class_docstr: A class to process & decode inputs/outputs of a fastrcnn classification+regression head.
code: def losses(self):
      encoded_fg_gt_boxes = (
          encode_bbox_target(
              tf.gather(self.gt_boxes, self.proposals.fg_inds_wrt_gt),
              self.proposals.fg_boxes(),
          )
          * self.bbox_regression_weights
      )
      return fastrcnn_losses(
          self.proposals.labels,
          self.label_logits,
          encoded_fg_gt_boxes,
          self.fg_box_logits(),
      )
  
imports: import tensorflow
  from tensorpack import tfv1
  from tensorpack.models import Conv2D, FullyConnected, layer_register
  from tensorpack.tfutils.argscope import argscope
  from tensorpack.tfutils.scope_utils import under_name_scope
  from tensorpack.tfutils.summary import add_moving_summary
  from tensorpack.utils.argtools import memoized_method
  from config import config
  from utils.box_ops import pairwise_iou
  from .model_box import decode_bbox_target, encode_bbox_target
  from .backbone import GroupNorm
label_desc: Use image node_id 3 for calling the FastRCNNHead obj's underlying member method code with example usage: obj.losses() and returns: fastrcnn_losses