Formatting

Author: c-salomonsen

main.py

@@ -1,4 +1,3 @@
-import argparse
 from pathlib import Path
 
 import numpy as np
@@ -9,7 +8,7 @@
 from torchvision import transforms
 from tqdm import tqdm
 
-from utils import MetricWrapper, createfolders, load_data, load_model, get_args
+from utils import MetricWrapper, createfolders, get_args, load_data, load_model
 
 
 def main():
@@ -31,7 +30,7 @@ def main():
 
     device = args.device
 
-    if args.dataset.lower() == "usps_0-6" or args.dataset.lower() == "uspsh5_7_9":
+    if args.dataset.lower() in ["usps_0-6", "uspsh5_7_9"]:
         augmentations = transforms.Compose(
             [
                 transforms.Resize((16, 16)),

tests/test_metrics.py

@@ -94,6 +94,6 @@ def test_accuracy():
 
     accuracy_score = accuracy(y_true, y_pred)
 
-    assert (torch.abs(torch.tensor(accuracy_score - 0.8)) < 1e-5), (
+    assert torch.abs(torch.tensor(accuracy_score - 0.8)) < 1e-5, (
         f"Accuracy Score: {accuracy_score.item()}"
     )

utils/dataloaders/mnist_0_3.py

@@ -149,5 +149,3 @@ def __getitem__(self, index):
             image = self.transform(image)
 
         return image, label
-    
-

utils/metrics/accuracy.py

@@ -6,7 +6,7 @@ class Accuracy(nn.Module):
     def __init__(self, num_classes):
         super().__init__()
         self.num_classes = num_classes
-        
+
     def forward(self, y_true, y_pred):
         """
         Compute the accuracy of the model.