#PRIVATE_TF_API_USAGE_CLEANUP Remove the usage of gather_non_trainable_weights. There is no reference to this method, so we just delete the method.

PiperOrigin-RevId: 353274439
Change-Id: I876eac533fd6a68912900118b4159651741e7978

tensorflow/python/keras/utils/layer_utils.py

@@ -299,38 +299,6 @@ def gather_trainable_weights(trainable, sub_layers, extra_variables):
   return weights + trainable_extra_variables
 
 
-def gather_non_trainable_weights(trainable, sub_layers, extra_variables):
-  """Lists the non-trainable weights for an object with sub-layers.
-
-  Args:
-    trainable: Whether the object collecting the variables is trainable.
-    sub_layers: A flat list of Layer objects owned by this object, to collect
-      variables from.
-    extra_variables: Any extra variables to include. Their `.trainable` property
-      is used to categorize them.
-
-  Returns:
-    A list of collected non-trainable weights/variables.
-  """
-  trainable_extra_variables = []
-  non_trainable_extra_variables = []
-  for v in extra_variables:
-    if v.trainable:
-      trainable_extra_variables.append(v)
-    else:
-      non_trainable_extra_variables.append(v)
-  weights = []
-  for layer in sub_layers:
-    weights += layer.non_trainable_weights
-  if not trainable:
-    trainable_weights = []
-    for layer in sub_layers:
-      trainable_weights += layer.trainable_weights
-    return (trainable_weights + trainable_extra_variables
-            + weights + non_trainable_extra_variables)
-  return weights + non_trainable_extra_variables
-
-
 def convert_dense_weights_data_format(dense,
                                       previous_feature_map_shape,
                                       target_data_format='channels_first'):

tensorflow/python/training/tracking/layer_utils.py

@@ -179,35 +179,3 @@ def gather_trainable_weights(trainable, sub_layers, extra_variables):
   trainable_extra_variables = [
       v for v in extra_variables if v.trainable]
   return weights + trainable_extra_variables
-
-
-def gather_non_trainable_weights(trainable, sub_layers, extra_variables):
-  """Lists the non-trainable weights for an object with sub-layers.
-
-  Args:
-    trainable: Whether the object collecting the variables is trainable.
-    sub_layers: A flat list of Layer objects owned by this object, to collect
-      variables from.
-    extra_variables: Any extra variables to include. Their `.trainable` property
-      is used to categorize them.
-
-  Returns:
-    A list of collected non-trainable weights/variables.
-  """
-  trainable_extra_variables = []
-  non_trainable_extra_variables = []
-  for v in extra_variables:
-    if v.trainable:
-      trainable_extra_variables.append(v)
-    else:
-      non_trainable_extra_variables.append(v)
-  weights = []
-  for layer in sub_layers:
-    weights += layer.non_trainable_weights
-  if not trainable:
-    trainable_weights = []
-    for layer in sub_layers:
-      trainable_weights += layer.trainable_weights
-    return (trainable_weights + trainable_extra_variables
-            + weights + non_trainable_extra_variables)
-  return weights + non_trainable_extra_variables