Update vasr.py

vasr.py

@@ -32,14 +32,8 @@ _HOMEPAGE = "https://vasr-dataset.github.io/"
 _LICENSE = "https://creativecommons.org/licenses/by/4.0/"
 
 _URL = "https://huggingface.co/datasets/nlphuji/vasr/blob/main"
-_URLS = {
-    "train": os.path.join(_URL, "train_gold.csv"),
-    "dev": os.path.join(_URL, "dev_gold.csv"),
-    "test": os.path.join(_URL, "test_gold.csv"),
-}
 
-
-class Vasr(datasets.GeneratorBasedBuilder):
+class Winogavil(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.1.0")
 
     # If you need to make complex sub-parts in the datasets with configurable options
@@ -49,9 +43,7 @@ class Vasr(datasets.GeneratorBasedBuilder):
     # You will be able to load one or the other configurations in the following list with
     # data = datasets.load_dataset('vasr', 'test')
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="TEST", version=VERSION, description="vasr dataset gold test"),
-        # datasets.BuilderConfig(name="VALIDATION", version=VERSION, description="vasr dataset gold validation"),
-        # datasets.BuilderConfig(name="TRAIN", version=VERSION, description="vasr dataset gold train")
+        datasets.BuilderConfig(name="TEST", version=VERSION, description="vasr dataset"),
     ]
     IMAGE_EXTENSION = "jpg"
 
@@ -92,7 +84,10 @@ class Vasr(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
-        # downloaded_files = dl_manager.download_and_extract(_URLS)
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         data_dir = dl_manager.download_and_extract({
             "examples_csv": hf_hub_url("datasets/nlphuji/vasr", filename="test_gold.csv"),
             "images_dir": hf_hub_url("datasets/nlphuji/vasr", filename="vasr_images.zip")
@@ -100,23 +95,6 @@ class Vasr(datasets.GeneratorBasedBuilder):
 
         return [datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=data_dir)]
 
-        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
-        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
-        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
-        # data_dir = dl_manager.download_and_extract({
-        #     "images_dir": hf_hub_url("datasets/nlphuji/vasr", filename="vasr_images.zip")
-        # })
-        #
-        # # return [datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=data_dir)]
-        # return [
-        #     datasets.SplitGenerator(name=datasets.Split.TEST,
-        #                             gen_kwargs={**data_dir, **{'filepath': downloaded_files["test"]}}),
-        #     datasets.SplitGenerator(name=datasets.Split.TRAIN,
-        #                             gen_kwargs={**data_dir, **{'filepath': downloaded_files["train"]}}),
-        #     datasets.SplitGenerator(name=datasets.Split.VALIDATION,
-        #                             gen_kwargs={**data_dir, **{'filepath': downloaded_files["dev"]}}),
-        # ]
-
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, examples_csv, images_dir):
         # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.