code: def set_input_image(self, image):
      image_nd = self.to_tensor(image)
  
      for transform in self.transforms:
          transform.reset()
      self.original_image = image_nd
      if len(self.original_image.shape) == 3:
          self.original_image = self.original_image.unsqueeze(0)
      self.prev_prediction = paddle.zeros_like(
          self.original_image[:, :1, :, :]
      )
      if not self.with_prev_mask:
          self.prev_edge = paddle.zeros_like(
              self.original_image[:, :1, :, :]
          )
  
imports: import paddle
  import paddle.nn.functional
  import numpy
  from inference.transforms import AddHorizontalFlip, SigmoidForPred, LimitLongestSide
  from .ops import DistMaps, ScaleLayer, BatchImageNormalize
label_desc: Use image node_id 3 for calling the BasePredictor obj's underlying member method code with example usage: obj.set_input_image(image) without return types