code: def add_model_training_inputs(model):
      """Load the training dataset and attach the training inputs to the model."""
      logger = logging.getLogger(__name__)
      logger.info("Loading dataset: {}".format(cfg.TRAIN.DATASETS))
      roidb = combined_roidb_for_training(
          cfg.TRAIN.DATASETS, cfg.TRAIN.PROPOSAL_FILES
      )
      logger.info("{:d} roidb entries".format(len(roidb)))
      model_builder.add_training_inputs(model, roidb=roidb)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import cv2
  import logging
  import numpy
  import os
  import re
  from caffe2.python import memonger
  from caffe2.python import workspace
  from detectron.core.config import cfg
  from detectron.core.config import get_output_dir
  from detectron.datasets.roidb import combined_roidb_for_training
  from detectron.modeling import model_builder
  from detectron.utils import lr_policy
  from detectron.utils.training_stats import TrainingStats
  import detectron.utils.env
  import detectron.utils.net
label_desc: Use image node_id 5 for calling a global function with example usage: add_model_training_inputs(model) without return types