class_docstr: 将类似于 ``[[1], [1, 2]]`` 的内容 pad 为 ``[[1, 0], [1, 2]]`` 。可以 pad 多重嵌套的数据。
  
  :param pad_val: pad 的值；
  :param ele_dtype: 用于检测当前 field 的元素类型是否可以转换为 :class:`np.array` 类型；
  :param dtype: 输出的数据的 dtype ；
class_docstr_tok: ["\u5c06\u7c7b\u4f3c\u4e8e","``","[","[","1","]",",","[","1",",","2","]","]","``","\u7684\u5185\u5bb9","pad","\u4e3a","``","[","[","1",",","0","]",",","[","1",",","2","]","]","``","\u3002\u53ef\u4ee5","pad","\u591a\u91cd\u5d4c\u5957\u7684\u6570\u636e\u3002",":","param","pad_val",":","pad","\u7684\u503c\uff1b",":","param","ele_dtype",":","\u7528\u4e8e\u68c0\u6d4b\u5f53\u524d","field","\u7684\u5143\u7d20\u7c7b\u578b\u662f\u5426\u53ef\u4ee5\u8f6c\u6362\u4e3a",":","class",":","`","np.array","`","\u7c7b\u578b\uff1b",":","param","dtype",":","\u8f93\u51fa\u7684\u6570\u636e\u7684","dtype","\uff1b"]
code: def __init__(self, pad_val=0, ele_dtype=None, dtype=None):
      dtype = _get_dtype(ele_dtype, dtype, self.__class__.__name__)
      super().__init__(pad_val=pad_val, dtype=dtype)
  
file_path: fastNLP/fastNLP/core/collators/padders/raw_padder.py
imports: from .padder import Padder
  from .utils import is_number, get_padded_numpy_array, is_number_or_numpy_number
  from .exceptions import *
label_desc: Use image node_id 1 to create a new RawTensorPadder object from inherited base classes: Padder with example: obj = RawTensorPadder(pad_val, ele_dtype, dtype)