class_docstr: Pure Python implementation of multi-blank transducer loss (https://arxiv.org/pdf/2211.03541.pdf)
class_docstr_tok: ["Pure","Python","implementation","of","multi-blank","transducer","loss","(","https",":","\/\/arxiv.org\/pdf\/2211.03541.pdf",")"]
docstr: Output types definitions for CTCLoss.
  loss:
      NeuralType(None)
docstr_tok: ["Output","types","definitions","for","CTCLoss",".","loss",":","NeuralType","(","None",")"]
code: def output_types(self):
      """Output types definitions for CTCLoss.
      loss:
          NeuralType(None)
      """
      return {"loss": NeuralType(elements_type=LossType())}
  
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 2 for calling the MultiblankRNNTLossPytorch obj's underlying member method code with example usage: obj.output_types() and returns: dict