code: def test_if_transforms_missing(self):
      from bigdl.nano.pytorch.vision.transforms import (
          transforms as nano_module,
      )
      from torchvision.transforms import transforms as compared_module
  
      assert all(
          [x in nano_module.__all__ for x in compared_module.__all__]
      ), "Missing transforms"
  
file_path: BigDL/python/nano/test/pytorch/tests/vision/test_vision_transforms.py
imports: import pytest
  import os
  from unittest import TestCase
  from bigdl.nano.pytorch.vision.models import vision
  from test.pytorch.utils._train_torch_lightning import train_with_linear_top_layer
label_desc: Use image node_id 1 for calling the TestVisionTransforms obj's underlying member method code with example usage: obj.test_if_transforms_missing() without return types