code: def __init__(self, blank_logprob=-1, loss_scale=1.0):
      super().__init__()
      self.log_softmax = torch.nn.LogSoftmax(dim=-1)
      self.ctc_loss = torch.nn.CTCLoss(zero_infinity=True)
      self.blank_logprob = blank_logprob
      self.loss_scale = loss_scale
  
file_path: NeMo/nemo/collections/tts/losses/aligner_loss.py
imports: import torch
  import torch.nn.functional
  from nemo.core.classes import Loss, typecheck
  from nemo.core.neural_types.elements import LengthsType, LogprobsType, LossType, ProbsType
  from nemo.core.neural_types.neural_type import NeuralType
label_desc: Use image node_id 1 to create a new ForwardSumLoss object from inherited base classes: Loss with example: obj = ForwardSumLoss(blank_logprob, loss_scale)