code: def setUp(self):
      if self.dtype == numpy.float16:
          # Use fixed random values to avoid non-differential inputs
          uniform = numpy.random.RandomState(0).uniform
      else:
          uniform = numpy.random.uniform
  
      self.x = uniform(size=self.in_shape).astype(self.dtype)
      self.grid = uniform(low=-2, high=2, size=self.grid_shape).astype(
          self.dtype
      )
      self.grads = uniform(size=self.out_shape).astype(self.dtype)
  
      if self.dtype == numpy.float16:
          self.assert_options = {"atol": 1e-2}
      else:
          self.assert_options = {}
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import functions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import condition
  from chainer import Variable
label_desc: Use image node_id 1 for calling the TestSpatialTransformerSamplerConsistencyWithCuDNN obj's underlying member method code with example usage: obj.setUp() without return types