code: def preprocess(self, data):
      self.is_dogs = [False] * len(data)
      inp_imgs = []
      for idx, row in enumerate(data):
          cat_dog_response = row.get("cat_dog_classification").decode()
          input_data = row.get("pre_processing").decode()
          if cat_dog_response == "dog":
              self.is_dogs[idx] = True
              # Wrap the input data into a format that is expected by the parent
              # preprocessing method
              inp_imgs.append({"body": input_data})
      if len(inp_imgs) > 0:
          return ImageClassifier.preprocess(self, inp_imgs)
  
imports: from ts.torch_handler.image_classifier import ImageClassifier
  import json
label_desc: Use image node_id 1 for calling the DogBreedClassifier obj's underlying member method code with example usage: obj.preprocess(data) and returns: ImageClassifier