code: def __init__(self, spatial_dims, num_classes, **kwargs):
      super().__init__()
      self.spatial_dims = spatial_dims
      self.num_classes = num_classes
      self.num_anchors = 1
      self.cls_key = "cls"
      self.box_reg_key = "box_reg"
      self.size_divisible = 1
  
file_path: MONAI/tests/test_retinanet_predict_utils.py
imports: from __future__ import annotations
  import unittest
  import torch
  from parameterized import parameterized
  from monai.apps.detection.utils.predict_utils import ensure_dict_value_to_list_, predict_with_inferer
  from monai.inferers import SlidingWindowInferer
label_desc: Use image node_id 1 to create a new NaiveNetwork2 object from inherited base classes: torch.nn with example: obj = NaiveNetwork2(spatial_dims, num_classes)