class_docstr: E2E module.
  
  :param List idims: List of dimensions of inputs
  :param int odim: dimension of outputs
  :param Namespace args: argument Namespace containing options
docstr: Add arguments for ctc in multi-encoder setting.
code: def ctc_add_arguments(parser):
      """Add arguments for ctc in multi-encoder setting."""
      group = parser.add_argument_group("E2E multi-ctc setting")
      group.add_argument(
          "--share-ctc",
          type=strtobool,
          default=False,
          help="The flag to switch to share ctc across multiple encoders "
          "(multi-encoder asr mode only).",
      )
      group.add_argument(
          "--weights-ctc-train",
          type=float,
          action="append",
          help="ctc weight assigned to each encoder during training.",
      )
      group.add_argument(
          "--weights-ctc-dec",
          type=float,
          action="append",
          help="ctc weight assigned to each encoder during decoding.",
      )
      return parser
  
imports: import argparse
  import logging
  import math
  import os
  from itertools import groupby
  import chainer
  import numpy
  import torch
  from chainer import reporter
  from espnet.nets.asr_interface import ASRInterface
  from espnet.nets.e2e_asr_common import label_smoothing_dist
  from espnet.nets.pytorch_backend.ctc import ctc_for
  from espnet.nets.pytorch_backend.nets_utils import get_subsample, pad_list, to_device, to_torch_tensor
  from espnet.nets.pytorch_backend.rnn.attentions import att_for
  from espnet.nets.pytorch_backend.rnn.decoders import decoder_for
  from espnet.nets.pytorch_backend.rnn.encoders import Encoder, encoder_for
  from espnet.nets.scorers.ctc import CTCPrefixScorer
  from espnet.utils.cli_utils import strtobool
label_desc: Use image node_id 5 for calling the E2E obj's underlying member method code with example usage: obj.ctc_add_arguments(parser) and returns: parser