add fairface.py

fairface.py

@@ -0,0 +1,53 @@
+from pathlib import Path
+from typing import List
+import datasets
+import pickle
+
+logger = datasets.logging.get_logger(__name__)
+
+
+class Fairface(datasets.GeneratorBasedBuilder):
+
+    _HOMEPAGE = "https://huggingface.co/datasets/nateraw/fairface/"
+    _URL = "https://huggingface.co/datasets/nateraw/fairface/raw/main/"
+    _URLS = {
+        "train": _URL + "train.pt",
+        "dev": _URL + "val.pt",
+    }
+    _DESCRIPTION = "The Fairface dataset"
+    _CITATION = None
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=self._DESCRIPTION,
+            features=datasets.Features(
+                {
+                    'img_bytes': datasets.Value('binary'),
+                    'age': datasets.features.ClassLabel(names=['0-2', '3-9', '10-19', '20-29', '30-39', '40-49', '50-59', '60-69', 'more than 70']),
+                    "gender": datasets.features.ClassLabel(names=['Female', 'Male']),
+                    'race': datasets.features.ClassLabel(names=['Black', 'East Asian', 'Indian', 'Latino_Hispanic', 'Middle Eastern', 'Southeast Asian', 'White'])
+                }
+            ),
+            supervised_keys=('img_bytes', 'age'),
+            homepage=self._HOMEPAGE,
+            citation=self._CITATION,
+        )
+        
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        downloaded_files = dl_manager.download_and_extract(self._URLS)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]})
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+
+        with Path(filepath).open('rb') as f:
+            examples = pickle.load(f)
+
+        for i, ex in enumerate(examples):
+            print(ex)
+            _id = ex.pop('_id')
+            yield _id, ex