Upload fair_rationales.py

fair_rationales.py

@@ -58,6 +58,7 @@ class FairRationalesConfig(datasets.BuilderConfig):
 
     def __init__(
         self,
+        dataname,
         url,
         data_url,
         citation,
@@ -86,6 +87,7 @@ class FairRationalesConfig(datasets.BuilderConfig):
           **kwargs: keyword arguments forwarded to super.
         """
         super(FairRationalesConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        self.dataname = dataname
         self.label_classes = label_classes
         self.label_classes_original = label_classes_original
         # self.attentioncheck = attentioncheck
@@ -103,7 +105,7 @@ class FairRationales(datasets.GeneratorBasedBuilder):
 
     BUILDER_CONFIGS = [
         FairRationalesConfig(
-            name="sst2",
+            dataname="sst2",
             description=textwrap.dedent(
                 """\
                 The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language.
@@ -150,7 +152,7 @@ class FairRationales(datasets.GeneratorBasedBuilder):
             ),
         ),
         FairRationalesConfig(
-            name="dynasent",
+            dataname="dynasent",
             description=textwrap.dedent(
                 """\
                 DynaSent is an English-language benchmark task for ternary (positive/negative/neutral) sentiment analysis.
@@ -183,7 +185,7 @@ class FairRationales(datasets.GeneratorBasedBuilder):
             ),
         ),
         FairRationalesConfig(
-            name="cose",
+            dataname="cose",
             description=textwrap.dedent(
                 """\
                 Common Sense Explanations (CoS-E) allows for training language models to automatically 
@@ -236,7 +238,7 @@ class FairRationales(datasets.GeneratorBasedBuilder):
                     "originaldata_id": datasets.Value("string"),
                     "annotator_ID": datasets.Value("int64")
                     }
-        if self.config.name == "cose":
+        if self.config.dataname == "cose":
             features["label"] = datasets.Value("string")
         else:
             features["label"] = datasets.ClassLabel(names=self.config.label_classes)
@@ -288,7 +290,7 @@ class FairRationales(datasets.GeneratorBasedBuilder):
                 }
                 for attribute_name, _ in self.config.attributes:
                     example[attribute_name] = data[attribute_name]
-                if self.config.name == "sst2":
+                if self.config.dataname == "sst2":
                     example["sst2_id"] = data["sst2_id"]
                     example["sst2_split"] = data["sst2_split"]
                 yield id_, example