Add a script to load the data

YOSM.py

@@ -0,0 +1,111 @@
+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# 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.
+
+# Lint as: python3
+"""YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS"""
+
+import datasets
+import json
+import pandas as pd
+
+logger = datasets.logging.get_logger(__name__)
+
+_CITATION = """\
+        @inproceedings{
+        shode2022yosm,
+        title={{YOSM}: A {NEW} {YORUBA} {SENTIMENT} {CORPUS} {FOR} {MOVIE} {REVIEWS}},
+        author={Iyanuoluwa Shode and David Ifeoluwa Adelani and Anna Feldman},
+        booktitle={3rd Workshop on African Natural Language Processing},
+        year={2022},
+        url={https://openreview.net/forum?id=rRzx5qzVIb9}
+        }
+        """
+
+_DESCRIPTION = """\
+YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS
+- Yoruba
+"""
+
+languages=[
+    'yoruba'
+]
+
+_URL = "https://github.com/IyanuSh/YOSM"
+_TRAINING_FILE = "train.tsv"
+_DEV_FILE = "dev.tsv"
+_TEST_FILE = "test.tsv"
+
+class Yosm(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            version=datasets.Version('1.0.0'),
+            name=lang, 
+            description='YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS'
+        ) for lang in languages
+    ]
+
+    def _info(self):
+        features = datasets.features({
+            'yo_review': datasets.Value('string'),
+            'sentiment': datasets.Value('string')
+        })
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage=_URL,
+            # License for the dataset if available
+            license='',
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+    
+    def _split_generators(self, dl_manager):
+        lang = self.config.name
+
+        splits = [
+            datasets.SplitGenerator(
+                name='train',
+                gen_kwargs={
+                    'filepath': _TRAINING_FILE,
+                },
+            ),
+            datasets.SplitGenerator(
+                name='dev',
+                gen_kwargs={
+                    'filepath': _DEV_FILE,
+                },
+            ),
+            datasets.SplitGenerator(
+                name='test',
+                gen_kwargs={
+                    'filepath': _TEST_FILE,
+                },
+            )
+
+        ]
+        return splits
+    
+    def _generate_examples(self, filepath):
+        yosm_df = pd.read_csv(filepath, sep="\t", lineterminator='\n')
+        for index, row in yosm_df.iterrows():
+            yield row["yo_review"], row["sentiment"]
+        
+
+