Replace past with past_key_values (#20944)

* start cleanup

* more updates

* more models are affected

* more updates

* update generation utils

* style

* revert change that removed reorder cachce

* update generation utils

* style

* style

* remove reorder cache

templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_tf_{{cookiecutter.lowercase_modelname}}.py

@@ -1121,15 +1121,15 @@ class TF{{cookiecutter.camelcase_modelname}}ForCausalLM(TF{{cookiecutter.camelca
     def get_lm_head(self) -> tf.keras.layers.Layer:
         return self.mlm.predictions
 
-    def prepare_inputs_for_generation(self, inputs, past=None, attention_mask=None, **model_kwargs):
+    def prepare_inputs_for_generation(self, inputs, past_key_values=None, attention_mask=None, **model_kwargs):
         # cut decoder_input_ids if past is used
-        if past:
+        if past_key_values:
             inputs = tf.expand_dims(inputs[:, -1], -1)
 
         return {
             "input_ids": inputs,
             "attention_mask": attention_mask,
-            "past_key_values": past,
+            "past_key_values": past_key_values,
             "use_cache": model_kwargs["use_cache"],
         }
 
@@ -3003,7 +3003,7 @@ class TF{{cookiecutter.camelcase_modelname}}ForConditionalGeneration(TF{{cookiec
     def prepare_inputs_for_generation(
         self,
         decoder_input_ids,
-        past=None,
+        past_key_values=None,
         attention_mask=None,
         head_mask=None,
         decoder_head_mask=None,
@@ -3013,13 +3013,13 @@ class TF{{cookiecutter.camelcase_modelname}}ForConditionalGeneration(TF{{cookiec
         **kwargs
     ):
         # cut decoder_input_ids if past is used
-        if past is not None:
+        if past_key_values is not None:
             decoder_input_ids = decoder_input_ids[:, -1:]
 
         return {
             "input_ids": None,  # needs to be passed to make Keras.layer.__call__ happy
             "encoder_outputs": encoder_outputs,
-            "past_key_values": past,
+            "past_key_values": past_key_values,
             "decoder_input_ids": decoder_input_ids,
             "attention_mask": attention_mask,
             "head_mask": head_mask,

templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_{{cookiecutter.lowercase_modelname}}.py

@@ -1167,7 +1167,7 @@ class {{cookiecutter.camelcase_modelname}}ForCausalLM({{cookiecutter.camelcase_m
             cross_attentions=outputs.cross_attentions,
         )
 
-    def prepare_inputs_for_generation(self, input_ids, past=None, attention_mask=None, **model_kwargs):
+    def prepare_inputs_for_generation(self, input_ids, past_key_values=None, attention_mask=None, **model_kwargs):
         input_shape = input_ids.shape
 
         # if model is used as a decoder in encoder-decoder model, the decoder attention mask is created on the fly
@@ -1175,10 +1175,10 @@ class {{cookiecutter.camelcase_modelname}}ForCausalLM({{cookiecutter.camelcase_m
             attention_mask = input_ids.new_ones(input_shape)
 
         # cut decoder_input_ids if past is used
-        if past is not None:
+        if past_key_values is not None:
             input_ids = input_ids[:, -1:]
 
-        return {"input_ids": input_ids, "attention_mask": attention_mask, "past_key_values": past}
+        return {"input_ids": input_ids, "attention_mask": attention_mask, "past_key_values": past_key_values}
 
     def _reorder_cache(self, past, beam_idx):
         reordered_past = ()
@@ -2879,7 +2879,7 @@ class {{cookiecutter.camelcase_modelname}}ForConditionalGeneration({{cookiecutte
     def prepare_inputs_for_generation(
         self,
         decoder_input_ids,
-        past=None,
+        past_key_values=None,
         attention_mask=None,
         head_mask=None,
         decoder_head_mask=None,
@@ -2889,13 +2889,13 @@ class {{cookiecutter.camelcase_modelname}}ForConditionalGeneration({{cookiecutte
         **kwargs
     ):
         # cut decoder_input_ids if past is used
-        if past is not None:
+        if past_key_values is not None:
             decoder_input_ids = decoder_input_ids[:, -1:]
 
         return {
             "input_ids": None,  # encoder_outputs is defined. input_ids not needed
             "encoder_outputs": encoder_outputs,
-            "past_key_values": past,
+            "past_key_values": past_key_values,
             "decoder_input_ids": decoder_input_ids,
             "attention_mask": attention_mask,
             "head_mask": head_mask,
@@ -3328,7 +3328,7 @@ class {{cookiecutter.camelcase_modelname}}ForCausalLM({{cookiecutter.camelcase_m
             cross_attentions=outputs.cross_attentions,
         )
 
-    def prepare_inputs_for_generation(self, input_ids, past=None, attention_mask=None, use_cache=None, **kwargs):
+    def prepare_inputs_for_generation(self, input_ids, past_key_values=None, attention_mask=None, use_cache=None, **kwargs):
         # if model is used as a decoder in encoder-decoder model, the decoder attention mask is created on the fly
         if attention_mask is None:
             attention_mask = input_ids.new_ones(input_ids.shape)
@@ -3339,7 +3339,7 @@ class {{cookiecutter.camelcase_modelname}}ForCausalLM({{cookiecutter.camelcase_m
         return {
             "input_ids": input_ids,  # encoder_outputs is defined. input_ids not needed
             "attention_mask": attention_mask,
-            "past_key_values": past,
+            "past_key_values": past_key_values,
             "use_cache": use_cache,
         }