Use main in conversion script (#25973)

* fix

* fix

---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

src/transformers/models/falcon/convert_custom_code_checkpoint.py

@@ -9,52 +9,53 @@ library. After conversion, performance (especially for generation) should improv
 without needing trust_remote_code=True.
 """
 
-parser = ArgumentParser()
-parser.add_argument(
+if __name__ == "__main__":
+    parser = ArgumentParser()
+    parser.add_argument(
         "--checkpoint_dir",
         type=Path,
         required=True,
         help="Directory containing a custom code checkpoint to convert to a modern Falcon checkpoint.",
-)
-args = parser.parse_args()
+    )
+    args = parser.parse_args()
 
-if not args.checkpoint_dir.is_dir():
+    if not args.checkpoint_dir.is_dir():
         raise ValueError("--checkpoint_dir argument should be a directory!")
 
-if (
+    if (
         not (args.checkpoint_dir / "configuration_RW.py").is_file()
         or not (args.checkpoint_dir / "modelling_RW.py").is_file()
-):
+    ):
         raise ValueError(
             "The model directory should contain configuration_RW.py and modelling_RW.py files! Are you sure this is a custom code checkpoint?"
         )
-(args.checkpoint_dir / "configuration_RW.py").unlink()
-(args.checkpoint_dir / "modelling_RW.py").unlink()
+    (args.checkpoint_dir / "configuration_RW.py").unlink()
+    (args.checkpoint_dir / "modelling_RW.py").unlink()
 
-config = args.checkpoint_dir / "config.json"
-text = config.read_text()
-text = text.replace("RWForCausalLM", "FalconForCausalLM")
-text = text.replace("RefinedWebModel", "falcon")
-text = text.replace("RefinedWeb", "falcon")
-json_config = json.loads(text)
-del json_config["auto_map"]
+    config = args.checkpoint_dir / "config.json"
+    text = config.read_text()
+    text = text.replace("RWForCausalLM", "FalconForCausalLM")
+    text = text.replace("RefinedWebModel", "falcon")
+    text = text.replace("RefinedWeb", "falcon")
+    json_config = json.loads(text)
+    del json_config["auto_map"]
 
-if "n_head" in json_config:
+    if "n_head" in json_config:
         json_config["num_attention_heads"] = json_config.pop("n_head")
-if "n_layer" in json_config:
+    if "n_layer" in json_config:
         json_config["num_hidden_layers"] = json_config.pop("n_layer")
-if "n_head_kv" in json_config:
+    if "n_head_kv" in json_config:
         json_config["num_kv_heads"] = json_config.pop("n_head_kv")
         json_config["new_decoder_architecture"] = True
-else:
+    else:
         json_config["new_decoder_architecture"] = False
-bos_token_id = json_config.get("bos_token_id", 1)
-eos_token_id = json_config.get("eos_token_id", 2)
-config.unlink()
-config.write_text(json.dumps(json_config, indent=2, sort_keys=True))
+    bos_token_id = json_config.get("bos_token_id", 1)
+    eos_token_id = json_config.get("eos_token_id", 2)
+    config.unlink()
+    config.write_text(json.dumps(json_config, indent=2, sort_keys=True))
 
-tokenizer_config = args.checkpoint_dir / "tokenizer_config.json"
-if tokenizer_config.is_file():
+    tokenizer_config = args.checkpoint_dir / "tokenizer_config.json"
+    if tokenizer_config.is_file():
         text = tokenizer_config.read_text()
         json_config = json.loads(text)
         if json_config["tokenizer_class"] == "PreTrainedTokenizerFast":
@@ -62,12 +63,12 @@ if tokenizer_config.is_file():
             tokenizer_config.unlink()
             tokenizer_config.write_text(json.dumps(json_config, indent=2, sort_keys=True))
 
-generation_config_path = args.checkpoint_dir / "generation_config.json"
-generation_dict = {
+    generation_config_path = args.checkpoint_dir / "generation_config.json"
+    generation_dict = {
         "_from_model_config": True,
         "bos_token_id": bos_token_id,
         "eos_token_id": eos_token_id,
         "transformers_version": "4.33.0.dev0",
-}
-generation_config_path.write_text(json.dumps(generation_dict, indent=2, sort_keys=True))
-print("Done! Please double-check that the new checkpoint works as expected.")
+    }
+    generation_config_path.write_text(json.dumps(generation_dict, indent=2, sort_keys=True))
+    print("Done! Please double-check that the new checkpoint works as expected.")