code: def generate_inputs(self):
      channels = 3
      shape = (5, channels) + (2,) * self.ndim
      dtype = self.dtype
      x = numpy.random.uniform(-1, 1, shape).astype(dtype)
      gamma = numpy.random.uniform(0.5, 1, (channels,)).astype(dtype)
      beta = numpy.random.uniform(-1, 1, (channels,)).astype(dtype)
      mean = numpy.random.uniform(-1, 1, (channels,)).astype(dtype)
      var = numpy.random.uniform(0.5, 1, (channels,)).astype(dtype)
      return x, gamma, beta, mean, var
  
imports: import numpy
  import six
  import chainer
  from chainer.functions.normalization import batch_renormalization
  from chainer import testing
  import chainerx
label_desc: Use image node_id 2 for calling the TestFixedBatchRenormalization obj's underlying member method code with example usage: obj.generate_inputs() and returns: x,  gamma,  beta,  mean,  var