class_docstr: A wrapper around paddle.nn.functional.sigmoid_focal_loss.
  Args:
      use_sigmoid (bool): currently only support use_sigmoid=True
      alpha (float): parameter alpha in Focal Loss
      gamma (float): parameter gamma in Focal Loss
      loss_weight (float): final loss will be multiplied by this
class_docstr_tok: ["A","wrapper","around","paddle.nn.functional.sigmoid_focal_loss",".","Args",":","use_sigmoid","(","bool",")",":","currently","only","support","use_sigmoid=True","alpha","(","float",")",":","parameter","alpha","in","Focal","Loss","gamma","(","float",")",":","parameter","gamma","in","Focal","Loss","loss_weight","(","float",")",":","final","loss","will","be","multiplied","by","this"]
docstr: forward function.
  Args:
      pred (Tensor): logits of class prediction, of shape (N, num_classes)
      target (Tensor): target class label, of shape (N, )
      reduction (str): the way to reduce loss, one of (none, sum, mean)
docstr_tok: ["forward","function",".","Args",":","pred","(","Tensor",")",":","logits","of","class","prediction",",","of","shape","(","N",",","num_classes",")","target","(","Tensor",")",":","target","class","label",",","of","shape","(","N",",",")","reduction","(","str",")",":","the","way","to","reduce","loss",",","one","of","(","none",",","sum",",","mean",")"]
code: def forward(self, pred, target, reduction="none"):
      """forward function.
      Args:
          pred (Tensor): logits of class prediction, of shape (N, num_classes)
          target (Tensor): target class label, of shape (N, )
          reduction (str): the way to reduce loss, one of (none, sum, mean)
      """
      num_classes = pred.shape[1]
      target = F.one_hot(target, num_classes + 1).cast(pred.dtype)
      target = target[:, :-1].detach()
      loss = F.sigmoid_focal_loss(
          pred,
          target,
          alpha=self.alpha,
          gamma=self.gamma,
          reduction=reduction,
      )
      return loss * self.loss_weight
  
file_path: PaddleDetection/ppdet/modeling/losses/focal_loss.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn.functional
  import paddle.nn
  from ppdet.core.workspace import register
label_desc: Use image node_id 2 for calling the FocalLoss obj's underlying member method code with example usage: obj.forward(pred, target, reduction) and returns: unknown