mirror of
https://github.com/wassname/pytorch-lightning.git
synced 2026-09-21 13:20:08 +08:00
Hadrien MaryandJirka Borovec
89d5772f55
* add .vscode in .gitignore * Split callbacks in individual files + add a property to Callback for easy trainer instance access * formatting * Add a conda env file for quick and easy env setup to develop on PL * Adress comments * add fix to kth_best_model * add some typing to callbacks * fix typo * add autopep8 config to pyproject.toml * format again * format * fix toml * fix toml again * consistent max line length in all config files * remove conda env file * Update pytorch_lightning/callbacks/early_stopping.py Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Update pytorch_lightning/callbacks/model_checkpoint.py Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * docstring * Update pytorch_lightning/callbacks/model_checkpoint.py Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Update pytorch_lightning/callbacks/model_checkpoint.py Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * fix logic error * format * simplify if/else * format * fix linting issue in changelog * edit changelog about new callback mechanism * fix remaining formating issue on CHANGELOG * remove lambda function because it's compatible with pickle (used during ddp) Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
69 lines
1.5 KiB
Python
69 lines
1.5 KiB
Python
"""
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Callbacks
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=========
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Callbacks supported by Lightning
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"""
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import abc
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_NO_TRAINER_ERROR_MSG = ".set_trainer() should be called after the callback initialization"
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class Callback(abc.ABC):
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"""Abstract base class used to build new callbacks."""
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def __init__(self):
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self._trainer = None
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@property
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def trainer(self):
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assert self._trainer is not None, _NO_TRAINER_ERROR_MSG
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return self._trainer
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def set_trainer(self, trainer):
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"""Make a link to the trainer, so different things like `trainer.current_epoch`,
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`trainer.batch_idx`, `trainer.global_step` can be used."""
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self._trainer = trainer
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def on_epoch_begin(self):
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"""Called when the epoch begins."""
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pass
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def on_epoch_end(self):
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"""Called when the epoch ends."""
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pass
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def on_batch_begin(self):
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"""Called when the training batch begins."""
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pass
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def on_batch_end(self):
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"""Called when the training batch ends."""
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pass
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def on_train_begin(self):
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"""Called when the train begins."""
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pass
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def on_train_end(self):
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"""Called when the train ends."""
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pass
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def on_validation_begin(self):
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"""Called when the validation loop begins."""
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pass
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def on_validation_end(self):
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"""Called when the validation loop ends."""
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pass
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def on_test_begin(self):
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"""Called when the test begins."""
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pass
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def on_test_end(self):
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"""Called when the test ends."""
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pass
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