mirror of
https://github.com/wassname/pytorch-lightning.git
synced 2026-08-30 11:29:56 +08:00
Jeremy Jordan
705e576417
* consolidate callbacks and hooks * ensure callbacks recieve proper arg types * remove model from init callback events * clean up early stopping event * update changelog * remove on_fit_start and on_fit_end * fix args for on_init_start and on_init_end * handle case where early stopping is not used * show all callback methods * wrap checkpoint callback logic into proper class * fix check for main process in checkpoint callback * move callbacks test to separate file * refactor arg checks * get model and call hook on same line * define trainer_options dict in one call * add more asserts to callback test
74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
from typing import Callable
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from abc import ABC
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from pytorch_lightning.callbacks import Callback
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class TrainerCallbackHookMixin(ABC):
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def __init__(self):
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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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self.callbacks: list[Callback] = []
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self.get_model: Callable = ...
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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_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_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_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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