Create medical-bios.py

medical-bios.py

@@ -0,0 +1,166 @@
+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Medical BIOS"""
+
+import json
+import os
+import textwrap
+
+import datasets
+
+
+MAIN_CITATION = """NA"""
+_DESCRIPTION = """NA"""
+MAIN_PATH = 'https://huggingface.co/datasets/coastalcph/medical-bios/resolve/main'
+
+
+class MedicalBIOSConfig(datasets.BuilderConfig):
+    """BuilderConfig for Medical BIOS."""
+
+    def __init__(
+        self,
+        url,
+        data_url,
+        citation,
+        **kwargs,
+    ):
+        """BuilderConfig for Medical BIOS.
+        Args:
+          url: `string`, url for the original project
+          data_url: `string`, url to download the zip file from
+          data_file: `string`, filename for data set
+          citation: `string`, citation for the data set
+          url: `string`, url for information about the data set
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(MedicalBIOSConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        self.url = url
+        self.data_url = data_url
+        self.citation = citation
+
+
+class XAIFairness(datasets.GeneratorBasedBuilder):
+    """Fairlex: A multilingual benchmark for evaluating fairness in legal text processing. Version 1.0"""
+
+    BUILDER_CONFIGS = [
+        MedicalBIOSConfig(
+            name="standard",
+            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"))}
+        return datasets.DatasetInfo(
+            description=self.config.description,
+            features=datasets.Features(features),
+            homepage=self.config.url,
+            citation=self.config.citation + "\n" + MAIN_CITATION,
+        )
+
+    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",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """This function returns the examples in the raw (text) form."""
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+                example = {
+                    "text": data["text"],
+                    "label": data[self.config.label_column]
+                }
+                if split != "test-extra":
+                    example["foil"] = data["foil"]
+                    example["words"] = data["words"]
+                    example["rationales"] = data["rationales"]
+                    example["contrastive_rationales"] = data["contrastive_rationales"]
+                else:
+                    example["foil"] = None
+                    example["words"] = None
+                    example["rationales"] = None
+                    example["contrastive_rationales"] = None
+                yield id_, example