update

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+*.jsonl filter=lfs diff=lfs merge=lfs -text

.gitignore

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+
+.git/
+.idea/
+
+**/flagged/
+**/log/
+**/logs/
+**/__pycache__/
+
+data/
+docs/
+dotenv/
+examples/preprocess/data
+hub_datasets/
+trained_models/
+temp/
+
+data/**/README.md
+data/**/*.json
+data/**/*.wav
+
+**/*.wav
+**/*.xlsx

README.md

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+---
+license: apache-2.0
+---
+## 语种识别
+
+
+### 数据来源
+
+数据集从网上收集整理如下:
+
+
+| 数据 | 原始数据/项目地址 | 样本个数 | 原始数据描述 | 替代数据下载地址 |
+| :--- |    :---:      |   :---: |    :---:    |     :---:     |
+| amazon_reviews_multi | [Multilingual Amazon Reviews Corpus](https://github.com/awslabs/open-data-docs/tree/main/docs/amazon-reviews-ml); [2010.02573](https://arxiv.org/abs/2010.02573) | TRAIN: 1191160, VALID: 29665, TEST: 29685 | 我们提出了多语言亚马逊评论语料库 (MARC)，这是用于多语言文本分类的大规模亚马逊评论集合。 该语料库包含 2015 年至 2019 年间收集的英语、日语、德语、法语、西班牙语和中文评论。 | [amazon_reviews_multi](https://huggingface.co/datasets/amazon_reviews_multi) |
+
+
+### 参考来源
+<details>
+<summary>参考的数据来源,展开查看</summary>
+<pre><code>
+https://huggingface.co/datasets/papluca/language-identification
+https://huggingface.co/datasets/unklefedor/language-identification
+
+</code></pre>
+</details>

examples/preprocess/preprocess_amazon_reviews_multi.py

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+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+import argparse
+from collections import defaultdict
+import json
+import os
+import sys
+
+pwd = os.path.abspath(os.path.dirname(__file__))
+sys.path.append(os.path.join(pwd, "../../"))
+
+from datasets import load_dataset, DownloadMode
+from tqdm import tqdm
+
+from project_settings import project_path
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--dataset_path", default="amazon_reviews_multi", type=str)
+    parser.add_argument(
+        "--dataset_cache_dir",
+        default=(project_path / "hub_datasets").as_posix(),
+        type=str
+    )
+    parser.add_argument(
+        "--output_file",
+        default=(project_path / "data/amazon_reviews_multi.jsonl"),
+        type=str
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = get_args()
+
+    dataset_dict = load_dataset(
+        path=args.dataset_path,
+        cache_dir=args.dataset_cache_dir,
+        revision="refs/convert/parquet",
+        # download_mode=DownloadMode.FORCE_REDOWNLOAD
+    )
+    print(dataset_dict)
+
+    text_set = set()
+    counter = defaultdict(int)
+    with open(args.output_file, "w", encoding="utf-8") as f:
+        for k, v in dataset_dict.items():
+            for sample in tqdm(v):
+
+                text = sample["review_body"]
+                language = sample["language"]
+
+                text = text.strip()
+
+                if text in text_set:
+                    continue
+                text_set.add(text)
+
+                row = {
+                    "text": text,
+                    "language": language,
+                    "data_source": "amazon_reviews_multi",
+                    "split": k
+                }
+                row = json.dumps(row, ensure_ascii=False)
+                f.write("{}\n".format(row))
+                counter[k] += 1
+
+    print("counter: {}".format(counter))
+
+    return
+
+
+if __name__ == '__main__':
+    main()

language_identification.py

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+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+from glob import glob
+import json
+import os
+from pathlib import Path
+
+import datasets
+
+
+_URLS = {
+    "amazon_reviews_multi": "data/amazon_reviews_multi.jsonl",
+}
+
+
+_CITATION = """\
+@dataset{language_identification,
+  author       = {Xing Tian},
+  title        = {language_identification},
+  month        = aug,
+  year         = 2024,
+  publisher    = {Xing Tian},
+  version      = {1.0},
+}
+"""
+
+
+class LanguageIdentification(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="amazon_reviews_multi", version=VERSION, description="amazon_reviews_multi"),
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+                "language": datasets.Value("string"),
+                "data_source": datasets.Value("string"),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            features=features,
+            supervised_keys=None,
+            homepage="",
+            license="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        url = _URLS[self.config.name]
+        dl_path = dl_manager.download(url)
+        archive_path = dl_path
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"archive_path": archive_path, "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"archive_path": archive_path, "split": "validation"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"archive_path": archive_path, "split": "test"},
+            ),
+        ]
+
+    def _generate_examples(self, archive_path, split):
+        archive_path = Path(archive_path)
+
+        idx = 0
+        with open(archive_path, "r", encoding="utf-8") as f:
+            for row in f:
+                sample = json.loads(row)
+
+                if sample["split"] != split:
+                    continue
+
+                yield idx, {
+                    "text": sample["text"],
+                    "language": sample["language"],
+                    "data_source": sample["data_source"],
+                }
+                idx += 1
+
+
+if __name__ == '__main__':
+    pass

main.py

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+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+from datasets import load_dataset, DownloadMode
+from tqdm import tqdm
+
+
+dataset = load_dataset(
+    "language_identification.py",
+    name="amazon_reviews_multi",
+    split="train",
+    # streaming=True,
+    cache_dir=None,
+    download_mode=DownloadMode.FORCE_REDOWNLOAD
+)
+
+for sample in tqdm(dataset):
+    print(sample)
+
+
+if __name__ == '__main__':
+    pass

project_settings.py

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+#!/usr/bin/python3
+# -*- coding: utf-8 -*-
+import os
+from pathlib import Path
+
+
+project_path = os.path.abspath(os.path.dirname(__file__))
+project_path = Path(project_path)
+
+
+if __name__ == '__main__':
+    pass

requirements.txt

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+datasets==2.4.0
+fsspec==2023.9.2
+tqdm==4.66.1
+pandas==2.0.3
+xlrd==1.2.0
+openpyxl==3.0.9