update

README.md

@@ -4,6 +4,7 @@ license: apache-2.0
 ## 语种识别
 
 
+
 ### 数据来源
 
 数据集从网上收集整理如下:
@@ -12,6 +13,9 @@ license: apache-2.0
 | 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) |
+| xnli | [XNLI](https://github.com/facebookresearch/XNLI); [D18-1269.pdf](https://aclanthology.org/D18-1269.pdf) | TRAIN: 7702055, VALID: 49750, TEST: 100129 | 我们希望我们的数据集 XNLI 能够通过提供信息丰富的标准评估任务来促进跨语言句子理解的研究。 | [xnli](https://huggingface.co/datasets/xnli) |
+| stsb_multi_mt | [SemEval-2017 Task 1](https://arxiv.org/abs/1708.00055) | 样本个数 | **使用时注意要打乱**。可用语言有：de、en、es、fr、it、nl、pl、pt、ru、zh | [stsb_multi_mt](https://huggingface.co/datasets/stsb_multi_mt) |
+
 
 
 ### 参考来源

data/stsb_multi_mt.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5484958b97b92ab66cd9693dabad7d3391b82de0b8b229fabce6629407256399
+size 23988370

data/xnli.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:45be37c2bf28d8110af51a6784c1e5fc207ba90887e8016482a4a0666b674983
+size 1408899727

examples/preprocess/preprocess_amazon_reviews_multi.py

@@ -12,6 +12,7 @@ sys.path.append(os.path.join(pwd, "../../"))
 from datasets import load_dataset, DownloadMode
 from tqdm import tqdm
 
+from language_identification import LANGUAGE_MAP
 from project_settings import project_path
 
 
@@ -59,6 +60,9 @@ def main():
                     continue
                 text_set.add(text)
 
+                if language not in LANGUAGE_MAP.keys():
+                    raise AssertionError(language)
+
                 row = {
                     "text": text,
                     "language": language,

examples/preprocess/preprocess_stsb_multi_mt.py

@@ -0,0 +1,91 @@
+#!/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 language_identification import LANGUAGE_MAP
+from project_settings import project_path
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--dataset_path", default="stsb_multi_mt", 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/stsb_multi_mt.jsonl"),
+        type=str
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = get_args()
+
+    name_list = ["de", "en", "es", "fr", "it", "nl", "pl", "pt", "ru", "zh"]
+
+    dataset_dict_list = list()
+    for name in name_list:
+        dataset_dict = load_dataset(
+            path=args.dataset_path,
+            name=name,
+            cache_dir=args.dataset_cache_dir,
+            # download_mode=DownloadMode.FORCE_REDOWNLOAD
+        )
+        print(dataset_dict)
+        dataset_dict_list.append((name, dataset_dict))
+
+    text_set = set()
+    counter = defaultdict(int)
+    with open(args.output_file, "w", encoding="utf-8") as f:
+        for language, dataset_dict in dataset_dict_list:
+            for k, v in dataset_dict.items():
+                for sample in tqdm(v):
+                    if k == "dev":
+                        k = "validation"
+
+                    sentence1 = sample["sentence1"]
+                    sentence2 = sample["sentence2"]
+
+                    for text in [sentence1, sentence2]:
+                        text = text.strip()
+
+                        if text in text_set:
+                            continue
+                        text_set.add(text)
+
+                        if language not in LANGUAGE_MAP.keys():
+                            raise AssertionError(language)
+
+                        row = {
+                            "text": text,
+                            "language": language,
+                            "data_source": "stsb_multi_mt",
+                            "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()

examples/preprocess/preprocess_xnli.py

@@ -0,0 +1,92 @@
+#!/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 language_identification import LANGUAGE_MAP
+from project_settings import project_path
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--dataset_path", default="xnli", type=str)
+    parser.add_argument("--dataset_name", default="all_languages", 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/xnli.jsonl"),
+        type=str
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+    args = get_args()
+
+    dataset_dict = load_dataset(
+        path=args.dataset_path,
+        name=args.dataset_name,
+        cache_dir=args.dataset_cache_dir,
+        # 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):
+
+                hypothesis = sample["hypothesis"]
+                premise = sample["premise"]
+                premise_language_list = list()
+                premise_text_list = list()
+                for language, text in premise.items():
+                    premise_language_list.append(language)
+                    premise_text_list.append(text)
+
+                language_list = hypothesis["language"] + premise_language_list
+                translation_list = hypothesis["translation"] + premise_text_list
+                for language, translation in zip(language_list, translation_list):
+
+                    text = translation.strip()
+
+                    if text in text_set:
+                        continue
+                    text_set.add(text)
+
+                    if language not in LANGUAGE_MAP.keys():
+                        raise AssertionError(language)
+
+                    row = {
+                        "text": text,
+                        "language": language,
+                        "data_source": "xnli",
+                        "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

@@ -25,6 +25,30 @@ _CITATION = """\
 """
 
 
+LANGUAGE_MAP = {
+    "ar": "arabic",
+    "bg": "bulgarian",
+    "de": "german",
+    "el": "modern greek",
+    "en": "english",
+    "es": "spanish",
+    "fr": "french",
+    "hi": "hindi",
+    "it": "italian",
+    "ja": "japanese",
+    "nl": "dutch",
+    "pl": "polish",
+    "pt": "portuguese",
+    "ru": "russian",
+    "sw": "swahili",
+    "th": "thai",
+    "tr": "turkish",
+    "ur": "urdu",
+    "vi": "vietnamese",
+    "zh": "chinese",
+}
+
+
 class LanguageIdentification(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.0.0")