class_docstr: This class will be used to perform annealing between two losses
code: def __init__(self, args):
      super(LossAnnealer, self).__init__()
      self._coeff = 0.5  # args.coefficient
      self.normalized_loss = True
  
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 LossAnnealer object from inherited base classes: torch.nn.modules.loss with example: obj = LossAnnealer(args)