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feature: 修改算子开发指南 (#127)
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@@ -7,83 +7,83 @@
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每个自定义算子都需要包含一个 `metadata.yml` 文件:
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```yaml
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name: '落盘算子'
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name_en: 'save file operator'
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description: '将文件内容保存为文件。'
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description_en: 'Save the file data as a file.'
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language: 'Python'
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vendor: 'Huawei'
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raw_id: 'FileExporter'
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name: '测试算子'
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description: '这是一个测试算子。'
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language: 'python'
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vendor: 'huawei'
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raw_id: 'TestMapper'
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version: '1.0.0'
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types:
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- 'collect'
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modal: 'others'
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effect:
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before: ''
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after: ''
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inputs: 'all'
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outputs: 'all'
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modal: 'text'
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inputs: 'text'
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outputs: 'text'
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```
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### 算子实现
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创建 `process.py` 文件:
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#### process.py
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```python
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# -*- coding: utf-8 -*-
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"""
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Description: Json文本抽取
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Create: 2024/06/06 15:43
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"""
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import time
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from loguru import logger
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from typing import Dict, Any
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# 导入所需数据结构,可以通过以下方式直接导入使用
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# 提供两种算子类:
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# Mapper用于映射和转换数据,使用时直接修改数据内容
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from datamate.core.base_op import Mapper
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class TestMapper(Mapper):
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def execute(self, sample):
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sample[self.text_key] += "\n新增的数据"
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return sample
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class TextFormatter(Mapper):
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"""把输入的json文件流抽取为txt"""
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# Filter用于过滤和选择性保留数据,使用时将需要过滤的数据的text或data置为空值
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from datamate.core.base_op import Filter
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def __init__(self, *args, **kwargs):
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super(TextFormatter, self).__init__(*args, **kwargs)
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@staticmethod
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def _extract_json(byte_io):
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"""将默认使用utf-8编码的Json文件流解码,抽取为txt"""
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# 用utf-8-sig的格式进行抽取,可以避免uft-8 BOM编码格式的文件在抽取后产生隐藏字符作为前缀。
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return byte_io.decode("utf-8-sig").replace("\r\n", "\n")
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def byte_read(self, sample: Dict[str, Any]):
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filepath = sample[self.filepath_key]
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with open(filepath, "rb") as file:
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byte_data = file.read()
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sample[self.data_key] = byte_data
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def execute(self, sample: Dict[str, Any]) -> Dict[str, Any]:
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start = time.time()
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try:
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self.byte_read(sample)
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sample[self.text_key] = self._extract_json(sample[self.data_key])
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sample[self.data_key] = b"" # 将sample[self.data_key]置空
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logger.info(
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f"fileName: {sample[self.filename_key]}, method: TextFormatter costs {(time.time() - start):6f} s")
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except UnicodeDecodeError as err:
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logger.exception(f"fileName: {sample[self.filename_key]}, method: TextFormatter causes decode error: {err}")
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raise
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class TestFilter(Filter):
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def execute(self, sample):
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if len(sample[self.text_key]) > 100:
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sample[self.text_key] += ""
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return sample
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```
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创建 `__init__.py` 文件:
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其中,sample的数据结构如下所示:
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```json lines
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// 数据结构
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{
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"text": "数据文件的文本内容",
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"data": "多模态文件的内容",
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"fileName": "文件名称",
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"fileType": "文件类型",
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"filePath": "文件路径",
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"fileSize": "文件大小",
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"export_path": "保存的文件路径",
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"extraFileType": "导出的文件类型"
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}
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// 数据示例
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{
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"text": "text",
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"data": "data",
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"fileName": "test",
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"fileType": "pdf",
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"filePath": "/dataset/test.pdf",
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"fileSize": "100B",
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"export_path": "/dataset/test.txt",
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"extraFileType": "txt"
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}
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```
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#### \_\_init__.py
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```python
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# -*- coding: utf-8 -*-
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# 导入OPERATORS用于进行模块注册,可以通过以下方式直接导入使用
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from datamate.core.base_op import OPERATORS
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OPERATORS.register_module(module_name='TextFormatter',
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module_path="ops.formatter.text_formatter.process")
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# module_name必须填写算子类名称;module_path中须替换模块的算子压缩包名称:python_operator.user.压缩包名.process
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OPERATORS.register_module(module_name='TestMapper',
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module_path="ops.user.test_operator.process")
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```
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@@ -5,9 +5,6 @@ vendor: 'huawei'
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raw_id: 'TestMapper'
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version: '1.0.0'
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modal: 'text'
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effect:
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before: '使用方式很简单,只需要将代码放入Markdown文本中即可,富文本格式可直接复制表情😀使用。'
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after: '使用方式很简单,只需要将代码放入Markdown文本中即可,富文本格式可直接复制表情使用。'
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inputs: 'text'
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outputs: 'text'
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settings:
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