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from pathlib import Path
from torch.nn import functional as F
from torch_uncertainty.models.resnet import resnet
from torch_uncertainty.layers.filter_response_norm import FilterResponseNorm2d
from safetensors.torch import load_file
def load_model(version: int):
"""Load the model corresponding to the given version."""
model = resnet(
arch=20,
num_classes=10,
in_channels=3,
style="cifar",
activation_fn=F.silu,
normalization_layer=FilterResponseNorm2d,
)
path = Path(
f"cifar10-resnet20-frn-silu/cifar10-resnet20-frn-silu-0-1023/version_{version}.safetensors"
)
if not path.exists():
raise ValueError("File does not exist")
state_dict = load_file(path)
model.load_state_dict(state_dict=state_dict)
return model
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