class_docstr: A class to process & decode inputs/outputs of a fastrcnn classification+regression head.
code: def decoded_output_boxes_for_label(self, labels):
      assert not self._bbox_class_agnostic
      indices = tf.stack(
          [tf.range(tf.size(labels, out_type=tf.int64)), labels]
      )
      needed_logits = tf.gather_nd(self.box_logits, indices)
      decoded = decode_bbox_target(
          needed_logits / self.bbox_regression_weights,
          self.proposals.boxes,
      )
      return decoded
  
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 7 for calling the FastRCNNHead obj's underlying member method code with example usage: obj.decoded_output_boxes_for_label(labels) and returns: decoded