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142bc0230e
* base implementation * docs + implementation * fix styling * add lr string * renaming * CHANGELOG.md * add tests * Apply suggestions from code review Co-Authored-By: Adrian Wälchli <aedu.waelchli@gmail.com> * Apply suggestions from code review * Update pytorch_lightning/callbacks/lr_logger.py * Update pytorch_lightning/callbacks/lr_logger.py * add test for naming * base implementation * docs + implementation * fix styling * add lr string * renaming * CHANGELOG.md * add tests * Apply suggestions from code review Co-Authored-By: Adrian Wälchli <aedu.waelchli@gmail.com> * Apply suggestions from code review * Update pytorch_lightning/callbacks/lr_logger.py * Update pytorch_lightning/callbacks/lr_logger.py * add test for naming * Update pytorch_lightning/callbacks/lr_logger.py Co-Authored-By: Adrian Wälchli <aedu.waelchli@gmail.com> * suggestions from code review * fix styling * rebase * fix tests Co-authored-by: Nicki Skafte <nugginea@gmail.com> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
94 lines
2.1 KiB
ReStructuredText
94 lines
2.1 KiB
ReStructuredText
.. role:: hidden
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:class: hidden-section
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.. _callbacks:
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Callbacks
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=========
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Lightning has a callback system to execute arbitrary code. Callbacks should capture NON-ESSENTIAL
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logic that is NOT required for your :class:`~pytorch_lightning.core.LightningModule` to run.
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An overall Lightning system should have:
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1. Trainer for all engineering
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2. LightningModule for all research code.
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3. Callbacks for non-essential code.
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Example:
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.. doctest::
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>>> import pytorch_lightning as pl
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>>> class MyPrintingCallback(pl.Callback):
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...
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... def on_init_start(self, trainer):
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... print('Starting to init trainer!')
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...
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... def on_init_end(self, trainer):
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... print('trainer is init now')
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...
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... def on_train_end(self, trainer, pl_module):
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... print('do something when training ends')
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...
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>>> trainer = pl.Trainer(callbacks=[MyPrintingCallback()])
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Starting to init trainer!
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trainer is init now
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We successfully extended functionality without polluting our super clean
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:class:`~pytorch_lightning.core.LightningModule` research code.
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---------
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.. automodule:: pytorch_lightning.callbacks.base
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:noindex:
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:exclude-members:
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_del_model,
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_save_model,
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_abc_impl,
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check_monitor_top_k,
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---------
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.. automodule:: pytorch_lightning.callbacks.early_stopping
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:noindex:
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:exclude-members:
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_del_model,
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_save_model,
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_abc_impl,
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check_monitor_top_k,
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---------
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.. automodule:: pytorch_lightning.callbacks.model_checkpoint
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:noindex:
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:exclude-members:
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_del_model,
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_save_model,
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_abc_impl,
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check_monitor_top_k,
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---------
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.. automodule:: pytorch_lightning.callbacks.gradient_accumulation_scheduler
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:noindex:
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:exclude-members:
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_del_model,
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_save_model,
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_abc_impl,
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check_monitor_top_k,
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---------
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.. automodule:: pytorch_lightning.callbacks.progress
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:noindex:
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:exclude-members:
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---------
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.. automodule:: pytorch_lightning.callbacks.lr_logger
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:noindex:
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:exclude-members:
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_extract_lr,
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_find_names |