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5 changes: 2 additions & 3 deletions src/diffusers/loaders/lora_base.py
Original file line number Diff line number Diff line change
Expand Up @@ -277,15 +277,14 @@ def _fetch_state_dict(
def _best_guess_weight_name(
pretrained_model_name_or_path_or_dict, file_extension=".safetensors", local_files_only=False
):
if local_files_only or HF_HUB_OFFLINE:
raise ValueError("When using the offline mode, you must specify a `weight_name`.")

targeted_files = []

if os.path.isfile(pretrained_model_name_or_path_or_dict):
return
elif os.path.isdir(pretrained_model_name_or_path_or_dict):
targeted_files = [f for f in os.listdir(pretrained_model_name_or_path_or_dict) if f.endswith(file_extension)]
elif local_files_only or HF_HUB_OFFLINE:
raise ValueError("When using the offline mode, you must specify a `weight_name`.")
else:
files_in_repo = model_info(pretrained_model_name_or_path_or_dict).siblings
targeted_files = [f.rfilename for f in files_in_repo if f.rfilename.endswith(file_extension)]
Expand Down
88 changes: 88 additions & 0 deletions tests/lora/test_lora_base.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,88 @@
# coding=utf-8
# Copyright 2026 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import tempfile
import unittest
from pathlib import Path
from unittest.mock import patch

import torch
from safetensors.torch import save_file

from diffusers.loaders import StableDiffusionLoraLoaderMixin
from diffusers.loaders.lora_base import _best_guess_weight_name


class LoraBaseBestGuessWeightNameTests(unittest.TestCase):
def test_local_file_with_local_files_only_returns_none(self):
with tempfile.TemporaryDirectory() as tmpdir:
weight_path = Path(tmpdir) / "adapter.safetensors"
save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))

weight_name = _best_guess_weight_name(str(weight_path), local_files_only=True)
self.assertIsNone(weight_name)

def test_local_directory_with_local_files_only_discovers_weight(self):
with tempfile.TemporaryDirectory() as tmpdir:
weight_path = Path(tmpdir) / "adapter.safetensors"
save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))

weight_name = _best_guess_weight_name(tmpdir, local_files_only=True)
self.assertEqual(weight_name, "adapter.safetensors")

def test_local_directory_with_hf_hub_offline_discovers_weight(self):
with tempfile.TemporaryDirectory() as tmpdir:
weight_path = Path(tmpdir) / "adapter.safetensors"
save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))

with patch("diffusers.loaders.lora_base.HF_HUB_OFFLINE", True):
weight_name = _best_guess_weight_name(tmpdir)
self.assertEqual(weight_name, "adapter.safetensors")

def test_remote_repo_with_local_files_only_raises(self):
with self.assertRaises(ValueError) as cm:
_best_guess_weight_name("some/repo", local_files_only=True)
self.assertIn("offline mode", str(cm.exception).lower())


class LoraBaseOfflineLoadingTests(unittest.TestCase):
def test_lora_state_dict_local_directory_with_local_files_only(self):
with tempfile.TemporaryDirectory() as tmpdir:
weight_path = Path(tmpdir) / "adapter.safetensors"
save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))

state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(tmpdir, local_files_only=True)
self.assertIn("unet.test.lora_A.weight", state_dict)

def test_lora_state_dict_local_file_with_local_files_only(self):
with tempfile.TemporaryDirectory() as tmpdir:
weight_path = Path(tmpdir) / "adapter.safetensors"
save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))

state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(str(weight_path), local_files_only=True)
self.assertIn("unet.test.lora_A.weight", state_dict)

@patch.dict(os.environ, {"HF_HUB_OFFLINE": "1"})
def test_lora_state_dict_local_directory_with_hf_hub_offline(self):
with tempfile.TemporaryDirectory() as tmpdir:
weight_path = Path(tmpdir) / "adapter.safetensors"
save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))

state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(tmpdir)
self.assertIn("unet.test.lora_A.weight", state_dict)


if __name__ == "__main__":
unittest.main()
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