code: def set_input_image(self, image):  # (1, 12, 512, 512)
      # image is np array or other format including scalar，tuple，list，and paddle.Tensor
      self.original_image = (
          paddle.to_tensor(image).astype("float32") / 255
      )  # 1, 512, 512, 12]
  
      for transform in self.transforms:
          transform.reset()
  
      if len(self.original_image.shape) == 4:
          self.original_image = self.original_image.unsqueeze(
              0
          )  # (1, 1, 12, 512, 512)
  
      # 默认 concate 一个全0的mask作为prev mask
      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 os
  import sys
  import logging
  import numpy
  from copy import deepcopy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.inference import create_predictor, Config
  from inference.ops import DistMaps3D, ScaleLayer, BatchImageNormalize3D, SigmoidForPred
label_desc: Use image node_id 4 for calling the BasePredictor obj's underlying member method code with example usage: obj.set_input_image(image) without return types