code: def check_forward_hidden(self, input, hx, hidden_label=""):
      if input.size(0) != hx.size(0):
          raise RuntimeError(
              "Input batch size {} doesn't match hidden{} batch size {}".format(
                  input.size(0), hidden_label, hx.size(0)
              )
          )
  
      if hx.size(1) != self.hidden_size:
          raise RuntimeError(
              "hidden{} has inconsistent hidden_size: got {}, expected {}".format(
                  hidden_label, hx.size(1), self.hidden_size
              )
          )
  
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 3 for calling the QuantRNNCellBase obj's underlying member method code with example usage: obj.check_forward_hidden(input, hx, hidden_label) without return types