docstr: 将 ``batch_field`` 数据 转为 :class:`jittor.Var` 并 pad 到相同长度。
  
  :param batch_field: 输入的某个 field 的 batch 数据。
  :param pad_val: 需要填充的值
  :param dtype: 数据的类型
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code: def pad(batch_field, pad_val=0, dtype=None):
      """
      将 ``batch_field`` 数据 转为 :class:`jittor.Var` 并 pad 到相同长度。
  
      :param batch_field: 输入的某个 field 的 batch 数据。
      :param pad_val: 需要填充的值
      :param dtype: 数据的类型
      """
      try:
          if not isinstance(batch_field[0], jittor.Var):
              batch_field = [
                  jittor.Var(np.array(field.tolist(), dtype=dtype))
                  for field in batch_field
              ]
      except AttributeError:
          raise RuntimeError(
              f"If the field is not a jittor.Var (it is {type(batch_field[0])}), "
              f"it must have tolist() method."
          )
  
      shapes = [field.shape for field in batch_field]
      if len(batch_field) < 2:
          max_shape = [len(batch_field)] + list(shapes[0])
      else:
          max_shape = [len(batch_field)] + [
              max(*_) for _ in zip(*shapes)
          ]
  
      tensor = jittor.full(max_shape, pad_val, dtype=dtype)
      for i, field in enumerate(batch_field):
          slices = (i,) + tuple(slice(0, s) for s in shapes[i])
          tensor[slices] = field
      return tensor
  
imports: from inspect import isclass
  import numpy
  from fastNLP.envs.imports import _NEED_IMPORT_JITTOR
  from .padder import Padder
  from .utils import is_number_or_numpy_number, is_number, is_numpy_number_dtype, get_shape, is_numpy_generic_class
  from .exceptions import *
label_desc: Use image node_id 2 for calling the JittorTensorPadder obj's underlying member method code with example usage: obj.pad(batch_field, pad_val, dtype) and returns: tensor