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Add periods to the documentation (#8252)

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Yuta Hayashibe 2021-07-02 23:48:55 +09:00 committed by GitHub
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commit 8193bae6bd
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1 changed files with 2 additions and 2 deletions
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pytorch_lightning/callbacks/model_checkpoint.py
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@ -102,7 +102,7 @@ class ModelCheckpoint(Callback):
saved (``model.save_weights(filepath)``), else the full model
is saved (``model.save(filepath)``).
every_n_train_steps: Number of training steps between checkpoints.
If ``every_n_train_steps == None or every_n_train_steps == 0``, we skip saving during training
If ``every_n_train_steps == None or every_n_train_steps == 0``, we skip saving during training.
To disable, set ``every_n_train_steps = 0``. This value must be ``None`` or non-negative.
This must be mutually exclusive with ``train_time_interval`` and ``every_n_val_epochs``.
train_time_interval: Checkpoints are monitored at the specified time interval.
@ -111,7 +111,7 @@ class ModelCheckpoint(Callback):
guaranteed to execute at the exact time specified, but should be close.
This must be mutually exclusive with ``every_n_train_steps`` and ``every_n_val_epochs``.
every_n_val_epochs: Number of validation epochs between checkpoints.
If ``every_n_val_epochs == None or every_n_val_epochs == 0``, we skip saving on validation end
If ``every_n_val_epochs == None or every_n_val_epochs == 0``, we skip saving on validation end.
To disable, set ``every_n_val_epochs = 0``. This value must be ``None`` or non-negative.
This must be mutually exclusive with ``every_n_train_steps`` and ``train_time_interval``.
Setting both ``ModelCheckpoint(..., every_n_val_epochs=V)`` and