added english and indonesian datasets, trying Huggingface data loading script

.gitignore

@@ -0,0 +1,160 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
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+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
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+.scrapy
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+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
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+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
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+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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+
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+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
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+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
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+*.sage.py
+
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+.env
+.venv
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+venv/
+ENV/
+env.bak/
+venv.bak/
+
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+.spyderproject
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+
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+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
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+
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+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

README.md

@@ -1,3 +1,9 @@
 ---
 license: apache-2.0
 ---
+
+# Multilingual Sentiments Dataset
+
+A 3 class (positive, neutral, negative) sentiment multilingual dataset.
+
+The creation of this dataset is motivated by the lack of a multilingual sentiment dataset that

multilingual_sentiments.py

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+import os
+import json
+import datasets
+from typing import List
+import logging
+import csv
+
+_DESCRIPTION = """\
+A collection of multilingual 3-class sentiments (positive, neutral, negative) dataset.
+
+Most multilingual sentiment datasets are either 5-class ratings of products reviews (e.g. Amazon multilingual dataset) or don't include Asian languages (e.g. Malay).
+"""
+
+
+class MultilingualSentimentsConfig(datasets.BuilderConfig):
+    """BuilderConfig for IndoNLU"""
+
+    def __init__(
+        self,
+        features,
+        train_url,
+        valid_url,
+        test_url,
+        citation,
+        **kwargs,
+    ):
+        """BuilderConfig for Multilingual Sentiments.
+        Args:
+          text_features: `dict[string, string]`, map from the name of the feature
+            dict for each text field to the name of the column in the txt/csv/tsv file
+          label_column: `string`, name of the column in the txt/csv/tsv file corresponding
+            to the label
+          label_classes: `list[string]`, the list of classes if the label is categorical
+          train_url: `string`, url to train file from
+          valid_url: `string`, url to valid file from
+          test_url: `string`, url to test file from
+          citation: `string`, citation for the data set
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(MultilingualSentimentsConfig, self).__init__(
+            version=datasets.Version("1.0.0"), **kwargs
+        )
+        self.features = features
+        self.train_url = train_url
+        self.valid_url = valid_url
+        self.test_url = test_url
+
+
+class MultilingualSentimentsConfig(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        MultilingualSentimentsConfig(
+            name="en",
+            description="English sentiment analysis dataset",
+            features=["text", "label"],
+            train_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/en/train.tsv",
+            valid_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/en/val.tsv",
+            test_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/en/test.tsv",
+            version=datasets.Version("0.0.0")
+        ),
+        MultilingualSentimentsConfig(
+            name="id",
+            description="Indonesian sentiment analysis dataset",
+            features=["text", "label"],
+            train_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/id/train.tsv",
+            valid_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/id/val.tsv",
+            test_url="https://raw.githubusercontent.com/tyqiangz/multilingual-sentiment-datasets/main/id/test.tsv"
+            version=datasets.Version("0.0.0")
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=self.config.description,
+            features=datasets.Features({
+                "text": datasets.Value("string"),
+                "label": datasets.Value("string")
+            })
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        train_path = dl_manager.download_and_extract(self.config.train_url)
+        valid_path = dl_manager.download_and_extract(self.config.valid_url)
+        test_path = dl_manager.download_and_extract(self.config.test_url)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={
+                                    "filepath": train_path}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={
+                                    "filepath": valid_path}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={
+                                    "filepath": test_path}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logging.info("generating examples from = %s", filepath)
+
+        with open(filepath) as f:
+            reader = csv.reader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+
+            for id_, row in enumerate(reader):
+                text, label = row
+                yield id_, {"text": text, "label": label}