From 5732a8f15a9af40f58c13a741b14cd72a0811d90 Mon Sep 17 00:00:00 2001
From: Gnome Ann <>
Date: Wed, 11 May 2022 14:40:31 -0400
Subject: [PATCH] Don't use `aria2_hook()` if `force_download=True` is used

---
 utils.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/utils.py b/utils.py
index 38066ed0..7295c677 100644
--- a/utils.py
+++ b/utils.py
@@ -1,4 +1,4 @@
-from threading import Timer
+from threading import Timer, local
 import re
 import shutil
 import json
@@ -141,7 +141,9 @@ def aria2_hook(pretrained_model_name_or_path: str, force_download=False, cache_d
     from huggingface_hub import HfFolder
     if shutil.which("aria2c") is None:  # Don't do anything if aria2 is not installed
         return
-    if os.path.isdir(pretrained_model_name_or_path) or os.path.isfile(pretrained_model_name_or_path) or transformers.modeling_utils.is_remote_url(pretrained_model_name_or_path) or os.path.isfile(pretrained_model_name_or_path + ".index"):
+    if local_files_only:  # If local_files_only is true, we obviously don't need to download anything
+        return
+    if os.path.isdir(pretrained_model_name_or_path) or os.path.isfile(pretrained_model_name_or_path) or os.path.isfile(pretrained_model_name_or_path + ".index") or transformers.modeling_utils.is_remote_url(pretrained_model_name_or_path):
         return
     if proxies:
         print("WARNING:  KoboldAI does not support using aria2 to download models from huggingface.co through a proxy.  Disabling aria2 download mode.")
@@ -179,7 +181,7 @@ def aria2_hook(pretrained_model_name_or_path: str, force_download=False, cache_d
     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 = transformers.file_utils.cached_path(url, cache_dir=cache_dir, force_download=force_download, proxies=proxies, resume_download=resume_download, local_files_only=local_files_only, use_auth_token=use_auth_token, user_agent=user_agent)
+        map_filename = transformers.file_utils.cached_path(url, cache_dir=cache_dir, force_download=force_download, proxies=proxies, resume_download=resume_download, use_auth_token=use_auth_token, user_agent=user_agent)
         with open(map_filename) as f:
             map_data = json.load(f)
         filenames = set(map_data["weight_map"].values())