class_docstr: Pure Python implementation of TDT loss (https://arxiv.org/pdf/2304.06795.pdf)
class_docstr_tok: ["Pure","Python","implementation","of","TDT","loss","(","https",":","\/\/arxiv.org\/pdf\/2304.06795.pdf",")"]
code: def __init__(
      self,
      blank: int,
      durations: List[int] = [],
      reduction: str = "sum",
      sigma: float = 0.0,
  ):
      super().__init__()
      self.blank = blank
      self.durations = durations
      self.n_durations = len(durations)
      self.reduction = reduction
      self.sigma = sigma
  
imports: from typing import List
  import torch
  from nemo.core.classes import Loss
  from nemo.core.neural_types import LabelsType, LengthsType, LogprobsType, LossType, NeuralType
label_desc: Use image node_id 3 to create a new TDTLossPytorch object from inherited base classes: Loss with example: obj = TDTLossPytorch(blank, durations, reduction, sigma)