TF - update (vision_)encoder_decoder past variable (#16260)

src/transformers/models/encoder_decoder/modeling_tf_encoder_decoder.py

@@ -647,19 +647,17 @@ class TFEncoderDecoderModel(TFPreTrainedModel, TFCausalLanguageModelingLoss):
         # The starting index of the remaining elements in `decoder_outputs`
         start_index = sum([1 if x is not None else 0 for x in (loss, logits, past_key_values)])
 
-        past = (encoder_outputs[0], past_key_values) if past_key_values else None
-
         if not decoder_inputs["return_dict"]:
             if not isinstance(encoder_outputs, tuple):
                 encoder_outputs = encoder_outputs.to_tuple()
-            output = (loss, logits, past) + decoder_outputs[start_index:] + encoder_outputs
+            output = (loss, logits, past_key_values) + decoder_outputs[start_index:] + encoder_outputs
             output = tuple([x for x in output if x is not None])
             return output
 
         return TFSeq2SeqLMOutput(
             loss=loss,
             logits=decoder_outputs.logits,
-            past_key_values=past,
+            past_key_values=past_key_values,
             decoder_hidden_states=decoder_outputs.hidden_states,
             decoder_attentions=decoder_outputs.attentions,
             cross_attentions=decoder_outputs.cross_attentions,

src/transformers/models/vision_encoder_decoder/modeling_tf_vision_encoder_decoder.py

@@ -678,19 +678,17 @@ class TFVisionEncoderDecoderModel(TFPreTrainedModel, TFCausalLanguageModelingLos
         # The starting index of the remaining elements in `decoder_outputs`
         start_index = sum([1 if x is not None else 0 for x in (loss, logits, past_key_values)])
 
-        past = (encoder_outputs[0], past_key_values) if past_key_values else None
-
         if not decoder_inputs["return_dict"]:
             if not isinstance(encoder_outputs, tuple):
                 encoder_outputs = encoder_outputs.to_tuple()
-            output = (loss, logits, past) + decoder_outputs[start_index:] + encoder_outputs
+            output = (loss, logits, past_key_values) + decoder_outputs[start_index:] + encoder_outputs
             output = tuple([x for x in output if x is not None])
             return output
 
         return TFSeq2SeqLMOutput(
             loss=loss,
             logits=decoder_outputs.logits,
-            past_key_values=past,
+            past_key_values=past_key_values,
             decoder_hidden_states=decoder_outputs.hidden_states,
             decoder_attentions=decoder_outputs.attentions,
             cross_attentions=decoder_outputs.cross_attentions,