code: def get_im(shape=None, dtype=None, device=None):
      if shape is None:
          shape = (1, 10, 8)
      affine = torch.randint(0, 10, (4, 4))
      meta = {"fname": rand_string()}
      t = torch.rand(shape)
      if dtype is not None:
          t = t.to(dtype)
      if device is not None:
          t = t.to(device)
      m = MetaTensor(t.clone(), affine, meta)
      return m
  
imports: from __future__ import annotations
  import random
  import string
  import unittest
  from copy import deepcopy
  import numpy
  import torch
  from parameterized import parameterized
  from monai import config
  from monai.data.meta_tensor import MetaTensor
  from monai.transforms import FromMetaTensord, ToMetaTensord
  from monai.utils.enums import PostFix
  from tests.utils import TEST_DEVICES, assert_allclose
label_desc: Use image node_id 1 for calling the TestToFromMetaTensord obj's underlying member method code with example usage: obj.get_im(shape, dtype, device) and returns: m