Move ans2label and id2feature loading to _generate_examples

gqa-lxmert.py

@@ -88,20 +88,47 @@ class GqaLxmert(datasets.GeneratorBasedBuilder):
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
         dl_dir = dl_manager.download_and_extract(_URLS)
-        self.ans2label = json.load(open(dl_dir["ans2label"]))
-        self.id2features = self._load_features(os.path.join(dl_dir["feat"], _FEAT_PATH))
-
+        features_path = os.path.join(dl_dir["feat"], _FEAT_PATH)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": dl_dir["train"]},
+                gen_kwargs={
+                    "filepath": dl_dir["train"],
+                    "ans2label_path": dl_dir["ans2label"],
+                    "features_path": features_path,
+                },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
-                gen_kwargs={"filepath": dl_dir["dev"]},
+                gen_kwargs={
+                    "filepath": dl_dir["dev"],
+                    "ans2label_path": dl_dir["ans2label"],
+                    "features_path": features_path,
+                },
             ),
         ]
 
+    def _generate_examples(self, filepath, ans2label_path, features_path):
+        """ Yields examples as (key, example) tuples."""
+        if not hasattr(self, "ans2label"):
+            with open(ans2label_path, encoding="utf-8") as f:
+                self.ans2label = json.load(f)
+        if not hasattr(self, "id2features"):
+            self.id2features = self._load_features(features_path)
+        with open(filepath, encoding="utf-8") as f:
+            gqa = json.load(f)
+            for id_, d in enumerate(gqa):
+                img_features = self.id2features[d["img_id"]]
+                label = self.ans2label[next(iter(d["label"]))]
+                yield id_, {
+                    "question": d["sent"],
+                    "question_id": d["question_id"],
+                    "image_id": d["img_id"],
+                    "features": img_features["features"],
+                    "normalized_boxes": img_features["normalized_boxes"],
+                    "label": label,
+                }
+
     def _load_features(self, filepath):
         """Returns a dictionary mapping an image id to the corresponding image's objects features."""
         id2features = {}
@@ -126,19 +153,3 @@ class GqaLxmert(datasets.GeneratorBasedBuilder):
         normalized_boxes[:, (0, 2)] /= img_w
         normalized_boxes[:, (1, 3)] /= img_h
         return normalized_boxes
-
-    def _generate_examples(self, filepath):
-        """ Yields examples as (key, example) tuples."""
-        with open(filepath, encoding="utf-8") as f:
-            gqa = json.load(f)
-            for id_, d in enumerate(gqa):
-                img_features = self.id2features[d["img_id"]]
-                label = self.ans2label[next(iter(d["label"]))]
-                yield id_, {
-                    "question": d["sent"],
-                    "question_id": d["question_id"],
-                    "image_id": d["img_id"],
-                    "features": img_features["features"],
-                    "normalized_boxes": img_features["normalized_boxes"],
-                    "label": label,
-                }