class_docstr: Base class for encoder decoder CTC-based models.
class_docstr_tok: ["Base","class","for","encoder","decoder","CTC-based","models","."]
code: def wer(self):
      return self._wer
  
imports: import copy
  import json
  import os
  import tempfile
  from math import ceil
  from typing import Dict, List, Optional, Union
  import torch
  from omegaconf import DictConfig, OmegaConf, open_dict
  from pytorch_lightning import Trainer
  from tqdm.auto import tqdm
  from nemo.collections.asr.data import audio_to_text_dataset
  from nemo.collections.asr.losses.ctc import CTCLoss
  from nemo.collections.asr.metrics.wer import WER
  from nemo.collections.asr.models.asr_model import ASRModel, ExportableEncDecModel
  from nemo.collections.asr.parts.mixins import ASRModuleMixin, InterCTCMixin
  from nemo.collections.asr.parts.submodules.ctc_decoding import CTCDecoding, CTCDecodingConfig
  from nemo.collections.asr.parts.utils.audio_utils import ChannelSelectorType
  from nemo.collections.multimodal.speech_cv.data import video_to_text_dataset
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.classes.mixins import AccessMixin
  from nemo.core.neural_types import LabelsType, LengthsType, LogprobsType, NeuralType, VideoSignal
  from nemo.utils import logging
label_desc: Use image node_id 21 for calling the VisualEncDecCTCModel obj's underlying member method code with example usage: obj.wer() and returns: self