New serving (#9419)

* Add a serving method

* Add albert

* Add serving for BERT and BART

* Add more models

* Finish the serving addition

* Temp fix

* Restore DPR

* Fix funnel attribute

* Fix attributes GPT2

* Fix OpenAIGPT attribute

* Fix T5 attributes

* Fix Bart attributes

* Fix TransfoXL attributes

* Add versioning

* better test

* Update template

* Fix Flaubert

* Fix T5

* Apply style

* Remove unused imports

* Deactivate extra parameters

* Remove too long test + saved_model default to False

* Ignore the saved model test for some models

* Fix some inputs

* Fix mpnet serving

* Trigger CI

* Address all comments

src/transformers/models/ctrl/modeling_tf_ctrl.py

@@ -594,6 +594,18 @@ class TFCTRLModel(TFCTRLPreTrainedModel):
         )
         return outputs
 
+    def serving_output(self, output):
+        pkv = tf.convert_to_tensor(output.past_key_values) if self.config.use_cache else None
+        hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None
+        attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None
+
+        return TFBaseModelOutputWithPast(
+            last_hidden_state=output.last_hidden_state,
+            past_key_values=pkv,
+            hidden_states=hs,
+            attentions=attns,
+        )
+
 
 class TFCTRLLMHead(tf.keras.layers.Layer):
     def __init__(self, config, input_embeddings, **kwargs):
@@ -729,6 +741,18 @@ class TFCTRLLMHeadModel(TFCTRLPreTrainedModel, TFCausalLanguageModelingLoss):
             attentions=transformer_outputs.attentions,
         )
 
+    def serving_output(self, output):
+        pkv = tf.convert_to_tensor(output.past_key_values) if self.config.use_cache else None
+        hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None
+        attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None
+
+        return TFCausalLMOutputWithPast(
+            logits=output.logits,
+            past_key_values=pkv,
+            hidden_states=hs,
+            attentions=attns,
+        )
+
 
 @add_start_docstrings(
     """
@@ -885,3 +909,13 @@ class TFCTRLForSequenceClassification(TFCTRLPreTrainedModel, TFSequenceClassific
             hidden_states=transformer_outputs.hidden_states,
             attentions=transformer_outputs.attentions,
         )
+
+    def serving_output(self, output):
+        hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None
+        attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None
+
+        return TFSequenceClassifierOutput(
+            logits=output.logits,
+            hidden_states=hs,
+            attentions=attns,
+        )