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def test_load_model():
from lama_cleaner.plugins import InteractiveSeg
from lama_cleaner.model_manager import ModelManager
interactive_seg_model = InteractiveSeg('vit_l', 'cpu')
models = [
"lama",
"ldm",
"zits",
"mat",
"fcf",
"manga",
]
for m in models:
ModelManager(
name=m,
device="cpu",
no_half=False,
hf_access_token="",
disable_nsfw=False,
sd_cpu_textencoder=True,
sd_run_local=True,
local_files_only=True,
cpu_offload=True,
enable_xformers=False,
)
# def create_empty_file(tmp_dir, name):
# tmp_model_dir = os.path.join(tmp_dir, "torch", "hub", "checkpoints")
# Path(tmp_model_dir).mkdir(exist_ok=True, parents=True)
# path = os.path.join(tmp_model_dir, name)
# with open(path, "w") as f:
# f.write("1")
#
#
# def test_load_model_error():
# MODELS = [
# ("big-lama.pt", "e3aa4aaa15225a33ec84f9f4bc47e500"),
# ("cond_stage_model_encode.pt", "23239fc9081956a3e70de56472b3f296"),
# ("cond_stage_model_decode.pt", "fe419cd15a750d37a4733589d0d3585c"),
# ("diffusion.pt", "b0afda12bf790c03aba2a7431f11d22d"),
# ]
# with tempfile.TemporaryDirectory() as tmp_dir:
# os.environ["XDG_CACHE_HOME"] = tmp_dir
# for name, md5 in MODELS:
# create_empty_file(tmp_dir, name)
# test_load_model()
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