[Pretrained Model] Add resize_position_embeddings (#13559)

* finish

* delete bogus file

* correct some stuff

* finish

* finish

examples/pytorch/summarization/run_summarization.py

@@ -99,6 +99,13 @@ class ModelArguments:
             "with private models)."
         },
     )
+    resize_position_embeddings: Optional[bool] = field(
+        default=None,
+        metadata={
+            "help": "Whether to automatically resize the position embeddings if `max_source_length` exceeds "
+            "the model's position embeddings."
+        },
+    )
 
 
 @dataclass
@@ -366,6 +373,25 @@ def main():
     if model.config.decoder_start_token_id is None:
         raise ValueError("Make sure that `config.decoder_start_token_id` is correctly defined")
 
+    if (
+        hasattr(model.config, "max_position_embeddings")
+        and model.config.max_position_embeddings < data_args.max_source_length
+    ):
+        if model_args.resize_position_embeddings is None:
+            logger.warning(
+                f"Increasing the model's number of position embedding vectors from {model.config.max_position_embedding} "
+                f"to {data_args.max_source_length}."
+            )
+            model.resize_position_embeddings(data_args.max_source_length)
+        elif model_args.resize_position_embeddings:
+            model.resize_position_embeddings(data_args.max_source_length)
+        else:
+            raise ValueError(
+                f"`--max_source_length` is set to {data_args.max_source_length}, but the model only has {model.config.max_position_embeddings}"
+                f" position encodings. Consider either reducing `--max_source_length` to {model.config.max_position_embeddings} or to automatically "
+                "resize the model's position encodings by passing `--resize_position_embeddings`."
+            )
+
     prefix = data_args.source_prefix if data_args.source_prefix is not None else ""
 
     # Preprocessing the datasets.