print statements

SNLI-VE.py

@@ -75,19 +75,19 @@ _FEATURES = datasets.Features(
 class SNLIVE(datasets.GeneratorBasedBuilder):
     """SNLIVE."""
 
-    @property
-    def manual_download_instructions(self):
-        return """\
-    In order to get the flickr data on which SNLI-VE is built, You need to go to http://shannon.cs.illinois.edu/DenotationGraph/data/index.html,
-    and manually download the dataset ("Flickr 30k images."). Once it is completed,
-    a file named `flickr30k-images.tar.gz` will appear in your Downloads folder
-    or whichever folder your browser chooses to save files to.
-    Then, the dataset can be loaded using the following command `datasets.load_dataset("flickr30k", data_dir="<path/to/folder>")`.
-    """
+    # @property
+    # def manual_download_instructions(self):
+    #     return """\
+    # In order to get the flickr data on which SNLI-VE is built, You need to go to http://shannon.cs.illinois.edu/DenotationGraph/data/index.html,
+    # and manually download the dataset ("Flickr 30k images."). Once it is completed,
+    # a file named `flickr30k-images.tar.gz` will appear in your Downloads folder
+    # or whichever folder your browser chooses to save files to.
+    # Then, the dataset can be loaded using the following command `datasets.load_dataset("flickr30k", data_dir="<path/to/folder>")`.
+    # """
     DEFAULT_CONFIG_NAME = "Default"
-
+    print("HER0")
     def _info(self):
-
+        print("HERE1")
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=_FEATURES,
@@ -97,7 +97,7 @@ class SNLIVE(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        
+        print("HERE2")
         urls = {
             "Default": {
                 "train": os.path.join(_SNLI_VE_URL_BASE, _SNLI_VE_SPLITS["train"]),
@@ -134,6 +134,7 @@ class SNLIVE(datasets.GeneratorBasedBuilder):
         
     def _generate_examples(self, snli_ve_annotation_path, images_path):
         counter = 0
+        print("HERE3")
         print(snli_ve_annotation_path)
         with open(snli_ve_annotation_path, 'r') as json_file:
             for elem in json_file: