code: def setUp(self):
      class Model(chainer.Chain):
          def __call__(self, x):
              mean = x.array.mean(axis=0)
              var = x.array.var(axis=0)
              gamma = np.ones_like(mean, dtype=x.dtype)
              beta = np.zeros_like(mean, dtype=x.dtype)
              return F.fixed_batch_normalization(
                  x, gamma, beta, mean, var
              )
  
      self.model = Model()
      self.x = input_generator.increasing(2, 5)
  
imports: import chainer
  import chainer.functions
  import chainer.links
  from chainer import testing
  import numpy
  from onnx_chainer.testing import input_generator
  from onnx_chainer_tests.helper import get_initializer_names
  from onnx_chainer_tests.helper import ONNXModelTest
label_desc: Use image node_id 1 for calling the TestFixedBatchNormalizationFunctionImplicitInputs obj's underlying member method code with example usage: obj.setUp() and returns: F