class_docstr: CenterFocalLoss is a variant of focal loss.
  
  More details can be found in the `paper
  <https://arxiv.org/abs/1808.01244>`_
  
  Args:
      reduction (str): Options are "none", "mean" and "sum".
      loss_weight (float): Loss weight of current loss.
class_docstr_tok: ["CenterFocalLoss","is","a","variant","of","focal","loss",".","More","details","can","be","found","in","the","`","paper","<","https",":","\/\/arxiv.org\/abs\/1808.01244",">","`","_","Args",":","reduction","(","str",")",":","Options","are","``","none","''",",","``","mean","''","and","``","sum","''",".","loss_weight","(","float",")",":","Loss","weight","of","current","loss","."]
code: def __init__(self, reduction="none", loss_weight=1.0):
      super(CenterFocalLoss, self).__init__()
      self.reduction = reduction
      self.loss_weight = loss_weight
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from itertools import cycle, islice
  from collections import abc
  import numpy
  import paddle
  import paddle.nn
  from ppdet.core.workspace import register, serializable
label_desc: Use image node_id 1 to create a new CenterFocalLoss object from inherited base classes: nn with example: obj = CenterFocalLoss(reduction, loss_weight)