code: def __init__(
      self,
      gamma: float = 2,
      alphas: Any = None,
      size_average: bool = True,
      normalized: bool = True,
  ):
      super(FocalLoss, self).__init__()
      self._gamma = gamma
      self._alphas = alphas
      self.size_average = size_average
      self.normalized = normalized
  
imports: from typing import Any
  from collections import OrderedDict
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  from torch_points3d.datasets.segmentation import IGNORE_LABEL
  from .metric_losses import *
label_desc: Use image node_id 1 to create a new FocalLoss object from inherited base classes: torch.nn.modules.loss with example: obj = FocalLoss(gamma, alphas, size_average, normalized)