Format evaluator files using black

evaluator/dataset.py

@@ -117,7 +117,7 @@ class ZEWDPCBaseDataset(Dataset):
         Useful during the evaluation for comparison with the ground_truth.
         """
         return self.labels_df[self.labels_column_names].to_numpy()
-    
+
     def _get_filename(self, idx):
         row = self._get_row(idx)
         filename = row.filename.replace(".png", "").replace(".jpg", "")
@@ -191,6 +191,7 @@ class ZEWDPCBaseDataset(Dataset):
             idx = idx.item()
         return idx
 
+
 class ZEWDPCProtectedDataset(ZEWDPCBaseDataset):
     """
     A protected Dataset access object which wraps over an `ZEWDPCBaseDataset` object
@@ -249,22 +250,19 @@ class ZEWDPCProtectedDataset(ZEWDPCBaseDataset):
         return self.budget - len(self.purchases)
 
 
-
-
 if __name__ == "__main__":
 
     ###########################################################################
     ###########################################################################
-    ## 
+    ##
     ## BaseDataset Access Examples
     ###########################################################################
-    ###########################################################################    
+    ###########################################################################
     dataset = ZEWDPCBaseDataset(
         images_dir="./data/prepared/v0.1/dataset_debug",
         labels_path="./data/prepared/v0.1/dataset_debug/labels.csv",
         drop_labels=False,
     )
-    
 
     print("Labels Dictionary :", dataset.labels_column_names)
     """
@@ -273,10 +271,10 @@ if __name__ == "__main__":
     """
     for sample in tqdm.tqdm(dataset):
         """
-        Each of the samples will have the following structure : 
-        
+        Each of the samples will have the following structure :
+
             {
-                'idx': 0, 
+                'idx': 0,
                 'image': array([[[110, 128, 140],
                     [110, 128, 139],
                     [110, 128, 140],
@@ -285,29 +283,28 @@ if __name__ == "__main__":
                     [134, 154, 168],
                     [137, 158, 173]]]),
                 'label': [0, 0, 1, 1]
-            }    
-        
-        where : 
+            }
+
+        where :
             `idx`   : contains the reference id for this image
             `image` : contains the image as an numpy array loaded by skimage.io.imread
-            `label` : contains the associated labels for this data point. 
-                      The values at each of the indices in the label represent the presence or absence 
-                      of the following features : 
+            `label` : contains the associated labels for this data point.
+                      The values at each of the indices in the label represent the presence or absence
+                      of the following features :
                         ['scratch_small', 'scratch_large', 'dent_small', 'dent_large']
-                        
-                    If `drop_labels` is passed as True during the instantiation of the class, 
-                    then the `labels` key is not included in the sample. 
+
+                    If `drop_labels` is passed as True during the instantiation of the class,
+                    then the `labels` key is not included in the sample.
         """
         print(sample)
         break
-    
 
     ###########################################################################
     ###########################################################################
-    ## 
+    ##
     ## Protected Dataset Access Examples
     ###########################################################################
-    ###########################################################################    
+    ###########################################################################
     p_dataset = ZEWDPCProtectedDataset(
         images_dir="./data/prepared/v0.1/dataset_debug",
         labels_path="./data/prepared/v0.1/dataset_debug/labels.csv",
@@ -332,11 +329,11 @@ if __name__ == "__main__":
         # Labels, instead have to be "purchased"
         label = p_dataset.purchase_label(idx)
         print(label, p_dataset.check_available_budget())
-        # When the budget for accessing the labels has been exhausted, the 
-        # Protected Dataset will throw an OutOfBudetException. 
+        # When the budget for accessing the labels has been exhausted, the
+        # Protected Dataset will throw an OutOfBudetException.
 
         if idx == 50:
-            # Example of transform applied to the images in the dataset 
+            # Example of transform applied to the images in the dataset
             # midway.
             preprocess = transforms.Compose(
                 [
@@ -348,4 +345,3 @@ if __name__ == "__main__":
             p_dataset.set_transform(preprocess)
             print(sample.keys())
             input("Transofrm applied. Press any key....")
-

evaluator/evaluation_metrics.py

 import torch
-import numpy as np 
+import numpy as np
 
 from sklearn.metrics import accuracy_score
 from sklearn.metrics import hamming_loss
@@ -8,5 +8,5 @@ from sklearn.metrics import hamming_loss
 def exact_match_ratio(y_true, y_pred):
     if type(y_pred) == torch.Tensor:
         y_pred = y_pred.numpy()
-    
-    return np.all(y_pred == y_true, axis=1).mean()
+
+    return np.all(y_pred == y_true, axis=1).mean()
\ No newline at end of file

evaluator/exceptions.py

@@ -3,9 +3,10 @@
 
 class OutOfBudetException(Exception):
     """Out of labelling budget"""
+
     def __init__(self, available_budget):
         self.available_budget = available_budget
         self.message = "Already Exhausted Label Purchasing Budget of : {}".format(
             self.available_budget
         )
-        super().__init__(self.message)
+        super().__init__(self.message)
\ No newline at end of file