Update sotab.py

sotab.py

@@ -77,9 +77,13 @@ class WikiTableQuestions(datasets.GeneratorBasedBuilder):
         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)
+        # train_file = "{}.json.gz".format(self.config.name)
+        # test_file = "{}.json.gz".format(self.config.name)
+        # dev_file = "{}.json.gz".format(self.config.name)
+
+        train_file = "CTA_training_gt.csv".format(self.config.name)
+        test_file = "CTA_test_gt.csv".format(self.config.name)
+        dev_file = "CTA_validation_gt.csv".format(self.config.name)
         
         return [
             datasets.SplitGenerator(
@@ -100,56 +104,40 @@ class WikiTableQuestions(datasets.GeneratorBasedBuilder):
         ]
 
     def _read_table_from_file(self, table_name: str, root_dir: str):
-        def _extract_table_content(_line: str):
-            _vals = 
-            # _vals = [_.replace("\n", " ").strip() for _ in _line.strip("\n").split("\t")]
-            return _vals
-
-        rows = []
-        df_gt = pd.read_csv('CTA_Test_MusicRecording.csv',  encoding="utf8")
-        df = pd.read_json("./MusicRecording/"+df_gt.loc[i]["table_name"], compression='gzip', lines=True)
-        df = df.dropna().reset_index(drop=True)
-        correct_label = df_gt.loc[i]["label"]
-        
-        if df.empty:
-            op = "None"
-            output_list.append(op)
-            continue
+        df_ = pd.read_json(os.path.join(root_dir, table_name), compression='gzip', lines=True)
         
         col = []
-        for j in range(len(df.loc[0])):
+        for j in range(len(df_.loc[0])):
             col.append("col" + str(j+1))
 
         row = []
-        for index in range(len(df)):
+        for index in range(len(df_)):
             row.append(df.loc[index, :].values.tolist())
 
         # {"header": ["col1", "col2", "col3"], "rows": [["row11", "row12", "row13"], ["row21", "row22", "row23"]]}
+            
         table_context = {}
         table_context["header"] = col
         table_context["rows"] = row
-        
-        # assert ".csv" in _wtq_table_name
-        # use the normalized table file
-        table_name = table_name.replace(".csv", ".tsv")
-        with open(os.path.join(root_dir, table_name), "r", encoding="utf8") as table_f:
-            table_lines = table_f.readlines()
-            # the first line is header
-            # header = _extract_table_content(table_lines[0])
-            for line in table_lines[1:]:
-                rows.append(_extract_table_content(line))
-        return {"header": header, "rows": rows, "name": table_name}
+        table_context["name"] = table_name
+
+        return table_context
 
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, main_filepath, root_dir):
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        with open(main_filepath, encoding="utf-8") as f:
-            # skip the first line since it is the tsv header
-            next(f)
-            for idx, line in enumerate(f):
-                example_id, question, table_name, answer = line.strip("\n").split("\t")
-                answer = answer.split("|")
-                # must contain rows and header keys
-                table_content = self._read_table_from_file(table_name, root_dir)
-
-                yield idx, {"id": example_id, "question": question, "answers": answer, "table": table_content}
+
+        df = pd.read_csv(main_filepath,  encoding="utf8")
+        for ind in df.index:
+            example_id = ind
+            table_name = df['table_name'][ind]
+            column_index = df['column_index'][ind]
+            label = df['label'][ind]
+            table_content = self._read_table_from_file(table_name, root_dir)
+            
+        # for idx, line in enumerate(f):
+        #     example_id, question, table_name, answer = line.strip("\n").split("\t")
+        #     answer = answer.split("|")
+        #     # must contain rows and header keys
+        #     table_content = self._read_table_from_file(table_name, root_dir)
+
+            yield idx, {"id": example_id, "column_index": column_index, "label": label, "table": table_content}