Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[keras/feature_column] Standardise docstring usage of "Default to" #17958

Merged
merged 1 commit into from
May 31, 2023
Merged

[keras/feature_column] Standardise docstring usage of "Default to" #17958

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions keras/feature_column/dense_features.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -90,7 +90,7 @@ def __init__(
trainable: Boolean, whether the layer's variables will be updated via
gradient descent during training.
name: Name to give to the DenseFeatures.
partitioner: Partitioner for input layer. Defaults to None.
partitioner: Partitioner for input layer. Defaults to `None`.
**kwargs: Keyword arguments to construct a layer.

Raises:
Expand Down Expand Up @@ -150,8 +150,8 @@ def call(self, features, cols_to_output_tensors=None, training=None):
method of any `FeatureColumn` that takes a `training` argument. For
example, if a `FeatureColumn` performed dropout, the column could
expose a `training` argument to control whether the dropout should
be applied. If `None`, defaults to
`tf.keras.backend.learning_phase()`.
be applied. If `None`, becomes `tf.keras.backend.learning_phase()`.
Defaults to `None`.


Returns:
Expand Down
4 changes: 2 additions & 2 deletions keras/feature_column/sequence_feature_column.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -122,8 +122,8 @@ def call(self, features, training=None):
method of any `FeatureColumn` that takes a `training` argument. For
example, if a `FeatureColumn` performed dropout, the column could
expose a `training` argument to control whether the dropout should
be applied. If `None`, defaults to
`tf.keras.backend.learning_phase()`.
be applied. If `None`, becomes `tf.keras.backend.learning_phase()`.
Defaults to `None`.
Returns:
Expand Down