code: def _init_vars(self):
      input_cfg = self.session.get_inputs()[0]
      input_shape = input_cfg.shape
      # print(input_shape)
      if isinstance(input_shape[2], str):
          self.input_size = None
      else:
          self.input_size = tuple(input_shape[2:4][::-1])
      # print('image_size:', self.image_size)
      input_name = input_cfg.name
      self.input_shape = input_shape
      outputs = self.session.get_outputs()
      output_names = []
      for o in outputs:
          output_names.append(o.name)
      self.input_name = input_name
      self.output_names = output_names
      self.input_mean = 127.5
      self.input_std = 128.0
      # print(self.output_names)
      # assert len(outputs)==10 or len(outputs)==15
      self.use_kps = False
      self._anchor_ratio = 1.0
      self._num_anchors = 1
      if len(outputs) == 6:
          self.fmc = 3
          self._feat_stride_fpn = [8, 16, 32]
          self._num_anchors = 2
      elif len(outputs) == 9:
          self.fmc = 3
          self._feat_stride_fpn = [8, 16, 32]
          self._num_anchors = 2
          self.use_kps = True
      elif len(outputs) == 10:
          self.fmc = 5
          self._feat_stride_fpn = [8, 16, 32, 64, 128]
          self._num_anchors = 1
      elif len(outputs) == 15:
          self.fmc = 5
          self._feat_stride_fpn = [8, 16, 32, 64, 128]
          self._num_anchors = 1
          self.use_kps = True
  
file_path: insightface/python-package/insightface/model_zoo/retinaface.py
imports: from __future__ import division
  import datetime
  import numpy
  import onnx
  import onnxruntime
  import os
  import os.path
  import cv2
  import sys
label_desc: Use image node_id 2 for calling the RetinaFace obj's underlying member method code with example usage: obj._init_vars() without return types