code: def setUp(self):
      x_shape = (self.batchsize, self.input_dim)
      retry = 0
      while True:
          self.x0 = numpy.random.uniform(-1, 1, x_shape).astype(
              self.dtype
          )
          self.x1 = numpy.random.uniform(-1, 1, x_shape).astype(
              self.dtype
          )
          d = numpy.sqrt(numpy.sum((self.x0 - self.x1) ** 2, axis=1))
          if (d > 3e-2).all() and (
              numpy.abs(d - self.margin) > 1e-2
          ).all():
              break
          retry += 1
          assert retry <= 10, "Too many retries to generate inputs"
      self.t = numpy.random.randint(0, 2, (self.batchsize,)).astype(
          self.label_dtype
      )
      if self.reduce == "mean":
          self.gy = numpy.random.uniform(-1, 1, ()).astype(self.dtype)
      else:
          self.gy = numpy.random.uniform(
              -1, 1, (self.batchsize,)
          ).astype(self.dtype)
      self.gx0 = numpy.random.uniform(-1, 1, x_shape).astype(self.dtype)
      self.gx1 = numpy.random.uniform(-1, 1, x_shape).astype(self.dtype)
  
imports: import math
  import unittest
  import numpy
  import six
  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
label_desc: Use image node_id 1 for calling the TestContrastive obj's underlying member method code with example usage: obj.setUp() without return types