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: Get total subsampling factor.
code: def get_total_subsampling_factor(self):
      """Get total subsampling factor."""
      if isinstance(self.enc, Encoder):
          return self.enc.conv_subsampling_factor * int(
              np.prod(self.subsample_list[0])
          )
      else:
          return self.enc[0].conv_subsampling_factor * int(
              np.prod(self.subsample_list[0])
          )
  
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 6 for calling the E2E obj's underlying member method code with example usage: obj.get_total_subsampling_factor() and returns: unknown, unknown