INIT

.gitattributes

@@ -53,3 +53,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.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.gz filter=lfs diff=lfs merge=lfs -text

MNBVC-core.py

@@ -0,0 +1,101 @@
+"""
+MNBVC: Massive Never-ending BT Vast Chinese corpus
+"""
+
+import json
+import datasets
+import numpy as np
+import traceback
+from .meta import MNBVC_META
+from .features import Features
+
+
+_CITATION = """\
+"""
+
+_DESCRIPTION = """\
+MNBVC-core: core split of Massive Never-ending BT Vast Chinese corpus
+"""
+
+_HOMEPAGE = "https://github.com/esbatmop/MNBVC"
+
+_LICENSE = "MIT"
+
+
+class MNBVC(datasets.GeneratorBasedBuilder):
+
+    # multi configurations 配置
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name=key, version=datasets.Version("0.0.1"), description=value['description']) for key, value in MNBVC_META.items()]
+
+    def _info(self):
+        """
+        dataset 的关键属性信息
+        """
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=Features[MNBVC_META[self.config.name]['feature_type']],  
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """
+        下载数据，组织split
+        """
+        data_dir = dl_manager.download_and_extract(MNBVC_META[self.config.name]['files'])
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_files": data_dir,
+                },
+            ),
+        ]
+
+    # 生成器：id 和数据元素的元祖
+    def _generate_examples(self, data_files):
+        id = 0
+        features = self._info().features
+        feature_keys = set(features.keys())
+
+        def _drop_unused_keys(data):
+            rm_keys = []
+            for key in data.keys():
+                if key not in feature_keys:
+                    rm_keys.append(key)
+            for key in rm_keys:
+                del data[key]
+            return data
+
+        try:
+            for file_i, data_file in enumerate(data_files):
+                with open(data_file, encoding="utf-8") as f:
+                    for line_i, line in enumerate(f):
+                        id += 1
+                        data = json.loads(line)
+                        if self.config.name == 'law_judgement':
+                            text = data['详情']
+                            del data['详情']
+                            yield id, {
+                                "text": text,
+                                "meta": json.dumps(data, ensure_ascii=False),
+                            }
+                        else:
+                            data = _drop_unused_keys(data)
+                            if 'simhash' in data:  # for issue https://github.com/huggingface/datasets/issues/6007
+                                data['simhash'] = str(data['simhash'])
+                            
+                            yield id, data
+        except Exception as e:
+            error_msg = 'oops, we find an error when loading the dataset\n'
+            error_msg += f'Dataset: {self.config.name}\n'
+            error_msg += f'Data File: {file_i} {data_file}\n'
+            error_msg += f'Row: {line_i}'
+            print(error_msg)
+            traceback.print_exc()
+
+            raise e

features.py

@@ -0,0 +1,115 @@
+import datasets
+
+Features = {}
+
+# 项目早期所使用的数据集字段，后续会在更新过程中逐渐废弃
+Features['TEXT_CORPUS_LEGACY'] = datasets.Features(
+    {
+        "text": datasets.Value("string"),
+        "meta": datasets.Value("string")
+    }
+)
+
+# 文本数据集所使用的格式
+Features['TEXT_CORPUS'] = datasets.Features(
+    {
+        "文件名": datasets.Value("string"),
+        "是否待查文件": datasets.Value("bool"),
+        "是否重复文件": datasets.Value("bool"),
+        "文件大小": datasets.Value("int64"),
+        "simhash": datasets.Value("string"),  # for issue https://github.com/huggingface/datasets/issues/6007
+        "最长段落长度": datasets.Value("int64"),
+        "段落数": datasets.Value("int64"),
+        "去重段落数": datasets.Value("int64"),
+        "低质量段落数": datasets.Value("int64"),
+        "段落": [
+            datasets.Features(
+                {
+                    "行号": datasets.Value("int64"),
+                    "是否重复": datasets.Value("bool"),
+                    "是否跨文件重复": datasets.Value("bool"),
+                    "md5": datasets.Value("string"),
+                    "内容": datasets.Value("string"),
+                }
+            )
+        ]
+    }
+)
+
+# 问答数据所使用的格式
+Features['QA_CORPUS'] = datasets.Features(
+    {
+        "id": datasets.Value("string"),
+        "问": datasets.Value("string"),
+        "答": datasets.Value("string"),
+        "来源": datasets.Value("string"),
+        "元数据": {
+            "create_time": datasets.Value("string"),
+            "问题明细": datasets.Value("string"),
+            "回答明细": datasets.Value("string"),
+            "扩展字段": datasets.Value("string"),
+        }
+    }
+)
+
+# 代码数据所使用的格式
+Features['CODE_CORPUS'] = datasets.Features(
+    {
+        "来源": datasets.Value("string"),
+        "仓库名": datasets.Value("string"),
+        "path": datasets.Value("string"),
+        "文件名": datasets.Value("string"),
+        "ext": datasets.Value("string"),
+        "size": datasets.Value("int64"),
+        "原始编码": datasets.Value("string"),
+        "md5": datasets.Value("string"),
+        "text": datasets.Value("string")
+    }
+)
+
+# 论坛对话语料
+Features['FORUM_DIALOGUE'] = datasets.Features(
+    {
+        "ID": datasets.Value('int32'),
+        "主题": datasets.Value("string"),
+        "来源": datasets.Value("string"),
+        "回复": [
+            datasets.Features(
+                {
+                    "楼ID": datasets.Value("string"),
+                    "回复": datasets.Value("string"),
+                    "扩展字段": datasets.Value("string"),
+                }
+            )
+        ],
+        "元数据": {
+            "发帖时间": datasets.Value("string"),
+            "回复数": datasets.Value("int32"),
+            "扩展字段": datasets.Value("string")
+        }
+    }
+)
+
+# 论坛对话语料
+Features['TEXT_CORPUS'] = datasets.Features(
+    {
+        '文件名': datasets.Value("string"),
+        '是否待查文件': datasets.Value("bool"),
+        '是否重复文件': datasets.Value("bool"),
+        '文件大小': datasets.Value("int64"),
+        'simhash': datasets.Value("int64"),
+        '最长段落长度': datasets.Value("int32"),
+        '段落数': datasets.Value("int32"),
+        '去重段落数': datasets.Value("int32"),
+        '低质量段落数': datasets.Value("int32"),
+        '段落': [
+            {
+                '行号': datasets.Value("int32"),
+                '是否重复': datasets.Value("bool"),
+                '是否跨文件重复': datasets.Value("bool"),
+                'md5': datasets.Value("string"),
+                '内容': datasets.Value("string")
+            }
+        ]
+    }
+)

gov/GovReport.jsonl.gz

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+size 13833331

gov/XueXiQiangGuo.jsonl.gz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:27ea4e9f7a7e4ac54330fabb3e519765b89162494e5a8d8a6c169a1eabd4f979
+size 419641134

meta.py

@@ -0,0 +1,61 @@
+
+MNBVC_META = {}
+
+base_url = 'https://huggingface.co/datasets/qbo-odp/MNBVC-core/resolve/main'
+def _flatten_list(input):
+    res = []
+    for i in input:
+        if type(i) == list:
+            res += _flatten_list(i)
+        else:
+            res.append(i)
+    return res
+
+
+# =============================
+# gov_xuexiqiangguo
+MNBVC_META['gov_xuexiqiangguo'] = {}
+MNBVC_META['gov_xuexiqiangguo']['files'] = [f'{base_url}/gov/XueXiQiangGuo.jsonl.gz']
+MNBVC_META['gov_xuexiqiangguo']['feature_type'] = "TEXT_CORPUS"
+MNBVC_META['gov_xuexiqiangguo']['description'] = "Texts from government files (XueXiQiangGuo)"
+
+
+# =============================
+# gov_report
+MNBVC_META['gov_report'] = {}
+MNBVC_META['gov_report']['files'] = [f'{base_url}/gov/GovReport.jsonl.gz']
+MNBVC_META['gov_report']['feature_type'] = "TEXT_CORPUS_LEGACY"
+MNBVC_META['gov_report']['description'] = "Texts from government files (Gov Report)"
+
+# =============================
+# qa_mfa
+MNBVC_META['qa_mfa'] = {}
+MNBVC_META['qa_mfa']['files'] = [
+    [f'{base_url}/qa/mfa/0.jsonl.gz']
+]
+MNBVC_META['qa_mfa']['files'] = _flatten_list(MNBVC_META['qa_mfa']['files'])
+MNBVC_META['qa_mfa']['feature_type'] = "QA_CORPUS"
+MNBVC_META['qa_mfa']['description'] = "QA data from Ministry of Foreign Affairs"
+
+
+# =============================
+# news_peoples_daily
+MNBVC_META['news_peoples_daily'] = {}
+MNBVC_META['news_peoples_daily']['files'] = [
+    [f'{base_url}/news/peoples_daily/{i}.jsonl.gz' for i in range(12)] 
+]
+MNBVC_META['news_peoples_daily']['files'] = _flatten_list(MNBVC_META['news_peoples_daily']['files'])
+MNBVC_META['news_peoples_daily']['feature_type'] = "TEXT_CORPUS"
+MNBVC_META['news_peoples_daily']['description'] = "News data from people's daily"
+
+# =============================
+# qa_stackexchange
+MNBVC_META['qa_stackexchange'] = {}
+MNBVC_META['qa_stackexchange']['files'] = []
+
+MNBVC_META['qa_stackexchange']['files'] += [
+    [f'{base_url}/qa/stackexchange/{i}.jsonl.gz' for i in range(1, 2)] 
+]
+MNBVC_META['qa_stackexchange']['files'] = _flatten_list(MNBVC_META['qa_stackexchange']['files'])
+MNBVC_META['qa_stackexchange']['feature_type'] = "QA_CORPUS"
+MNBVC_META['qa_stackexchange']['description'] = "QA data from StackExchange"

news/peoples_daily/0.jsonl.gz

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test.ipynb

@@ -0,0 +1,150 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5d3c22fa-b62f-4828-bb55-60640e1a393c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install datasets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9f6e89ca-43c5-409c-987e-94b6a1c89082",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 测试 datasets 正确性\n",
+    "!datasets-cli test /workspace/data/MNBVC-core --data_dir=/workspace/data/MNBVC-core --save_info --all_configs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "2cb2a5cf-43b1-4372-8583-bd37455406a0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_from_disk,load_dataset_builder, get_dataset_split_names, get_dataset_config_names\n",
+    "\n",
+    "DATASET='/workspace/data/MNBVC-core'\n",
+    "CONFIGURATION='qa_mfa'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "ddadbe3a-5b78-4b22-8d5a-fb82b42dd01f",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "FileNotFoundError",
+     "evalue": "Directory /workspace/data/MNBVC-core is neither a `Dataset` directory nor a `DatasetDict` directory.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m ds \u001b[38;5;241m=\u001b[39m \u001b[43mload_from_disk\u001b[49m\u001b[43m(\u001b[49m\u001b[43mDATASET\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/opt/conda/envs/envd/lib/python3.10/site-packages/datasets/load.py:2252\u001b[0m, in \u001b[0;36mload_from_disk\u001b[0;34m(dataset_path, fs, keep_in_memory, storage_options)\u001b[0m\n\u001b[1;32m   2250\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m DatasetDict\u001b[38;5;241m.\u001b[39mload_from_disk(dataset_path, keep_in_memory\u001b[38;5;241m=\u001b[39mkeep_in_memory, storage_options\u001b[38;5;241m=\u001b[39mstorage_options)\n\u001b[1;32m   2251\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2252\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\n\u001b[1;32m   2253\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDirectory \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdataset_path\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m is neither a `Dataset` directory nor a `DatasetDict` directory.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   2254\u001b[0m     )\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: Directory /workspace/data/MNBVC-core is neither a `Dataset` directory nor a `DatasetDict` directory."
+     ]
+    }
+   ],
+   "source": [
+    "ds = load_from_disk(DATASET)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "5fe8f56e-019f-475d-811a-f707450934e2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on function load_from_disk in module datasets.load:\n",
+      "\n",
+      "load_from_disk(dataset_path: str, fs='deprecated', keep_in_memory: Optional[bool] = None, storage_options: Optional[dict] = None) -> Union[datasets.arrow_dataset.Dataset, datasets.dataset_dict.DatasetDict]\n",
+      "    Loads a dataset that was previously saved using [`~Dataset.save_to_disk`] from a dataset directory, or\n",
+      "    from a filesystem using any implementation of `fsspec.spec.AbstractFileSystem`.\n",
+      "    \n",
+      "    Args:\n",
+      "        dataset_path (`str`):\n",
+      "            Path (e.g. `\"dataset/train\"`) or remote URI (e.g.\n",
+      "            `\"s3://my-bucket/dataset/train\"`) of the [`Dataset`] or [`DatasetDict`] directory where the dataset will be\n",
+      "            loaded from.\n",
+      "        fs (`~filesystems.S3FileSystem` or `fsspec.spec.AbstractFileSystem`, *optional*):\n",
+      "            Instance of the remote filesystem used to download the files from.\n",
+      "    \n",
+      "            <Deprecated version=\"2.9.0\">\n",
+      "    \n",
+      "            `fs` was deprecated in version 2.9.0 and will be removed in 3.0.0.\n",
+      "            Please use `storage_options` instead, e.g. `storage_options=fs.storage_options`.\n",
+      "    \n",
+      "            </Deprecated>\n",
+      "    \n",
+      "        keep_in_memory (`bool`, defaults to `None`):\n",
+      "            Whether to copy the dataset in-memory. If `None`, the dataset\n",
+      "            will not be copied in-memory unless explicitly enabled by setting `datasets.config.IN_MEMORY_MAX_SIZE` to\n",
+      "            nonzero. See more details in the [improve performance](../cache#improve-performance) section.\n",
+      "    \n",
+      "        storage_options (`dict`, *optional*):\n",
+      "            Key/value pairs to be passed on to the file-system backend, if any.\n",
+      "    \n",
+      "            <Added version=\"2.9.0\"/>\n",
+      "    \n",
+      "    Returns:\n",
+      "        [`Dataset`] or [`DatasetDict`]:\n",
+      "        - If `dataset_path` is a path of a dataset directory: the dataset requested.\n",
+      "        - If `dataset_path` is a path of a dataset dict directory, a [`DatasetDict`] with each split.\n",
+      "    \n",
+      "    Example:\n",
+      "    \n",
+      "    ```py\n",
+      "    >>> from datasets import load_from_disk\n",
+      "    >>> ds = load_from_disk('path/to/dataset/directory')\n",
+      "    ```\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "help(load_from_disk)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6a2a08b1-0f99-4944-bc6d-98d288f6e366",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}