Update test.py

test.py

@@ -566,44 +566,39 @@ class Food500(datasets.GeneratorBasedBuilder):
         archive_path = dl_manager.download(_BASE_URL)
         split_metadata_path = dl_manager.download(_METADATA_URL)
         metadata = dl_manager.iter_archive(split_metadata_path)
-        train_file = None
-        valid_file = None
-        test_file = None
         for file_path, file_obj in metadata:
-            if file_path == _TRAIN_TXT: train_file = file_obj
-            if file_path == _VALID_TXT: valid_file = file_obj
-            if file_path == _TEST_TXT: test_file = file_obj
-            # pass
+            if file_path == _TRAIN_TXT: train_set = set(file_obj.read().split("\n"))
+            if file_path == _VALID_TXT: valid_set = set(file_obj.read().split("\n"))
+            if file_path == _TEST_TXT: test_set = set(file_obj.read().split("\n"))
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
                     "images": dl_manager.iter_archive(archive_path),
-                    "metadata_file": train_file,
+                    "metadata_set": train_set,
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
                     "images": dl_manager.iter_archive(archive_path),
-                    "metadata_file": valid_file,
+                    "metadata_set": valid_set,
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
                     "images": dl_manager.iter_archive(archive_path),
-                    "metadata_file": test_file,
+                    "metadata_set": test_set,
                 },
             ),
         ]
 
-    def _generate_examples(self, images, metadata_file):
+    def _generate_examples(self, images, metadata_set):
         """Generate images and labels for splits."""
-        files_to_keep = set(metadata_file.read().split("\n"))
         for file_path, file_obj in images:
             if file_path.startswith(_IMAGES_DIR):
-                if file_path[len(_IMAGES_DIR) : -len(".jpg")] in files_to_keep:
+                if file_path[len(_IMAGES_DIR) : -len(".jpg")] in metadata_set:
                     label = file_path.split("/")[2]
                     yield file_path, {
                         "image": {"path": file_path, "bytes": file_obj.read()},