code: def fastrcnn_outputs(feature, num_classes, class_agnostic_regression=False):
      
      classification = FullyConnected(
          'class', feature, num_classes,
          kernel_initializer=tf.random_normal_initializer(stddev=0.01))
      num_classes_for_box = 1 if class_agnostic_regression else num_classes
      box_regression = FullyConnected(
          'box', feature, num_classes_for_box * 4,
          kernel_initializer=tf.random_normal_initializer(stddev=0.001))
      box_regression = tf.reshape(box_regression, (-1, num_classes_for_box, 4), name='output_box')
      return classification, box_regression
docs: Args:
          feature (any shape):
          num_classes(int): num_category + 1
          class_agnostic_regression (bool): if True, regression to N x 1 x 4
  
      Returns:
          cls_logits: N x num_class classification logits
          reg_logits: N x num_classx4 or Nx2x4 if class agnostic