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 logsumexp(self, a, b):
      ret = torch.logsumexp(torch.stack([a, b]), dim=0)
      return ret
  
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 5 for calling the TDTLossPytorch obj's underlying member method code with example usage: obj.logsumexp(a, b) and returns: ret