feat: update ._contrastive(streamer)

Author: dmarx

src/transformers/generation/utils.py

@@ -2818,8 +2818,6 @@ def _contrastive_search(
 
             # Rebuilds the relevant parts of the model output for the selected token, for use in the next iteration
             if self.config.is_encoder_decoder:
-                next_step_cross_attentions = ()
-                next_step_decoder_attentions = ()
                 if output_attentions:
                     for layer in outputs.cross_attentions:
                         layer = torch.stack(torch.split(layer, top_k, dim=0))[range(batch_size), selected_idx, ...]
@@ -2856,7 +2854,21 @@ def _contrastive_search(
             # update generated ids, model inputs, and length for next step
             input_ids = torch.cat([input_ids, next_tokens[:, None]], dim=-1)
             if streamer is not None:
-                streamer.put(next_tokens.cpu())
+                output_stub = self._prepare_output(
+                    return_dict_in_generate=return_dict_in_generate,
+                    sequences=next_tokens,
+                    scores=(processed_logit_for_next_step,),  # (scores,),
+                    logits=(processed_logit_for_next_step,),
+                    # I think there's an issue with the contrastive sampling implementation that is currently returning the same values for logits as scores    #(logits[selected_idx,:],), #(logit_for_next_step,), # `logit_for_next_step`: values don't match, `logits`: shapes don't match
+                    encoder_attentions=None,  # probably doesn't make sense to stream this
+                    encoder_hidden_states=None,  # probably doesn't make sense to stream this
+                    decoder_attentions=(next_step_decoder_attentions,),
+                    # ([0],),# very concerning that if I set this to `([0],)` my tests don't fail
+                    cross_attentions=(next_step_cross_attentions,),
+                    decoder_hidden_states=(next_decoder_hidden_states,),
+                    past_key_values=None,  # probably doesn't make sense to stream this
+                )
+                streamer.put(output_stub)
             model_kwargs = self._update_model_kwargs_for_generation(
                 outputs,
                 model_kwargs,