Merge pull request #1473 from rstudio/retether-3.6.0

Retether to Keras v3.6.0

Author: t-kalinowski

.tether/man/activation_elu.txt

@@ -3,7 +3,7 @@ keras.activations.elu(x, alpha=1.0)
 __doc__
 Exponential Linear Unit.
 
-The exponential linear unit (ELU) with `alpha > 0` is define as:
+The exponential linear unit (ELU) with `alpha > 0` is defined as:
 
 - `x` if `x > 0`
 - alpha * `exp(x) - 1` if `x < 0`
@@ -23,3 +23,4 @@ Args:
 Reference:
 
 - [Clevert et al., 2016](https://arxiv.org/abs/1511.07289)
+

.tether/man/application_densenet121.txt

@@ -53,7 +53,7 @@ Args:
             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.
+        if no `weights` argument is specified. Defaults to 1000.
     classifier_activation: A `str` or callable.
         The activation function to use
         on the "top" layer. Ignored unless `include_top=True`. Set

.tether/man/application_densenet169.txt

@@ -53,7 +53,7 @@ Args:
             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.
+        if no `weights` argument is specified. Defaults to 1000.
     classifier_activation: A `str` or callable.
         The activation function to use
         on the "top" layer. Ignored unless `include_top=True`. Set

.tether/man/application_densenet201.txt

@@ -53,7 +53,7 @@ Args:
             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.
+        if no `weights` argument is specified. Defaults to 1000.
     classifier_activation: A `str` or callable.
         The activation function to use
         on the "top" layer. Ignored unless `include_top=True`. Set

.tether/man/application_resnet101.txt

@@ -53,7 +53,7 @@ Args:
         - `max` means that global max pooling will 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.
+        specified. 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.

.tether/man/application_resnet152.txt

@@ -53,7 +53,7 @@ Args:
         - `max` means that global max pooling will 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.
+        specified. 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.

.tether/man/application_resnet50.txt

@@ -53,7 +53,7 @@ Args:
         - `max` means that global max pooling will 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.
+        specified. 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.

.tether/man/application_xception.txt

@@ -59,7 +59,7 @@ Args:
             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.
+        if no `weights` argument is specified. 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"

.tether/man/clone_model.txt

@@ -87,7 +87,7 @@ def clone_function(layer):
         config["seed"] = 1337
     return layer.__class__.from_config(config)
 
-new_model = clone_model(model)
+new_model = clone_model(model, clone_function=clone_function)
 ```
 
 Using a `call_function` to add a `Dropout` layer after each `Dense` layer

.tether/man/export_savedmodel.keras.src.models.model.Model.txt

@@ -2,7 +2,8 @@ __signature__
 keras.Model.export(
   self,
   filepath,
-  format='tf_saved_model'
+  format='tf_saved_model',
+  verbose=True
 )
 __doc__
 Create a TF SavedModel artifact for inference.
@@ -22,6 +23,7 @@ entirely standalone.
 Args:
     filepath: `str` or `pathlib.Path` object. Path where to save
         the artifact.
+    verbose: whether to print all the variables of the exported model.
 
 Example: