class_docstr: A class to process & decode inputs/outputs of a fastrcnn classification+regression head.
docstr: Returns: N x #class x 4 
docstr_tok: ["Returns",":","N","x","#","class","x","4"]
code: def decoded_output_boxes(self):
      """Returns: N x #class x 4"""
      anchors = tf.tile(
          tf.expand_dims(self.proposals.boxes, 1),
          [1, self._num_classes, 1],
      )  # N x #class x 4
      decoded_boxes = decode_bbox_target(
          self.box_logits / self.bbox_regression_weights, anchors
      )
      return decoded_boxes
  
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 4 for calling the FastRCNNHead obj's underlying member method code with example usage: obj.decoded_output_boxes() and returns: decoded_boxes