class_docstr: SOLOv2Loss
  Args:
      ins_loss_weight (float): Weight of instance loss.
      focal_loss_gamma (float): Gamma parameter for focal loss.
      focal_loss_alpha (float): Alpha parameter for focal loss.
class_docstr_tok: ["SOLOv2Loss","Args",":","ins_loss_weight","(","float",")",":","Weight","of","instance","loss",".","focal_loss_gamma","(","float",")",":","Gamma","parameter","for","focal","loss",".","focal_loss_alpha","(","float",")",":","Alpha","parameter","for","focal","loss","."]
code: def __init__(
      self,
      ins_loss_weight=3.0,
      focal_loss_gamma=2.0,
      focal_loss_alpha=0.25,
  ):
      self.ins_loss_weight = ins_loss_weight
      self.focal_loss_gamma = focal_loss_gamma
      self.focal_loss_alpha = focal_loss_alpha
  
file_path: PaddleDetection/ppdet/modeling/losses/solov2_loss.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn.functional
  from ppdet.core.workspace import register, serializable
label_desc: Use image node_id 1 to create a new SOLOv2Loss object from inherited base classes: object with example: obj = SOLOv2Loss(ins_loss_weight, focal_loss_gamma, focal_loss_alpha)