class_docstr: FocalLossCost.
  
  Args:
      weight (int | float, optional): loss_weight
      alpha (int | float, optional): focal_loss alpha
      gamma (int | float, optional): focal_loss gamma
      eps (float, optional): default 1e-12
      binary_input (bool, optional): Whether the input is binary,
         default False.
class_docstr_tok: ["FocalLossCost",".","Args",":","weight","(","int","|","float",",","optional",")",":","loss_weight","alpha","(","int","|","float",",","optional",")",":","focal_loss","alpha","gamma","(","int","|","float",",","optional",")",":","focal_loss","gamma","eps","(","float",",","optional",")",":","default","1e-12","binary_input","(","bool",",","optional",")",":","Whether","the","input","is","binary",",","default","False","."]
docstr: Args:
      cls_pred (Tensor): Predicted classfication logits.
      gt_labels (Tensor)): Labels.
  
  Returns:
      Tensor: Focal cost matrix with weight in shape                (num_query, num_gt).
docstr_tok: ["Args",":","cls_pred","(","Tensor",")",":","Predicted","classfication","logits",".","gt_labels","(","Tensor",")",")",":","Labels",".","Returns",":","Tensor",":","Focal","cost","matrix","with","weight","in","shape","(","num_query",",","num_gt",")","."]
code: def __call__(self, cls_pred, gt_labels):
      """
          Args:
              cls_pred (Tensor): Predicted classfication logits.
              gt_labels (Tensor)): Labels.
  
          Returns:
              Tensor: Focal cost matrix with weight in shape\
                  (num_query, num_gt).
          """
      if self.binary_input:
          return self._mask_focal_loss_cost(cls_pred, gt_labels)
      else:
          return self._focal_loss_cost(cls_pred, gt_labels)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import paddle
  import paddle.nn.functional
  from ppdet.core.workspace import register
label_desc: Use image node_id 4 for calling the FocalLossCost obj's underlying member method code with example usage: obj.__call__(cls_pred, gt_labels) and returns: self, self