code: def generate_inputs(self):
      x_shape = []
      x_shape.append(self.shape[0])
      x_shape.append(4 * self.shape[1])
      for i in range(2, len(self.shape)):
          x_shape.append(self.shape[i])
  
      x_shape = tuple(x_shape)
      c1 = numpy.random.uniform(-1, 1, self.shape).astype(self.dtype)
      c2 = numpy.random.uniform(-1, 1, self.shape).astype(self.dtype)
      x1 = numpy.random.uniform(-1, 1, x_shape).astype(self.dtype)
      x2 = numpy.random.uniform(-1, 1, x_shape).astype(self.dtype)
      if self.flat:
          return (
              c1[..., 0],
              c2[..., 0],
              x1[..., 0],
              x2[..., 0],
          )
      else:
          return (
              c1,
              c2,
              x1,
              x2,
          )
  
imports: import unittest
  import numpy
  import six
  from chainer.backends import cuda
  from chainer import functions
  from chainer.functions.rnn import slstm
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import backend
label_desc: Use image node_id 2 for calling the TestSLSTM obj's underlying member method code with example usage: obj.generate_inputs() and returns: c1,  c2,  x1,  x2, c1,  c2,  x1,  x2