initial commit

.gitattributes

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 *.jpg filter=lfs diff=lfs merge=lfs -text
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data.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:be5fd795dbfd22936d262aa0adef4269a7687bfc867e41adc2bc09682a7df6c3
+size 13384578

id-review-gen.py

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+# 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.
+# TODO: Address all TODOs and remove all explanatory comments
+"""id-review-gen: An Indonesian Review Generation Dataset."""
+
+
+import csv
+import pandas as pd
+
+import datasets
+
+_DESCRIPTION = """\
+This dataset is built as a playground for review text generation.
+"""
+
+_HOMEPAGE = "https://github.com/jakartaresearch"
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_TRAIN_URL = (
+    "https://huggingface.co/datasets/jakartaresearch/id-review-gen/raw/main/data.csv"
+)
+
+
+# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
+class ReviewGen(datasets.GeneratorBasedBuilder):
+    """GooglePlayReview: An Indonesian Sentiment Analysis Dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {"text": datasets.Value("string"), "label": datasets.Value("string")}
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION, features=features, homepage=_HOMEPAGE
+        )
+
+    def _split_generators(self, dl_manager):
+        train_path = dl_manager.download_and_extract(_TRAIN_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}
+            )
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath):
+        """Generate examples."""
+        df = pd.read_csv(filepath, encoding="utf-8")
+        for item in df.itertuples():
+            print(item)
+            yield item.Index, {"text": item.text, "label": item.label}
+        
+        # with open(filepath, encoding="utf-8") as csv_file:
+        #     csv_reader = csv.reader(csv_file, delimiter=",")
+        #     next(csv_reader)
+        #     for id_, row in enumerate(csv_reader):
+        #         text, label = row
+        #         yield id_, {"text": text, "label": label}