Update medical-bios.py

medical-bios.py

@@ -95,14 +95,53 @@ class XAIFairness(datasets.GeneratorBasedBuilder):
             }"""
             ),
         ),
+        MedicalBIOSConfig(
+            name="rationales",
+            description=textwrap.dedent(
+                """\
+                The dataset is based on the Common Crawl. Specifically, De-Arteaga et al. identified online
+                biographies, written in English, by filtering for lines that began
+                with a name-like pattern (i.e., a sequence of two capitalized words)
+                followed by the string “is a(n) (xxx) title,” where title is 
+                an occupation from the BLS Standard Occupation Classification system.
+                This version of the dataset comprises English biographies labeled with occupations.
+                We also include a subset of biographies labeled with human rationales.
+                """
+            ),
+            label_classes=['psychologist', 'surgeon', 'nurse', 'dentist', 'physician'],
+            data_url=os.path.join(MAIN_PATH, "bios.zip"),
+            url="https://github.com/microsoft/biosbias",
+            citation=textwrap.dedent(
+                """\
+            @inproceedings{10.1145/3287560.3287572,
+                            author = {De-Arteaga, Maria and Romanov, Alexey and Wallach, Hanna and Chayes, 
+                            Jennifer and Borgs, Christian and Chouldechova, Alexandra and Geyik, Sahin 
+                            and Kenthapadi, Krishnaram and Kalai, Adam Tauman},
+                            title = {Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting},
+                            year = {2019},
+                            isbn = {9781450361255},
+                            publisher = {Association for Computing Machinery},
+                            address = {New York, NY, USA},
+                            url = {https://doi.org/10.1145/3287560.3287572},
+                            doi = {10.1145/3287560.3287572},
+                            booktitle = {Proceedings of the Conference on Fairness, Accountability, and Transparency},
+                            pages = {120–128},
+                            numpages = {9},
+                            location = {Atlanta, GA, USA},
+                            series = {FAT* '19}
+            }"""
+            ),
+        ),
     ]
 
     def _info(self):
-        features = {"text": datasets.Value("string"), "label": datasets.ClassLabel(names=self.config.label_classes),
-                    "foil": datasets.ClassLabel(names=self.config.label_classes),
-                    "words": datasets.Sequence(datasets.Value("string")),
-                    "rationales": datasets.Sequence(datasets.Value("int")),
-                    "contrastive_rationales": datasets.Sequence(datasets.Value("int"))}
+        if self.config.name == "standard":
+            features = {"text": datasets.Value("string"), "label": datasets.ClassLabel(names=self.config.label_classes)}
+        else:
+            features = {"text": datasets.Value("string"), "label": datasets.ClassLabel(names=self.config.label_classes),
+                        "foil": datasets.ClassLabel(names=self.config.label_classes),
+                        "words": datasets.Sequence(datasets.Value("string")),
+                        "rationales": datasets.Sequence(datasets.Value("int"))}
         return datasets.DatasetInfo(
             description=self.config.description,
             features=datasets.Features(features),
@@ -112,40 +151,44 @@ class XAIFairness(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         data_dir = dl_manager.download_and_extract(self.config.data_url)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, f"train.jsonl"),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "test.jsonl"),
-                    "split": "test",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, f"validation.jsonl"),
-                    "split": "val",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="test-extra",
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, f"test_extra.jsonl"),
-                    "split": "test-extra",
-                },
-            ),
-        ]
+        if self.config.name == 'standard':
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, f"train.jsonl"),
+                        "split": "train",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, "test.jsonl"),
+                        "split": "test",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, f"validation.jsonl"),
+                        "split": "val",
+                    },
+                ),
+            ]
+        else:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, "test.jsonl"),
+                        "split": "test",
+                    },
+                ),
+            ]
 
     def _generate_examples(self, filepath, split):
         """This function returns the examples in the raw (text) form."""
@@ -156,14 +199,9 @@ class XAIFairness(datasets.GeneratorBasedBuilder):
                     "text": data["text"],
                     "label": data[self.config.label_column]
                 }
-                if split != "test-extra":
+                if self.config.name == "rationales":
                     example["foil"] = data["foil"]
                     example["words"] = data["words"]
                     example["rationales"] = data["rationales"]
                     example["contrastive_rationales"] = data["contrastive_rationales"]
-                else:
-                    example["foil"] = 'N/A'
-                    example["words"] = ['N/A']
-                    example["rationales"] = [0]
-                    example["contrastive_rationales"] = [0]
                 yield id_, example