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Make Fuzzy Gdown Argument Version-dependent #8986

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Make Fuzzy Gdown Argument Version-dependent #8986

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78312f6
Make Fuzzy Gdown Argument Version-dependent
ericspod Jul 9, 2026
5354e61
Merge branch 'dev' into fuzzy_fix
ericspod Jul 9, 2026
9a5395b
Fix
ericspod Jul 9, 2026
5a973c2
Fix
ericspod Jul 9, 2026
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2 changes: 1 addition & 1 deletion monai/apps/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -240,7 +240,7 @@ def download_url(
if urlparse(url).netloc == "drive.google.com":
if not has_gdown:
raise RuntimeError("To download files from Google Drive, please install the gdown dependency.")
if "fuzzy" not in gdown_kwargs:
if "fuzzy" not in gdown_kwargs and not min_version(gdown, "6.0.0"): # "fuzzy" dropped in gdown 6.0.0
gdown_kwargs["fuzzy"] = True # default to true for flexible url
gdown.download(url, f"{tmp_name}", quiet=not progress, **gdown_kwargs)
elif urlparse(url).netloc == "cloud-api.yandex.net":
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1 change: 0 additions & 1 deletion monai/bundle/scripts.py
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Expand Up @@ -2005,7 +2005,6 @@ def download_large_files(bundle_path: str | None = None, large_file_name: str |
parser.read_config(large_file_path)
large_files_list = parser.get()["large_files"]
for lf_data in large_files_list:
lf_data["fuzzy"] = True
if "hash_val" in lf_data and lf_data.get("hash_val", "") == "":
lf_data.pop("hash_val")
if "hash_type" in lf_data and lf_data.get("hash_type", "") == "":
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4 changes: 2 additions & 2 deletions monai/networks/nets/hovernet.py
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Expand Up @@ -632,7 +632,7 @@ def _remap_preact_resnet_model(model_url: str):
pattern_bna = re.compile(r"^(.+\.d\d+)\.blk_bna\.(.+)")
# download the pretrained weights into torch hub's default dir
weights_dir = os.path.join(torch.hub.get_dir(), "preact-resnet50.pth")
download_url(model_url, fuzzy=True, filepath=weights_dir, progress=False)
download_url(model_url, filepath=weights_dir, progress=False)
map_location = None if torch.cuda.is_available() else torch.device("cpu")
state_dict = torch.load(weights_dir, map_location=map_location, weights_only=True)["desc"]

Expand Down Expand Up @@ -667,7 +667,7 @@ def _remap_standard_resnet_model(model_url: str, state_dict_key: str | None = No
pattern_downsample1 = re.compile(r"^(res_blocks.d\d+).+\.downsample\.1\.(.+)")
# download the pretrained weights into torch hub's default dir
weights_dir = os.path.join(torch.hub.get_dir(), "resnet50.pth")
download_url(model_url, fuzzy=True, filepath=weights_dir, progress=False)
download_url(model_url, filepath=weights_dir, progress=False)
map_location = None if torch.cuda.is_available() else torch.device("cpu")
state_dict = torch.load(weights_dir, map_location=map_location, weights_only=True)
if state_dict_key is not None:
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