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: Encode feature.
  
  Args:
      x_list (list): input feature [(T1, D), (T2, D), ... ]
  Returns:
      list
          encoded feature [(T1, D), (T2, D), ... ]
code: def encode(self, x_list):
      """Encode feature.
  
      Args:
          x_list (list): input feature [(T1, D), (T2, D), ... ]
      Returns:
          list
              encoded feature [(T1, D), (T2, D), ... ]
  
      """
      self.eval()
      ilens_list = [
          [x_list[idx].shape[0]] for idx in range(self.num_encs)
      ]
  
      # subsample frame
      x_list = [
          x_list[idx][:: self.subsample_list[idx][0], :]
          for idx in range(self.num_encs)
      ]
      p = next(self.parameters())
      x_list = [
          torch.as_tensor(x_list[idx], device=p.device, dtype=p.dtype)
          for idx in range(self.num_encs)
      ]
      # make a utt list (1) to use the same interface for encoder
      xs_list = [
          x_list[idx].contiguous().unsqueeze(0)
          for idx in range(self.num_encs)
      ]
  
      # 1. encoder
      hs_list = []
      for idx in range(self.num_encs):
          hs, _, _ = self.enc[idx](xs_list[idx], ilens_list[idx])
          hs_list.append(hs[0])
      return hs_list
  
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 11 for calling the E2E obj's underlying member method code with example usage: obj.encode(x_list) and returns: hs_list