class_docstr: A class to process & decode inputs/outputs of a fastrcnn classification+regression head.
docstr: Returns: N x #class scores, summed to one for each box.
docstr_tok: ["Returns",":","N","x","#","class","scores",",","summed","to","one","for","each","box","."]
code: def output_scores(self, name=None):
      """Returns: N x #class scores, summed to one for each box."""
      return tf.nn.softmax(self.label_logits, name=name)
  
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 9 for calling the FastRCNNHead obj's underlying member method code with example usage: obj.output_scores(name) and returns: tf