import tensorflow as tf

    gtargets = labels['targets'][num_feature_layers : 2 * num_feature_layers][0]
    gscores = labels['targets'][2 * num_feature_layers : 3 * num_feature_layers][0]

    with tf.variable_scope(params['model_scope'], default_name = None, values = [features], reuse=tf.AUTO_REUSE):
        backbone = xdet_body_v3.xdet_resnet_v3(params['resnet_size'], params['data_format'])
        body_cls_output, body_regress_output = backbone(inputs=features, is_training=(mode == tf.estimator.ModeKeys.TRAIN))
