Revert "Finished the SVHN dataset"

This reverts commit 3605671.

Author: Seilmast

test.py

@@ -1,68 +1,12 @@
-import os 
-from scipy.io import loadmat
-import torch as th
-from torchvision import transforms
 from torch.utils.data import Dataset
-from torchvision.datasets import SVHN 
 
-class SVHNDataset(Dataset):
-    def __init__(self,
-                 datapath: str,
-                 transforms=None,
-                 download_data=True,
-                 split='train'):
-        """
-        Initializes the SVHNDataset object.
-        Args:
-            datapath (str): Path to where the data lies. If download_data is set to True, this is where the data will be downloaded.
-            transforms: Torch composite of transformations which are to be applied to the dataset images.
-            download_data (bool): If True, downloads the dataset to the specified datapath.
-            split (str): The dataset split to use, either 'train' or 'test'.
-        Raises:
-            AssertionError: If the split is not 'train' or 'test'.
-        """
+
+class SVHN(Dataset):
+    def __init__(self):
         super().__init__()
-        assert split == 'train' or split == 'test'
-        
-        if download_data:
-            self._download_data(datapath, split)
-        
-        data = loadmat(os.path.join(datapath, f'{split}_32x32.mat'))
-        
-        # Images on the form N x H x W x C
-        self.images = data['X'].transpose(3, 1, 0, 2)
-        self.labels = data['y'].flatten()
-        self.labels[self.labels == 10] = 0
-        
-        self.transforms = transforms
-    def _download_data(self, path: str, split: str):
-        """
-        Downloads the SVHN dataset.
-        Args:
-            path (str): The directory where the dataset will be downloaded.
-            split (str): The dataset split to download, either 'train' or 'test'.
-        """
-        print(f'Downloading SVHN data into {path}')
-        SVHN(path, split=split, download=True) 
-    
+
     def __len__(self):
-        """
-        Returns the number of samples in the dataset.
-        Returns:
-            int: The number of samples.
-        """
-        return len(self.labels)
+        return
+
     def __getitem__(self, index):
-        """
-        Retrieves the image and label at the specified index.
-        Args:
-            index (int): The index of the sample to retrieve.
-        Returns:
-            tuple: A tuple containing the image and its corresponding label.
-        """
-        img, lab = self.images[index], self.labels[index]
-        
-        if self.transforms is not None:
-            img = self.transforms(img)
-        
-        return img, lab
+        return