code: def rotate_and_shift(
      inputs: Tensor,
      translation: Tuple[float, float] = (0.0, 0.0),
      rotation: float = 0.0,
  ) -> Any:
      rotation = rotation * math.pi / 180.0
      if isinstance(inputs, TensorFlowTensor):
          transformed_tensor = transform_tf(
              inputs, translation, rotation
          )
      elif isinstance(inputs, PyTorchTensor):
          transformed_tensor = transform_pt(
              inputs, translation, rotation
          )
      else:
          raise NotImplementedError()
  
      return transformed_tensor
  
imports: from typing import Tuple, Any
  import numpy
  import math
  from eagerpy import astensor, Tensor
  from eagerpy.tensor import TensorFlowTensor, PyTorchTensor
label_desc: Use image node_id 1 for calling a global function with example usage: rotate_and_shift(inputs, translation, rotation) and returns: transformed_tensor