code: def generate_inputs(self):
      h_shape = (self.n_layers, self.batches[0], self.hidden_size)
      dtype = numpy.float32
  
      h = array(h_shape, dtype)
      c = array(h_shape, dtype)
      in_size = self.input_size
      out_size = self.hidden_size
      xs = []
      for b in range(len(self.batches)):
          xs.append(array((self.batches[b], in_size), dtype))
  
      def w_in(i, j):
          return in_size if i == 0 and j < 4 else out_size
  
      inputs = []
      inputs.append(h)
      inputs.append(c)
      for i in range(len(self.batches)):
          inputs.append(xs[i])
      for n in range(self.n_layers):
          for i in range(8):
              inputs.append(array((out_size, w_in(n, i)), dtype))
          for i in range(8):
              inputs.append(array((out_size,), dtype))
      return tuple(inputs)
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  import chainer.functions
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import backend
  from chainer.testing import condition
label_desc: Use image node_id 2 for calling the TestNStepLSTM obj's underlying member method code with example usage: obj.generate_inputs() and returns: tuple, unknown