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traditional_chinese_aya_dataset.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
+"""ted2020_tw_mt"""
+
+
+import csv
+import json
+import os
+import datasets
+
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {中文 Aya dataset},
+author={Heng-Shiou Sheu
+},
+year={2024}
+}
+"""
+
+# You can copy an official description
+_DESCRIPTION = """\
+是一個精心策劃的資料集，源自 CohereForAI 的綜合 Aya 集合，特別關注繁體中文資料。
+此資料集聚合了 CohereForAI/aya_collection、CohereForAI/aya_dataset 和 CohereForAI/aya_evaluation_suite 中的內容，
+過濾掉除中文內容之外的所有內容，包括繁體中文與簡體中文。
+"""
+
+# TODO 請使用 MAC 讀取資料夾內容來做更新
+_Subset_names = [
+    'default'
+ ]
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "https://huggingface.co/Heng666"
+
+_LICENSE = "apache-2.0"
+
+# 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)
+_URLS = {
+    "aya_collection": "https://huggingface.co/datasets/CohereForAI/aya_collection",
+    "aya_dataset": "https://huggingface.co/datasets/CohereForAI/aya_dataset",
+    "evaluation_suite": "https://huggingface.co/datasets/CohereForAI/aya_evaluation_suite"
+}
+
+class ChineseAyaDatasetConfig(datasets.BuilderConfig):
+    """BuilderConfig for Chinese Aya"""
+
+    def __init__(self, subset, **kwargs):
+        super().__init__(**kwargs)
+        """
+        Args:
+            subset: subset, you want to load
+            **kwargs: keyword arguments forwarded to super.
+        """
+        self.subset = subset
+
+
+class ChineseAyaDatasetDataset(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIG_CLASS = ChineseAyaDatasetConfig
+    
+    BUILDER_CONFIGS = [
+        ChineseAyaDatasetConfig(
+            name=subset, 
+            description=_DESCRIPTION, 
+            subset=subset 
+        )
+        for subset in _Subset_names
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({
+                "inputs": datasets.Value("string"),
+                "targets": datasets.Value("string"),
+                "language": datasets.Value("string"),
+                "language_code": datasets.Value("string"),
+                "annotation_type": datasets.Value("string"),
+                "user_id": datasets.Value("string"),
+            }),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            license=_LICENSE
+        )
+
+    def _split_generators(self, dl_manager):
+
+        subset = self.config.subset
+        
+        files = {}
+    
+        train_path = os.path.join("train/", f"CohereForAI-{subset}-train.csv")
+        files["train"] = train_path
+        test_path = os.path.join("test", f"CohereForAI-{subset}-test.csv")
+        files["test"] = test_path
+        validation_path = os.path.join("validation", f"CohereForAI-{subset}-validation.csv")
+        files["validation"] = validation_path
+
+        try:
+            data_dir = dl_manager.download_and_extract(files)
+        except:
+            files.pop("test")
+            files.pop("validation")
+            data_dir = dl_manager.download_and_extract(files)
+            
+        output = []
+        if "train" in files:
+            train = datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir["train"]
+                }
+            )
+            output.append(train)
+
+        if "test" in files:
+            test = datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": data_dir["test"]
+                }
+            )
+            output.append(test)
+        
+        if "validation" in files:
+            validation = datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": data_dir["validation"]
+                }
+            )
+            output.append(validation)
+
+        return output
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.reader(f, delimiter=",", quotechar='"')
+            for id_, row in enumerate(reader):
+                if id_ == 0:
+                    continue
+                yield id_, {
+                    "inputs": row[0],
+                    "targets": row[1],
+                    "language": row[2],
+                    "language_code": row[3],
+                    "annotation_type": row[4],
+                    "user_id": row[5],
+                }