code: def setUp(self):
      self.stride = 2
      self.pad = 1
      batch_sz = 2
      in_channels_a_group = 64
      out_channels_a_group = 64
      in_channels = in_channels_a_group * self.groups
      out_channels = out_channels_a_group * self.groups
      kh, kw = (3, 3)
      in_h, in_w = (32, 128)
      out_h, out_w = (16, 64)
      # should be same types for cudnn test
      x_dtype = numpy.float32
      W_dtype = numpy.float32
      self.W = numpy.random.normal(
          0,
          numpy.sqrt(1.0 / (kh * kw * in_channels_a_group)),
          (out_channels, in_channels_a_group, kh, kw),
      ).astype(W_dtype)
      self.b = numpy.random.uniform(-1, 1, out_channels).astype(x_dtype)
      self.x = numpy.random.uniform(
          -1, 1, (batch_sz, in_channels, in_h, in_w)
      ).astype(x_dtype)
      self.gy = numpy.random.uniform(
          -1, 1, (batch_sz, out_channels, out_h, out_w)
      ).astype(x_dtype)
      self.should_call_cudnn = True
      if self.groups > 1 and cuda.cuda.cudnn.getVersion() < 7000:
          self.should_call_cudnn = False
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  import chainer.functions
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import backend
label_desc: Use image node_id 1 for calling the TestConvolution2DFunctionCudnnDeterministic obj's underlying member method code with example usage: obj.setUp() without return types