File size: 1,174 Bytes
77e3e0a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
from pathlib import Path
from torch_uncertainty.models.resnet import resnet
from safetensors.torch import load_file
def load_model(version: int):
"""Load the model corresponding to the given version."""
model = resnet(
arch=18,
num_classes=200,
in_channels=3,
style="cifar",
conv_bias=False,
)
path = Path(
f"tiny-imagenet-resnet18/tiny-imagenet-resnet18-0-1023/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
from torch_uncertainty.datamodules.classification.tiny_imagenet import TinyImageNetDataModule
from torchmetrics import Accuracy
# Compute the accuracy using the first checkpoint
acc = Accuracy("multiclass", num_classes=200)
data_module = TinyImageNetDataModule(
root="data",
batch_size=32,
)
model = load_model(0)
model.eval()
data_module.setup("test")
for batch in data_module.test_dataloader()[0]:
x, y = batch
y_hat = model(x)
acc.update(y_hat, y)
print(f"Accuracy on the test set: {acc.compute():.3%}") |