Update sotab.py

sotab.py

@@ -34,7 +34,7 @@ _LICENSE = ""
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _DATA_URL = (
-    "https://github.com/ppasupat/WikiTableQuestions/releases/download/v1.0.2/WikiTableQuestions-1.0.2-compact.zip"
+    # "https://github.com/ppasupat/WikiTableQuestions/releases/download/v1.0.2/WikiTableQuestions-1.0.2-compact.zip"
 )
 
 
@@ -58,7 +58,7 @@ class WikiTableQuestions(datasets.GeneratorBasedBuilder):
         datasets.BuilderConfig(
             name="random-split-1",
             version=VERSION,
-            description="The random-split-1-train/dev.tsv and pristine-unseen-tables.tsv",
+            description="",
         ),
     ]
 
@@ -70,7 +70,7 @@ class WikiTableQuestions(datasets.GeneratorBasedBuilder):
         features = datasets.Features(
             {
                 "id": datasets.Value("string"),
-                "column_index": datasets.Value("int"),
+                "column_index": datasets.Value("int32"),
                 "label": datasets.features.Sequence(datasets.Value("string")),
                 "table": {
                     "header": datasets.features.Sequence(datasets.Value("string")),
@@ -96,27 +96,33 @@ class WikiTableQuestions(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        train_file = "{}-train.tsv".format(self.config.name)
-        dev_file = "{}-dev.tsv".format(self.config.name)
-        test_file = "pristine-unseen-tables.tsv"
-        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
-        urls = _DATA_URL
-        root_dir = os.path.join(dl_manager.download_and_extract(urls), "WikiTableQuestions")
+        train_url = "https://huggingface.co/datasets/shivangibithel/SOTAB/resolve/main/CTA_Training.zip"
+        dev_url = "https://huggingface.co/datasets/shivangibithel/SOTAB/resolve/main/CTA_Validation.zip"
+        test_url = "https://huggingface.co/datasets/shivangibithel/SOTAB/resolve/main/CTA_Test.zip"
+        
+        CTA_Training = os.path.join(dl_manager.download_and_extract(train_url), "CTA_Training")
+        CTA_Validation = os.path.join(dl_manager.download_and_extract(dev_url), "CTA_Validation")
+        CTA_Test = os.path.join(dl_manager.download_and_extract(test_url), "CTA_Test")
+
+        train_file = "{}.json.gz".format(self.config.name)
+        test_file = "{}.json.gz".format(self.config.name)
+        dev_file = "{}.json.gz".format(self.config.name)
+        
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={"main_filepath": os.path.join(root_dir, "data", train_file), "root_dir": root_dir},
+                gen_kwargs={"main_filepath": os.path.join(root_dir, "Train", train_file), "root_dir": CTA_Training},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={"main_filepath": os.path.join(root_dir, "data", test_file), "root_dir": root_dir},
+                gen_kwargs={"main_filepath": os.path.join(root_dir, "Test", test_file), "root_dir": CTA_Test},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
-                gen_kwargs={"main_filepath": os.path.join(root_dir, "data", dev_file), "root_dir": root_dir},
+                gen_kwargs={"main_filepath": os.path.join(root_dir, "Validation", dev_file), "root_dir": CTA_Validation},
             ),
         ]