[Fix Download] update converted logic & fix hf hub download subfolder bug (#7911)

* update converted logic & fix hf hub download subfolder bug

Author: JunnYu

paddlenlp/transformers/model_utils.py

@@ -52,7 +52,7 @@
 from paddle.utils.download import is_url as is_remote_url
 from tqdm.auto import tqdm
 
-from paddlenlp.utils.downloader import get_path_from_url_with_filelock, hf_file_exists
+from paddlenlp.utils.downloader import get_path_from_url_with_filelock
 from paddlenlp.utils.env import (
     CONFIG_NAME,
     LEGACY_CONFIG_NAME,
@@ -367,28 +367,7 @@ def resolve_weight_file_from_hf_hub(repo_id: str, cache_dir: str, support_conver
         support_conversion (bool): whether support converting pytorch weight file to paddle weight file
         subfolder (str, optional) An optional value corresponding to a folder inside the repo.
     """
-    is_local = os.path.isdir(repo_id)
-    if not is_local:
-        if hf_file_exists(repo_id, PADDLE_WEIGHTS_NAME, subfolder=subfolder):
-            file_name = PADDLE_WEIGHTS_NAME
-            assert (
-                support_conversion is False
-            ), "Please call set convert_from_torch for paddle weights on huggingface hub, eg. Model.from_pretrained(model_name, from_hf_hub=True, convert_from_torch=False)"
-        elif hf_file_exists(repo_id, PYTORCH_WEIGHTS_NAME, subfolder=subfolder):
-            if not support_conversion:
-                raise EntryNotFoundError(
-                    f"can not download `{PADDLE_WEIGHTS_NAME} from https://huggingface.co/{repo_id}` "
-                    "and current model doesn't support conversion from pytorch weight file to paddle weight file"
-                )
-            file_name = PYTORCH_WEIGHTS_NAME
-        else:
-            raise EntryNotFoundError(
-                message=f"can not find the paddle/pytorch weight file from: https://huggingface.co/{repo_id}",
-                response=None,
-            )
-    else:
-        # for local file, we use support_conversion to select paddle or torch weight.
-        file_name = PYTORCH_WEIGHTS_NAME if support_conversion else PADDLE_WEIGHTS_NAME
+    file_name = PYTORCH_WEIGHTS_NAME if support_conversion else PADDLE_WEIGHTS_NAME
 
     file_name_list = [SAFE_WEIGHTS_NAME] + [file_name] + [PYTORCH_WEIGHTS_INDEX_NAME] + [SAFE_WEIGHTS_INDEX_NAME]
     resolved_file = None
@@ -2156,12 +2135,31 @@ def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs):
                     or resolved_archive_file.endswith(SAFE_WEIGHTS_NAME)
                     or resolved_archive_file.endswith(SAFE_WEIGHTS_INDEX_NAME)
                 ):
-                    # try to get the name-mapping info
-                    logger.info(
-                        f"Starting to convert pytorch weight file<{resolved_archive_file}> to "
-                        f"paddle weight file<{os.path.join(cache_dir, PADDLE_WEIGHTS_NAME)}> ..."
+                    converted_paddle_weights = os.path.join(
+                        os.path.dirname(resolved_archive_file), PADDLE_WEIGHTS_NAME
                     )
-                    state_dict = cls.convert(resolved_archive_file, config, cache_dir)
+                    if not os.path.exists(converted_paddle_weights):
+                        # try to get the name-mapping info
+                        logger.info(
+                            f"Starting to convert pytorch weight file <{resolved_archive_file}> to "
+                            f"paddle weight file <{converted_paddle_weights}> ..."
+                        )
+                        state_dict = cls.convert(resolved_archive_file, config, os.path.dirname(resolved_archive_file))
+                    else:
+                        # try to load the converted paddle weight file
+                        resolved_archive_file = converted_paddle_weights
+                        sharded_metadata = None
+                        is_sharded = False
+                        logger.info(
+                            f"Detect the converted Paddle weight file <{converted_paddle_weights}>. We intend to reuse this file."
+                        )
+                        if config.tensor_parallel_degree > 1 and resolved_archive_file.endswith(
+                            "model_state.pdparams"
+                        ):
+                            state_dict = cls.convert_tensor_parallel(resolved_archive_file, config)
+                        else:
+                            state_dict = load_state_dict(resolved_archive_file)
+                        logger.info("Loaded weights file from disk, setting weights to model.")
                 else:
                     raise ValueError(f"Unexpected file: {resolved_archive_file} for weight conversion.")
             else:

paddlenlp/transformers/utils.py

@@ -587,7 +587,7 @@ def cached_file_for_hf_hub(
         download_check(path_or_repo_id, full_filename, addition="from_hf_hub")
         resolved_file = hf_hub_download(
             repo_id=path_or_repo_id,
-            filename=full_filename,
+            filename=filename,
             cache_dir=cache_dir,
             subfolder=subfolder,
             library_name="PaddleNLP",