Torch-fidelity module not found in kaggle

1

!pip install torch-fidelity
import torch
import torch.nn as nn
from torchmetrics.image.kid import KernelInceptionDistance # Or import KernelInceptionDistance
import torch_fidelity
@torch.no_grad()
def compute_kid(model, val_loader, device, subsets=10, subset_size=512):
model.eval()
real_feats, pred_feats = ,
inception = nn.Identity() # Auto-handled by metric

for img_a, img_b, labels in tqdm(val_loader):
    img_a, img_b, labels = img_a.to(device), img_b.to(device), labels.to(device)
    
    # Real change maps (labels)
    real_feats.append(labels.cpu())  # Binary maps
    
    # Predicted
    pred = torch.sigmoid(model(img_a, img_b))
    pred_feats.append(pred.cpu())

real_maps = torch.cat(real_feats).flatten(1)  # (N, H*W) or Inception feats
pred_maps = torch.cat(pred_feats).flatten(1)

kid = KernelInceptionDistance(feature=2048,      # or whatever you want
subsets=10,
subset_size=1000)
return kid.item()  # Lower = better [web:100]

!pip install torch-fidelity
import torch_fidelity
transform=transforms.Compose([
transforms.Resize(256),
transforms.ToTensor()])
val_dataset = ChangeDetectionDataset(“midenet/test/imageA”, “midenet/test/imageB”, “midenet/test/label”, transform)
val_loader = DataLoader(val_dataset, batch_size=16, shuffle=False)

Post-epoch or final

model = load_change_model(
model_path=“/kaggle/working/best_change_detector.pth”,
device=“cuda”,
in_channels=3,
base_channels=32,
)
model.eval()
kid_score = compute_kid(model, val_loader, device=‘cuda’)
print(f"Val KID: {kid_score:.4f}")
torch.save({‘model_state_dict’: model.module.state_dict() if isinstance(model, nn.DataParallel) else model.state_dict(),
‘kid’: kid_score}, ‘best_kid_model.pth’)

I am working on a change detection model and using KID here are the code cell :backhand_index_pointing_up:t2: these code cell throw the ModuleNotFoundError

ModuleNotFoundError                       Traceback (most recent call last)
/tmp/ipykernel_55/128099551.py in <cell line: 0>()
     16     )
     17 model.eval()
---> 18 kid_score = compute_kid(model, val_loader, device='cuda')
     19 print(f"Val KID: {kid_score:.4f}")
     20 torch.save({'model_state_dict': model.module.state_dict() if isinstance(model, nn.DataParallel) else model.state_dict(),

/usr/local/lib/python3.12/dist-packages/torch/utils/_contextlib.py in decorate_context(*args, **kwargs)
    118     def decorate_context(*args, **kwargs):
    119         with ctx_factory():
--> 120             return func(*args, **kwargs)
    121 
    122     return decorate_context

/tmp/ipykernel_55/157051291.py in compute_kid(model, val_loader, device, subsets, subset_size)
     23     pred_maps = torch.cat(pred_feats).flatten(1)
     24 
---> 25     kid = KernelInceptionDistance(feature=2048,      # or whatever you want
     26     subsets=10,
     27     subset_size=1000)

/usr/local/lib/python3.12/dist-packages/torchmetrics/image/kid.py in __init__(self, feature, subsets, subset_size, degree, gamma, coef, reset_real_features, normalize, **kwargs)
    199         if isinstance(feature, (str, int)):
    200             if not _TORCH_FIDELITY_AVAILABLE:
--> 201                 raise ModuleNotFoundError(
    202                     "Kernel Inception Distance metric requires that `Torch-fidelity` is installed."
    203                     " Either install as `pip install torchmetrics[image]` or `pip install torch-fidelity`."

ModuleNotFoundError: Kernel Inception Distance metric requires that `Torch-fidelity` is installed. Either install as `pip install torchmetrics[image]` or `pip install torch-fidelity`.

Can anyone help me

2

I don’t know what the actual issue in your Kaggle notebook is, but note that installing Torch Fidelity works given your commands:

pip install torch-fidelity
Collecting torch-fidelity
  Downloading torch_fidelity-0.4.0-py3-none-any.whl.metadata (2.1 kB)
...
pip list | grep fidelity
torch_fidelity                   0.4.0
...
python -c "import torch_fidelity; print(torch_fidelity.__version__)"
0.4.0