code: def extra_repr(self):
      s = "{input_size}, {hidden_size}"
      if self.num_layers != 1:
          s += ", num_layers={num_layers}"
      if self.bias is not True:
          s += ", bias={bias}"
      if self.batch_first is not False:
          s += ", batch_first={batch_first}"
      if self.dropout != 0:
          s += ", dropout={dropout}"
      if self.bidirectional is not False:
          s += ", bidirectional={bidirectional}"
      return s.format(**self.__dict__)
  
imports: import math
  import torch
  import warnings
  import itertools
  import numbers
  from torch import nn
  from torch.nn import Parameter
  from torch.nn.utils.rnn import PackedSequence
  from lightseq.training.pytorch_quantization import tensor_quant
  from lightseq.training.pytorch_quantization.nn._functions import quant_rnn
  from .None import _utils
label_desc: Use image node_id 7 for calling the QuantRNNBase obj's underlying member method code with example usage: obj.extra_repr() and returns: s