Fix FashionMNIST loading MNIST (#640)

Before this would lead FashionMNIST to contain mnist data:

```
MNIST(root, download=True)
FashionMNIST(root, download=True)
```

As MNIST and FashionMNIST are the same classes, the processed
outputs actual ended up to be the same files. This commit now
stores them at different files and also stores the class name when
saving them. I also added md5 sums.

test/test_datasets.py

+import torch
+from torchvision.datasets import MNIST, FashionMNIST
+import unittest
+import tempfile
+import shutil
+import os
+
+
+class Tester(unittest.TestCase):
+    def setUp(self):
+        self.test_dir = tempfile.mkdtemp()
+
+    def tearDown(self):
+        shutil.rmtree(self.test_dir)
+
+    def test_fashion_mnist_doesnt_load_mnist(self):
+        MNIST(root=self.test_dir, download=True)
+        FashionMNIST(root=self.test_dir, download=True)
+
+
+if __name__ == '__main__':
+    unittest.main()

torchvision/datasets/mnist.py

@@ -7,6 +7,7 @@ import gzip
 import numpy as np
 import torch
 import codecs
+import hashlib
 from .utils import download_url, makedir_exist_ok
 
 
@@ -26,14 +27,25 @@ class MNIST(data.Dataset):
         target_transform (callable, optional): A function/transform that takes in the
             target and transforms it.
     """
+
     urls = [
         'http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz',
         'http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz',
         'http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz',
         'http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz',
     ]
-    training_file = 'training.pt'
-    test_file = 'test.pt'
+
+    md5s = {
+        't10k-images-idx3-ubyte.gz': '9fb629c4189551a2d022fa330f9573f3',
+        't10k-labels-idx1-ubyte.gz': 'ec29112dd5afa0611ce80d1b7f02629c',
+        'train-images-idx3-ubyte.gz': 'f68b3c2dcbeaaa9fbdd348bbdeb94873',
+        'train-labels-idx1-ubyte.gz': 'd53e105ee54ea40749a09fcbcd1e9432',
+    }
+
+    raw_folder = 'raw'
+    processed_folder = 'processed'
+    training_file = 'mnist-training.pt'
+    test_file = 'mnist-test.pt'
     classes = ['0 - zero', '1 - one', '2 - two', '3 - three', '4 - four',
                '5 - five', '6 - six', '7 - seven', '8 - eight', '9 - nine']
 
@@ -50,11 +62,22 @@ class MNIST(data.Dataset):
             raise RuntimeError('Dataset not found.' +
                                ' You can use download=True to download it')
 
+        def load_data(filename):
+            loaded_data = torch.load(
+                os.path.join(self.root, self.processed_folder, filename))
+            if len(loaded_data) == 2:
+                return loaded_data
+            else:
+                clsname, data, labels = loaded_data
+                if clsname != type(self).__name__:
+                    raise RuntimeError("Expected {} data but found {}"
+                                       .format(type(self).__name__, clsname, ))
+                return data, labels
+
         if self.train:
-            data_file = self.training_file
+            self.train_data, self.train_labels = load_data(self.training_file)
         else:
-            data_file = self.test_file
-        self.data, self.targets = torch.load(os.path.join(self.processed_folder, data_file))
+            self.train_data, self.train_labels = load_data(self.test_file)
 
     def __getitem__(self, index):
         """
@@ -64,7 +87,10 @@ class MNIST(data.Dataset):
         Returns:
             tuple: (image, target) where target is index of the target class.
         """
-        img, target = self.data[index], int(self.targets[index])
+        if self.train:
+            img, target = self.train_data[index], self.train_labels[index]
+        else:
+            img, target = self.test_data[index], self.test_labels[index]
 
         # doing this so that it is consistent with all other datasets
         # to return a PIL Image
@@ -108,6 +134,8 @@ class MNIST(data.Dataset):
 
     def download(self):
         """Download the MNIST data if it doesn't exist in processed_folder already."""
+        from six.moves import urllib
+        import gzip
 
         if self._check_exists():
             return
@@ -119,19 +147,21 @@ class MNIST(data.Dataset):
         for url in self.urls:
             filename = url.rpartition('/')[2]
             file_path = os.path.join(self.raw_folder, filename)
-            download_url(url, root=self.raw_folder, filename=filename, md5=None)
+            download_url(url, root=self.raw_folder, filename=filename, md5=self.md5s[filename])
             self.extract_gzip(gzip_path=file_path, remove_finished=True)
 
         # process and save as torch files
         print('Processing...')
 
         training_set = (
-            read_image_file(os.path.join(self.raw_folder, 'train-images-idx3-ubyte')),
-            read_label_file(os.path.join(self.raw_folder, 'train-labels-idx1-ubyte'))
+            type(self).__name__,
+            read_image_file(os.path.join(self.root, self.raw_folder, 'train-images-idx3-ubyte')),
+            read_label_file(os.path.join(self.root, self.raw_folder, 'train-labels-idx1-ubyte'))
         )
         test_set = (
-            read_image_file(os.path.join(self.raw_folder, 't10k-images-idx3-ubyte')),
-            read_label_file(os.path.join(self.raw_folder, 't10k-labels-idx1-ubyte'))
+            type(self).__name__,
+            read_image_file(os.path.join(self.root, self.raw_folder, 't10k-images-idx3-ubyte')),
+            read_label_file(os.path.join(self.root, self.raw_folder, 't10k-labels-idx1-ubyte'))
         )
         with open(os.path.join(self.processed_folder, self.training_file), 'wb') as f:
             torch.save(training_set, f)
@@ -169,14 +199,22 @@ class FashionMNIST(MNIST):
         target_transform (callable, optional): A function/transform that takes in the
             target and transforms it.
     """
+    training_file = 'fashion-mnist-training.pt'
+    test_file = 'fashion-mnist-test.pt'
+
     urls = [
         'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz',
         'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz',
         'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz',
         'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz',
     ]
-    classes = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat', 'Sandal',
-               'Shirt', 'Sneaker', 'Bag', 'Ankle boot']
+
+    md5s = {
+        't10k-images-idx3-ubyte.gz': 'bef4ecab320f06d8554ea6380940ec79',
+        't10k-labels-idx1-ubyte.gz': 'bb300cfdad3c16e7a12a480ee83cd310',
+        'train-images-idx3-ubyte.gz': '8d4fb7e6c68d591d4c3dfef9ec88bf0d',
+        'train-labels-idx1-ubyte.gz': '25c81989df183df01b3e8a0aad5dffbe',
+    }
 
 
 class EMNIST(MNIST):