class_docstr: Calculate losses for FCIS and report them.
  
  This is used to train FCIS in the joint training scheme [#FCISCVPR]_.
  
  The losses include:
  
  * :obj:`rpn_loc_loss`: The localization loss for         Region Proposal Network (RPN).
  * :obj:`rpn_cls_loss`: The classification loss for RPN.
  * :obj:`roi_loc_loss`: The localization loss for the head module.
  * :obj:`roi_cls_loss`: The classification loss for the head module.
  * :obj:`roi_mask_loss`: The mask loss for the head module.
  
  .. [#FCISCVPR] Yi Li, Haozhi Qi, Jifeng Dai, Xiangyang Ji, Yichen Wei.     Fully Convolutional Instance-aware Semantic Segmentation. CVPR 2017.
  
  Args:
      fcis (~chainercv.experimental.links.model.fcis.FCIS):
          A FCIS model for training.
      rpn_sigma (float): Sigma parameter for the localization loss
          of Region Proposal Network (RPN). The default value is 3,
          which is the value used in [#FCISCVPR]_.
      roi_sigma (float): Sigma paramter for the localization loss of
          the head. The default value is 1, which is the value used
          in [#FCISCVPR]_.
      anchor_target_creator: An instantiation of
          :class:`~chainercv.links.model.faster_rcnn.AnchorTargetCreator`.
      proposal_target_creator: An instantiation of
          :class:`~chainercv.experimental.links.model.fcis.ProposalTargetCreator`.
code: def __init__(
      self,
      fcis,
      rpn_sigma=3.0,
      roi_sigma=1.0,
      anchor_target_creator=AnchorTargetCreator(),
      proposal_target_creator=ProposalTargetCreator(),
  ):
      super(FCISTrainChain, self).__init__()
      with self.init_scope():
          self.fcis = fcis
      self.rpn_sigma = rpn_sigma
      self.roi_sigma = roi_sigma
      self.mask_size = self.fcis.head.roi_size
  
      self.loc_normalize_mean = fcis.loc_normalize_mean
      self.loc_normalize_std = fcis.loc_normalize_std
  
      self.anchor_target_creator = anchor_target_creator
      self.proposal_target_creator = proposal_target_creator
  
file_path: chainercv/chainercv/experimental/links/model/fcis/fcis_train_chain.py
imports: from __future__ import division
  import numpy
  import chainer
  from chainer.backends import cuda
  import chainer.functions
  from chainercv.experimental.links.model.fcis.utils.proposal_target_creator import ProposalTargetCreator
  from chainercv.links.model.faster_rcnn.faster_rcnn_train_chain import _fast_rcnn_loc_loss
  from chainercv.links.model.faster_rcnn.utils.anchor_target_creator import AnchorTargetCreator
label_desc: Use image node_id 1 to create a new FCISTrainChain object from inherited base classes: chainer with example: obj = FCISTrainChain(fcis, rpn_sigma, roi_sigma, anchor_target_creator, proposal_target_creator)