code: def generate_inputs(self):
      shape = self.shape
  
      # sample x such that x.std >= min_std
      min_std = 0.2 if self.dtype == numpy.float16 else 0.02
      retry = 0
      while True:
          x = numpy.random.uniform(-1, 1, shape).astype(self.dtype)
          x_groups = x.reshape(shape[0], self.groups, -1)
          if x_groups.std(axis=2).min() >= min_std:
              break
          retry += 1
          assert retry <= 20, "Too many retries to generate inputs"
  
      gamma = numpy.random.uniform(-1, 1, shape[1]).astype(self.dtype)
      beta = numpy.random.uniform(-1, 1, shape[1]).astype(self.dtype)
      return x, gamma, beta
  
file_path: chainer/tests/chainer_tests/functions_tests/normalization_tests/test_group_normalization.py
imports: import numpy
  import six
  from chainer import functions
  import chainer.functions.normalization.group_normalization
  from chainer import testing
label_desc: Use image node_id 2 for calling the TestGroupNormalization obj's underlying member method code with example usage: obj.generate_inputs() and returns: x,  gamma,  beta