Add ResNet-RS to keras.applications - code refactor 4
@@ -187,7 +187,7 @@ BASE_DOCSTRING = """Instantiates the {name} architecture.
`classifier_activation=None` to return the logits of the "top" layer.
include_preprocessing: Boolean, whether to include the preprocessing layer
(`Rescaling`) at the bottom of the network. Defaults to `True`.
- Note: if weights are 'imagenet' then Input image is normalized by ImageNet mean and standard deviation.
+ Note: Input image is normalized by ImageNet mean and standard deviation.
Returns:
A `keras.Model` instance.
@@ -564,7 +564,7 @@ def ResNetRS(
`classifier_activation=None` to return the logits of the "top" layer.
include_preprocessing: Boolean, whether to include the preprocessing layer
(`Rescaling`) at the bottom of the network. Defaults to `True`.
- Note: if weights are 'imagenet' then Input image is normalized by ImageNet mean and standard deviation.
+ Note: Input image is normalized by ImageNet mean and standard deviation.
Returns:
A `tf.keras.Model` instance.
