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[keras/applications/efficientnet.py] Standardise docstring usage of "Default to" #17758

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May 5, 2023
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[keras/applications/efficientnet.py] Standardise docstring usage of "Default to" #17758

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336f0ee
[keras/applications/convnext.py] Standardise docstring usage of "Defa…
SamuelMarks Apr 4, 2023
4107acf
[keras/applications/efficientnet.py] Standardise docstring usage of "…
SamuelMarks Apr 4, 2023
b391c10
[keras/applications/efficientnet.py] Remove {mode} from docstring
SamuelMarks Apr 6, 2023
7b1b04a
Merge branch 'master' into keras.applications.efficientnet
SamuelMarks Apr 23, 2023
f8622ce
[keras/applications/convnext.py] Revert changes to this file as this …
SamuelMarks Apr 23, 2023
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16 changes: 8 additions & 8 deletions keras/applications/efficientnet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -192,7 +192,7 @@

Args:
include_top: Whether to include the fully-connected
layer at the top of the network. Defaults to True.
layer at the top of the network. Defaults to `True`.
weights: One of `None` (random initialization),
'imagenet' (pre-training on ImageNet),
or the path to the weights file to be loaded. Defaults to 'imagenet'.
Expand All @@ -203,7 +203,7 @@
if `include_top` is False.
It should have exactly 3 inputs channels.
pooling: Optional pooling mode for feature extraction
when `include_top` is `False`. Defaults to None.
when `include_top` is `False`. Defaults to `None`.
- `None` means that the output of the model will be
the 4D tensor output of the
last convolutional layer.
Expand All @@ -215,8 +215,8 @@
be applied.
classes: Optional number of classes to classify images
into, only to be specified if `include_top` is True, and
if no `weights` argument is specified. Defaults to 1000 (number of
ImageNet classes).
if no `weights` argument is specified. 1000 is how many
ImageNet classes there are. Defaults to `1000`.
classifier_activation: A `str` or callable. The activation function to use
on the "top" layer. Ignored unless `include_top=True`. Set
`classifier_activation=None` to return the logits of the "top" layer.
Expand Down Expand Up @@ -852,10 +852,10 @@ def preprocess_input(x, data_format=None):

Args:
x: A floating point `numpy.array` or a `tf.Tensor`.
data_format: Optional data format of the image tensor/array. Defaults to
None, in which case the global setting
`tf.keras.backend.image_data_format()` is used (unless you changed it,
it defaults to "channels_last").{mode}
data_format: Optional data format of the image tensor/array. `None` means
the global setting `tf.keras.backend.image_data_format()` is used
(unless you changed it, it uses "channels_last").
Defaults to `None`.

Returns:
Unchanged `numpy.array` or `tf.Tensor`.
Expand Down