docstr: Runs an instance of RCNNTarget
  
  Args:
      model: an RCNNTarget model.
      gt_boxes: a Tensor holding the ground truth boxes, with shape
          (num_gt, 5). The last value is the class label.
      proposed_boxes: a Tensor holding the proposed boxes. Its shape is
          (num_proposals, 4). The first value is the batch number.
  
  Returns:
      The tuple returned by RCNNTarget._build().
docstr_tok: ["Runs","an","instance","of","RCNNTarget","Args",":","model",":","an","RCNNTarget","model",".","gt_boxes",":","a","Tensor","holding","the","ground","truth","boxes",",","with","shape","(","num_gt",",","5",")",".","The","last","value","is","the","class","label",".","proposed_boxes",":","a","Tensor","holding","the","proposed","boxes",".","Its","shape","is","(","num_proposals",",","4",")",".","The","first","value","is","the","batch","number",".","Returns",":","The","tuple","returned","by","RCNNTarget._build","(",")","."]
code: def _run_rcnn_target(self, model, gt_boxes, proposed_boxes):
      """Runs an instance of RCNNTarget
  
      Args:
          model: an RCNNTarget model.
          gt_boxes: a Tensor holding the ground truth boxes, with shape
              (num_gt, 5). The last value is the class label.
          proposed_boxes: a Tensor holding the proposed boxes. Its shape is
              (num_proposals, 4). The first value is the batch number.
  
      Returns:
          The tuple returned by RCNNTarget._build().
      """
      rcnn_target_net = model(proposed_boxes, gt_boxes)
      with self.test_session() as sess:
          return sess.run(rcnn_target_net)
  
file_path: luminoth/luminoth/models/fasterrcnn/rcnn_target_test.py
imports: import numpy
  import tensorflow
  from easydict import EasyDict
  from luminoth.models.fasterrcnn.rcnn_target import RCNNTarget
  from luminoth.utils.test.gt_boxes import generate_gt_boxes
label_desc: Use image node_id 2 for calling the RCNNTargetTest obj's underlying member method code with example usage: obj._run_rcnn_target(model, gt_boxes, proposed_boxes) and returns: sess