callback_class = type(callback)
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state = callback.on_save_checkpoint(self, self.get_model())
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if state:
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callback_states[callback_class] = state
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return callback_states
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def on_load_checkpoint(self, checkpoint):
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"""Called when loading a model checkpoint."""
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callback_states = checkpoint.get('callbacks')
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for callback in self.callbacks:
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state = callback_states.get(type(callback))
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if state:
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state = deepcopy(state)
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callback.on_load_checkpoint(state)
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