class_docstr: Encoder network class.
  
  Args:
      etype (str): Type of encoder network.
      idim (int): Number of dimensions of encoder network.
      elayers (int): Number of layers of encoder network.
      eunits (int): Number of lstm units of encoder network.
      eprojs (int): Number of projection units of encoder network.
      subsample (np.array): Subsampling number. e.g. 1_2_2_2_1
      dropout (float): Dropout rate.
docstr: Encoder forward.
  
  Args:
      xs (chainer.Variable): Batch of padded character ids. (B, Tmax)
      ilens (chainer.variable): Batch of length of each features. (B,)
  
  Returns:
      chainer.Variable: Output of the encoder.
      chainer.Variable: (Subsampled) vector of ilens.
docstr_tok: ["Encoder","forward",".","Args",":","xs","(","chainer.Variable",")",":","Batch","of","padded","character","ids",".","(","B",",","Tmax",")","ilens","(","chainer.variable",")",":","Batch","of","length","of","each","features",".","(","B",",",")","Returns",":","chainer.Variable",":","Output","of","the","encoder",".","chainer.Variable",":","(","Subsampled",")","vector","of","ilens","."]
code: def __call__(self, xs, ilens):
      """Encoder forward.
  
      Args:
          xs (chainer.Variable): Batch of padded character ids. (B, Tmax)
          ilens (chainer.variable): Batch of length of each features. (B,)
  
      Returns:
          chainer.Variable: Output of the encoder.
          chainer.Variable: (Subsampled) vector of ilens.
  
      """
      xs, ilens = self.enc(xs, ilens)
  
      return xs, ilens
  
imports: import logging
  import chainer
  import chainer.functions
  import chainer.links
  import numpy
  from chainer import cuda
  from espnet.nets.chainer_backend.nets_utils import _subsamplex
  from espnet.nets.e2e_asr_common import get_vgg2l_odim
label_desc: Use image node_id 2 for calling the Encoder obj's underlying member method code with example usage: obj.__call__(xs, ilens) and returns: xs,  ilens