[tokenizer] Recover accidentally deleted file (#3311)

extensions/tokenizers/src/main/python/djl_converter/model_converter.py

@@ -0,0 +1,64 @@
+#!/usr/bin/env python
+#
+# Copyright 2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file
+# except in compliance with the License. A copy of the License is located at
+#
+# http://aws.amazon.com/apache2.0/
+#
+# or in the "LICENSE.txt" file accompanying this file. This file is distributed on an "AS IS"
+# BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, express or implied. See the License for
+# the specific language governing permissions and limitations under the License.
+import logging
+import os
+import sys
+
+from huggingface_hub import HfApi
+
+sys.path.append(os.path.dirname(os.path.realpath(__file__)))
+
+from djl_converter.arg_parser import converter_args
+
+
+def main():
+    logging.basicConfig(stream=sys.stdout,
+                        format="%(message)s",
+                        level=logging.INFO)
+    args = converter_args()
+
+    output_dir = args.output_dir
+    if output_dir == ".":
+        output_dir = f"model/{args.model_id.split('/')[-1]}"
+
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    if os.listdir(output_dir):
+        logging.error(f"output directory: {output_dir} is not empty.")
+        return
+
+    api = HfApi()
+    model_info = api.model_info(args.model_id,
+                                revision=args.revision,
+                                token=args.token)
+
+    from djl_converter.huggingface_models import HuggingfaceModels, SUPPORTED_TASKS
+
+    task, arch = HuggingfaceModels.to_supported_task(model_info.config)
+    converter = SUPPORTED_TASKS[task]
+
+    try:
+        result, reason, _ = converter.save_model(model_info, args, output_dir,
+                                                 False)
+        if result:
+            logging.info(f"Convert model {model_info.modelId} finished.")
+        else:
+            logging.error(f"{model_info.modelId}: {reason}")
+    except Exception as e:
+        logging.warning(f"Failed to convert model: {model_info.modelId}.")
+        logging.warning(e, exc_info=True)
+
+
+if __name__ == "__main__":
+    main()