upload hubscripts/geokhoj_v1_hub.py to hub from bigbio repo

geokhoj_v1.py

@@ -0,0 +1,159 @@
+# coding=utf-8
+# Copyright 2022 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.
+
+"""
+GEOKhoj v1 contains metadata for 30,000 samples with their respective labels (control/perturbed),
+which were labelled using the information available in the metadata.
+Metadata has been extracted for samples from Microarray, Transcriptomics
+and Single cell experiments which are available on the GEO (Gene Expression Omnibus) database.
+"""
+
+import os
+from typing import Dict, Tuple
+
+import datasets
+import pandas as pd
+
+from .bigbiohub import text_features
+from .bigbiohub import BigBioConfig
+from .bigbiohub import Tasks
+
+_LANGUAGES = ['English']
+_PUBMED = False
+_LOCAL = False
+_CITATION = """\
+@misc{geokhoj_v1,
+  author = {Elucidata, Inc.},
+  title = {GEOKhoj v1},
+  howpublished = {\\url{https://github.com/ElucidataInc/GEOKhoj-datasets/tree/main/geokhoj_v1}},
+}
+"""
+
+_DATASETNAME = "geokhoj_v1"
+_DISPLAYNAME = "GEOKhoj v1"
+
+_DESCRIPTION = """\
+GEOKhoj v1 is a annotated corpus of control/perturbation labels for 30,000 samples
+from Microarray, Transcriptomics and Single cell experiments which are available on
+the GEO (Gene Expression Omnibus) database
+"""
+
+_HOMEPAGE = "https://github.com/ElucidataInc/GEOKhoj-datasets/tree/main/geokhoj_v1"
+
+_LICENSE = 'Creative Commons Attribution Non Commercial 4.0 International'
+
+_URLS = {
+    "source": "https://github.com/ElucidataInc/GEOKhoj-datasets/blob/main/geokhoj_v1/geokhoj_V1.zip?raw=True",
+    "bigbio_text": "https://github.com/ElucidataInc/GEOKhoj-datasets/blob/main/geokhoj_v1/geokhoj_V1.zip?raw=True",
+}
+
+_SUPPORTED_TASKS = [Tasks.TEXT_CLASSIFICATION]
+
+_SOURCE_VERSION = "1.0.0"
+
+_BIGBIO_VERSION = "1.0.0"
+
+
+class Geokhojv1Dataset(datasets.GeneratorBasedBuilder):
+    """
+    GEOKhoj v1 text classification dataset
+    """
+
+    DEFAULT_CONFIG_NAME = "geokhoj_v1_source"
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    BIGBIO_VERSION = datasets.Version(_BIGBIO_VERSION)
+
+    BUILDER_CONFIGS = [
+        BigBioConfig(
+            name="geokhoj_v1_source",
+            version=SOURCE_VERSION,
+            description="GEOKhoj v1 source schema",
+            schema="source",
+            subset_id="geokhoj_v1",
+        ),
+        BigBioConfig(
+            name="geokhoj_v1_bigbio_text",
+            version=BIGBIO_VERSION,
+            description="GEOKhoj v1 BigBio schema",
+            schema="bigbio_text",
+            subset_id="geokhoj_v1",
+        ),
+    ]
+
+    def _info(self):
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(
+                        names={0: "control", 1: "perturbation"}
+                    ),
+                    "text": datasets.Value("string"),
+                }
+            )
+
+        elif self.config.schema == "bigbio_text":
+            features = text_features
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=str(_LICENSE),
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls = _URLS[self.config.schema]
+        data_dir = dl_manager.download_and_extract(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir, "geokhoj_v1/data/train/geo_samples_train.csv"
+                    ),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir, "geokhoj_v1/data/test/geo_samples_test.csv"
+                    ),
+                    "split": "test",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        df = pd.read_csv(filepath, encoding="utf-8", header=None)
+
+        if self.config.schema == "source":
+            for id_, row in df.iterrows():
+                yield id_, {"id": row[0], "label": row[1], "text": row[2]}
+
+        elif self.config.schema == "bigbio_text":
+            for id_, row in df.iterrows():
+                yield id_, {
+                    "id": id_ + 1,
+                    "document_id": row[0],
+                    "text": row[2],
+                    "labels": [row[1]],
+                }