code: def setUp(self):
      hidden_shape = (3, 2, 4)
      dtype = self.dtype
      x_shape = (self.batch, 8, 4)
      y_shape = (self.batch, 2, 4)
  
      c_prev = numpy.random.uniform(-1, 1, hidden_shape).astype(dtype)
      x = numpy.random.uniform(-1, 1, x_shape).astype(dtype)
      c_next = numpy.random.uniform(-1, 1, hidden_shape).astype(dtype)
  
      gc = numpy.random.uniform(-1, 1, hidden_shape).astype(dtype)
      gh = numpy.random.uniform(-1, 1, y_shape).astype(dtype)
  
      ggc_prev = numpy.random.uniform(-1, 1, hidden_shape).astype(dtype)
      ggx = numpy.random.uniform(-1, 1, x_shape).astype(dtype)
  
      self.inputs = [c_prev, x, c_next, gc, gh]
      self.grad_outputs = [ggc_prev, ggx]
  
      self.check_backward_options = {"dtype": numpy.float64}
      if self.dtype == numpy.float16:
          self.check_backward_options = {
              "dtype": numpy.float64,
              "atol": 1e-3,
              "rtol": 1e-2,
          }
  
imports: import unittest
  import numpy
  import six
  from chainer.backends import cuda
  import chainer.functions
  from chainer.functions.rnn import lstm
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import backend
label_desc: Use image node_id 1 for calling the TestLSTMGrad obj's underlying member method code with example usage: obj.setUp() without return types