class_docstr: @property
  def input_types(self):
      """Returns definitions of module input ports.
      """
      return {
          "log_probs": NeuralType(('B', 'T', 'D'), LogprobsType()),
      }
  
  @property
  def output_types(self):
      """Returns definitions of module output ports.
      """
      return {"hypos": NeuralType(('B'), PredictionsType())}
docstr: Returns frame numbers corresponding to every non-blank token.
  Parameters
  ----------
  token_idxs : List[int]
      IDs of decoded tokens.
  Returns
  -------
  List[int]
      Frame numbers corresponding to every non-blank token.
docstr_tok: ["Returns","frame","numbers","corresponding","to","every","non-blank","token",".","Parameters","--","--","--","--","--","token_idxs",":","List","[","int","]","IDs","of","decoded","tokens",".","Returns","--","--","--","-","List","[","int","]","Frame","numbers","corresponding","to","every","non-blank","token","."]
code: def _get_timesteps(self, token_idxs: List[int]):
      """Returns frame numbers corresponding to every non-blank token.
      Parameters
      ----------
      token_idxs : List[int]
          IDs of decoded tokens.
      Returns
      -------
      List[int]
          Frame numbers corresponding to every non-blank token.
      """
  
      timesteps = []
      for i, token_idx in enumerate(token_idxs):
          if token_idx == self.blank:
              continue
          if i == 0 or token_idx != token_idxs[i - 1]:
              timesteps.append(i)
  
      return timesteps
  
imports: import itertools
  import math
  from typing import Iterable, List, Optional, Tuple, Union
  import numpy
  import torch
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
  from nemo.core.classes import NeuralModule, typecheck
  from nemo.core.neural_types import LengthsType, LogprobsType, NeuralType, PredictionsType
label_desc: Use image node_id 3 for calling the FlashLightKenLMBeamSearchDecoder obj's underlying member method code with example usage: obj._get_timesteps(token_idxs) and returns: timesteps