support passing in a source url to the mnist read_data_sets function,…

… to make it easier to use 'fashion mnist' etc. (tensorflow#12983)

tensorflow/contrib/learn/python/learn/datasets/mnist.py

@@ -30,7 +30,7 @@
 from tensorflow.python.platform import gfile
 
 # CVDF mirror of http://yann.lecun.com/exdb/mnist/
-SOURCE_URL = 'https://storage.googleapis.com/cvdf-datasets/mnist/'
+DEFAULT_SOURCE_URL = 'https://storage.googleapis.com/cvdf-datasets/mnist/'
 
 
 def _read32(bytestream):
@@ -215,7 +215,8 @@ def read_data_sets(train_dir,
                    dtype=dtypes.float32,
                    reshape=True,
                    validation_size=5000,
-                   seed=None):
+                   seed=None,
+                   source_url=DEFAULT_SOURCE_URL):
   if fake_data:
 
     def fake():
@@ -227,28 +228,31 @@ def fake():
     test = fake()
     return base.Datasets(train=train, validation=validation, test=test)
 
+  if not source_url:  # empty string check
+    source_url = DEFAULT_SOURCE_URL
+
   TRAIN_IMAGES = 'train-images-idx3-ubyte.gz'
   TRAIN_LABELS = 'train-labels-idx1-ubyte.gz'
   TEST_IMAGES = 't10k-images-idx3-ubyte.gz'
   TEST_LABELS = 't10k-labels-idx1-ubyte.gz'
 
   local_file = base.maybe_download(TRAIN_IMAGES, train_dir,
-                                   SOURCE_URL + TRAIN_IMAGES)
+                                   source_url + TRAIN_IMAGES)
   with gfile.Open(local_file, 'rb') as f:
     train_images = extract_images(f)
 
   local_file = base.maybe_download(TRAIN_LABELS, train_dir,
-                                   SOURCE_URL + TRAIN_LABELS)
+                                   source_url + TRAIN_LABELS)
   with gfile.Open(local_file, 'rb') as f:
     train_labels = extract_labels(f, one_hot=one_hot)
 
   local_file = base.maybe_download(TEST_IMAGES, train_dir,
-                                   SOURCE_URL + TEST_IMAGES)
+                                   source_url + TEST_IMAGES)
   with gfile.Open(local_file, 'rb') as f:
     test_images = extract_images(f)
 
   local_file = base.maybe_download(TEST_LABELS, train_dir,
-                                   SOURCE_URL + TEST_LABELS)
+                                   source_url + TEST_LABELS)
   with gfile.Open(local_file, 'rb') as f:
     test_labels = extract_labels(f, one_hot=one_hot)
 
@@ -262,13 +266,13 @@ def fake():
   train_images = train_images[validation_size:]
   train_labels = train_labels[validation_size:]
 
-  
+
   options = dict(dtype=dtype, reshape=reshape, seed=seed)
-  
+
   train = DataSet(train_images, train_labels, **options)
   validation = DataSet(validation_images, validation_labels, **options)
   test = DataSet(test_images, test_labels, **options)
-  
+
   return base.Datasets(train=train, validation=validation, test=test)