class_docstr: Uses PyTorch to transform an image (resize, crop, normalize, etc...)
  
  Args:
      size: (`int`)
          Image size to use. A resize to `size x size` followed by center crop and
          image normalization will be done.
code: def __call__(
      self, img_tensor: Union[np.ndarray, Image.Image, torch.Tensor]
  ) -> NamedTuple("Outputs", [("img_transformed", torch.Tensor)]):
      if isinstance(img_tensor, Image.Image):
          img_tensor = img_tensor.convert("RGB")
      Outputs = NamedTuple(
          "Outputs", [("img_transformed", torch.Tensor)]
      )
      return Outputs(self.tfms(img_tensor).unsqueeze(0))
  
file_path: towhee/tests/unittests/mock_operators/pytorch_transform_operator/pytorch_transform_operator.py
imports: from typing import NamedTuple, Union
  import numpy
  import torch
  from torchvision import transforms
  from towhee.operator import Operator
  from towhee.utils.pil_utils import PILImage
label_desc: Use image node_id 2 for calling the PytorchTransformOperator obj's underlying member method code with example usage: obj.__call__(img_tensor) and returns: Outputs