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fix typos in validation_step and test_step docs #5438

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Merged
merged 4 commits into from
Jan 11, 2021
Merged

fix typos in validation_step and test_step docs #5438

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8ca2f03
fixed docs in lightning.py
thepooons Jan 9, 2021
e8d7531
few more
rohitgr7 Jan 9, 2021
da7e943
Merge branch 'master' into fix_lit_docs
rohitgr7 Jan 9, 2021
336f862
Merge branch 'master' into fix_lit_docs
SkafteNicki Jan 10, 2021
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16 changes: 8 additions & 8 deletions pytorch_lightning/core/lightning.py
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Original file line number Diff line number Diff line change
Expand Up @@ -621,14 +621,14 @@ def validation_step(self, *args, **kwargs):
for val_batch in val_data:
out = validation_step(val_batch)
val_outs.append(out)
validation_epoch_end(val_outs)
validation_epoch_end(val_outs)

Args:
batch (:class:`~torch.Tensor` | (:class:`~torch.Tensor`, ...) | [:class:`~torch.Tensor`, ...]):
The output of your :class:`~torch.utils.data.DataLoader`. A tensor, tuple or list.
batch_idx (int): The index of this batch
dataloader_idx (int): The index of the dataloader that produced this batch
(only if multiple val datasets used)
(only if multiple val dataloaders used)

Return:
Any of.
Expand Down Expand Up @@ -677,11 +677,11 @@ def validation_step(self, batch, batch_idx):
# log the outputs!
self.log_dict({'val_loss': loss, 'val_acc': val_acc})

If you pass in multiple val datasets, validation_step will have an additional argument.
If you pass in multiple val dataloaders, :meth:`validation_step` will have an additional argument.

.. code-block:: python

# CASE 2: multiple validation datasets
# CASE 2: multiple validation dataloaders
def validation_step(self, batch, batch_idx, dataloader_idx):
# dataloader_idx tells you which dataset this is.

Expand Down Expand Up @@ -813,7 +813,7 @@ def test_step(self, *args, **kwargs):
The output of your :class:`~torch.utils.data.DataLoader`. A tensor, tuple or list.
batch_idx (int): The index of this batch.
dataloader_idx (int): The index of the dataloader that produced this batch
(only if multiple test datasets used).
(only if multiple test dataloaders used).

Return:
Any of.
Expand Down Expand Up @@ -853,17 +853,17 @@ def test_step(self, batch, batch_idx):
# log the outputs!
self.log_dict({'test_loss': loss, 'test_acc': test_acc})

If you pass in multiple validation datasets, :meth:`test_step` will have an additional
If you pass in multiple test dataloaders, :meth:`test_step` will have an additional
argument.

.. code-block:: python

# CASE 2: multiple test datasets
# CASE 2: multiple test dataloaders
def test_step(self, batch, batch_idx, dataloader_idx):
# dataloader_idx tells you which dataset this is.

Note:
If you don't need to validate you don't need to implement this method.
If you don't need to test you don't need to implement this method.

Note:
When the :meth:`test_step` is called, the model has been put in eval mode and
Expand Down