class_docstr: Cast a torch.Tensor to a different type
  param dtype: (string or torch.*Tensor literal or list) of such
          data type to which input(s) will be cast.
          If list, it should be the same length as inputs.
code: def __call__(self, *inputs):
      if not isinstance(self.dtype, (tuple, list)):
          dtypes = [self.dtype] * len(inputs)
      else:
          dtypes = self.dtype
  
      outputs = []
      idx = None
      for idx, _input in enumerate(inputs):
          _input = _input.type(dtypes[idx])
          outputs.append(_input)
      return outputs if idx >= 1 else outputs[0]
  
imports: import os
  import random
  import math
  import numpy
  import torch
label_desc: Use image node_id 2 for calling the TypeCast obj's underlying member method code with example usage: obj.__call__() and returns: unknown