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

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May 31, 2023
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[keras/feature_column] Standardise docstring usage of "Default to" #17958

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6 changes: 3 additions & 3 deletions keras/feature_column/dense_features.py
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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
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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