import tensorflow as tf

      class_feature_map = slim.conv2d(net, class_feature_map_depth, [1, 1],
                                      activation_fn=None,
                                      scope='class_predictions')
      class_predictions_with_background = ops.position_sensitive_crop_regions(
          class_feature_map,
          boxes=tf.reshape(proposal_boxes, [-1, self._box_code_size]),
          box_ind=get_box_indices(proposal_boxes),
          crop_size=self._crop_size,
          num_spatial_bins=self._num_spatial_bins,
          global_pool=True)
