From f57489f73c61f875bb207b0767e83d9f91552295 Mon Sep 17 00:00:00 2001 From: Henk Date: Tue, 31 Jan 2023 18:46:59 +0100 Subject: [PATCH] Revision Cleanup --- utils.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/utils.py b/utils.py index 45a7817f..aa37028e 100644 --- a/utils.py +++ b/utils.py @@ -286,7 +286,7 @@ def _transformers22_aria2_hook(pretrained_model_name_or_path: str, force_downloa if token is None: raise EnvironmentError("You specified use_auth_token=True, but a huggingface token was not found.") _cache_dir = str(cache_dir) if cache_dir is not None else transformers.TRANSFORMERS_CACHE - _revision = args.revision if args.revision is not None else huggingface_hub.constants.DEFAULT_REVISION + _revision = revision if revision is not None else huggingface_hub.constants.DEFAULT_REVISION sharded = False headers = {"user-agent": transformers.file_utils.http_user_agent(user_agent)} if use_auth_token: @@ -297,7 +297,7 @@ def _transformers22_aria2_hook(pretrained_model_name_or_path: str, force_downloa def is_cached(filename): try: - huggingface_hub.hf_hub_download(pretrained_model_name_or_path, filename, cache_dir=cache_dir, local_files_only=True, revision=_revision) + huggingface_hub.hf_hub_download(pretrained_model_name_or_path, filename, cache_dir=cache_dir, local_files_only=True, revision=revision) except ValueError: return False return True @@ -306,7 +306,7 @@ def _transformers22_aria2_hook(pretrained_model_name_or_path: str, force_downloa filename = transformers.modeling_utils.WEIGHTS_INDEX_NAME if sharded else transformers.modeling_utils.WEIGHTS_NAME except AttributeError: return - url = huggingface_hub.hf_hub_url(pretrained_model_name_or_path, filename, revision=_revision) + url = huggingface_hub.hf_hub_url(pretrained_model_name_or_path, filename, revision=revision) if is_cached(filename) or requests.head(url, allow_redirects=True, proxies=proxies, headers=headers): break if sharded: @@ -316,11 +316,11 @@ def _transformers22_aria2_hook(pretrained_model_name_or_path: str, force_downloa if not sharded: # If the model has a pytorch_model.bin file, that's the only file to download filenames = [transformers.modeling_utils.WEIGHTS_NAME] else: # Otherwise download the pytorch_model.bin.index.json and then let aria2 download all the pytorch_model-#####-of-#####.bin files mentioned inside it - map_filename = huggingface_hub.hf_hub_download(pretrained_model_name_or_path, filename, cache_dir=cache_dir, force_download=force_download, proxies=proxies, resume_download=resume_download, use_auth_token=use_auth_token, user_agent=user_agent) + map_filename = huggingface_hub.hf_hub_download(pretrained_model_name_or_path, filename, cache_dir=cache_dir, force_download=force_download, proxies=proxies, resume_download=resume_download, use_auth_token=use_auth_token, user_agent=user_agent, revision=revision) with open(map_filename) as f: map_data = json.load(f) filenames = set(map_data["weight_map"].values()) - urls = [huggingface_hub.hf_hub_url(pretrained_model_name_or_path, n, revision=_revision) for n in filenames] + urls = [huggingface_hub.hf_hub_url(pretrained_model_name_or_path, n, revision=revision) for n in filenames] if not force_download: urls = [u for u, n in zip(urls, filenames) if not is_cached(n)] if not urls: