Update the template

huggingface · Jan 26, 2021 · f9303d1 · f9303d1
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Showing 2 changed files with 34 additions and 12 deletions.
diff --git a/src/transformers/models/pegasus/modeling_tf_pegasus.py b/src/transformers/models/pegasus/modeling_tf_pegasus.py
@@ -601,6 +601,10 @@ def serving(self, inputs):
             output_attentions (:obj:`bool`, `optional`): Whether or not to return the attentions tensors of all
             attention layers. See ``attentions`` under returned tensors for more detail. This argument can be used only
             in eager mode, in graph mode the value in the config will be used instead.
+        output_attentions (:obj:`bool`, `optional`):
+            Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned
+            tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the
+            config will be used instead.
         output_hidden_states (:obj:`bool`, `optional`):
             Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors for
             more detail. This argument can be used only in eager mode, in graph mode the value in the config will be

diff --git a/...r-template-{{cookiecutter.modelname}}/modeling_tf_{{cookiecutter.lowercase_modelname}}.py b/...r-template-{{cookiecutter.modelname}}/modeling_tf_{{cookiecutter.lowercase_modelname}}.py
@@ -778,12 +778,15 @@ class TF{{cookiecutter.camelcase_modelname}}PreTrainedModel(TFPreTrainedModel):
             vectors than the model's internal embedding lookup matrix.
         output_attentions (:obj:`bool`, `optional`):
             Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned
-            tensors for more detail.
+            tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the
+            config will be used instead.
         output_hidden_states (:obj:`bool`, `optional`):
             Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors for
-            more detail.
+            more detail. This argument can be used only in eager mode, in graph mode the value in the config will be
+            used instead.
         return_dict (:obj:`bool`, `optional`):
-            Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple.
+            Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple. This
+            argument can be used in eager mode, in graph mode the value will always be set to True.
         training (:obj:`bool`, `optional`, defaults to :obj:`False`):
             Whether or not to use the model in training mode (some modules like dropout modules have different
             behaviors between training and evaluation).
@@ -2016,12 +2019,15 @@ def serving(self, inputs):
             decoding (see :obj:`past_key_values`). Set to :obj:`False` during training, :obj:`True` during generation
         output_attentions (:obj:`bool`, `optional`):
             Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned
-            tensors for more detail.
+            tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the
+            config will be used instead.
         output_hidden_states (:obj:`bool`, `optional`):
             Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors for
-            more detail.
+            more detail. This argument can be used only in eager mode, in graph mode the value in the config will be
+            used instead.
         return_dict (:obj:`bool`, `optional`):
-            Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple.
+            Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple. This
+            argument can be used in eager mode, in graph mode the value will always be set to True.
         training (:obj:`bool`, `optional`, defaults to :obj:`False`):
             Whether or not to use the model in training mode (some modules like dropout modules have different
             behaviors between training and evaluation).
@@ -2100,12 +2106,18 @@ def call(
                 into associated vectors than the model's internal embedding lookup matrix.
             output_attentions (:obj:`bool`, `optional`):
                 Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under
-                returned tensors for more detail.
+                returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value
+                in the config will be used instead.
             output_hidden_states (:obj:`bool`, `optional`):
                 Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors
-                for more detail.
+                for more detail. This argument can be used only in eager mode, in graph mode the value in the config
+                will be used instead.
             return_dict (:obj:`bool`, `optional`):
-                Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple.
+                Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple. This
+                argument can be used in eager mode, in graph mode the value will always be set to True.
+            training (:obj:`bool`, `optional`, defaults to :obj:`False`):
+                Whether or not to use the model in training mode (some modules like dropout modules have different
+                behaviors between training and evaluation).
         """
         inputs = input_processing(
             func=self.call,
@@ -2263,12 +2275,18 @@ def call(
                 into associated vectors than the model's internal embedding lookup matrix.
             output_attentions (:obj:`bool`, `optional`):
                 Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under
-                returned tensors for more detail.
+                returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value
+                in the config will be used instead.
             output_hidden_states (:obj:`bool`, `optional`):
                 Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors
-                for more detail.
+                for more detail. This argument can be used only in eager mode, in graph mode the value in the config
+                will be used instead.
             return_dict (:obj:`bool`, `optional`):
-                Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple.
+                Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple. This
+                argument can be used in eager mode, in graph mode the value will always be set to True.
+            training (:obj:`bool`, `optional`, defaults to :obj:`False`):
+                Whether or not to use the model in training mode (some modules like dropout modules have different
+                behaviors between training and evaluation).
         """
         inputs = input_processing(
             func=self.call,