code: def setUp(self):
      shape = (self.n_layers * 2, len(self.lengths), self.out_size)
      if self.hidden_none:
          self.h = numpy.zeros(shape, "f")
      else:
          self.h = numpy.random.uniform(-1, 1, shape).astype("f")
      self.xs = [
          numpy.random.uniform(-1, 1, (l, self.in_size)).astype("f")
          for l in self.lengths
      ]
  
      self.gh = numpy.random.uniform(-1, 1, shape).astype("f")
      self.gys = [
          numpy.random.uniform(-1, 1, (l, self.out_size * 2)).astype(
              "f"
          )
          for l in self.lengths
      ]
      self.rnn = links.NStepBiGRU(
          self.n_layers, self.in_size, self.out_size, self.dropout
      )
  
      for layer in self.rnn:
          for p in layer.params():
              p.array[...] = numpy.random.uniform(-1, 1, p.shape)
      self.rnn.cleargrads()
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import gradient_check
  from chainer import links
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 1 for calling the TestNStepBiGRU obj's underlying member method code with example usage: obj.setUp() without return types