text: from chainer import distributions
  from chainer import testing
  import numpy
  
  
  @testing.parameterize(*testing.product({
      'shape': [(2, 3), ()],
      'is_variable': [True, False],
      'sample_shape': [(3, 2), ()],
  }))
  @testing.fix_random()
  @testing.with_requires('scipy')
  class TestChisquare(testing.distribution_unittest):
  
      scipy_onebyone = True
  
      def setUp_configure(self):
          from scipy import stats
          self.dist = distributions.Chisquare
          self.scipy_dist = stats.chi2
  
          self.test_targets = set([
              "batch_shape", "entropy", "event_shape", "log_prob", "mean",
              "sample", "support", "variance"])
  
          k = numpy.random.randint(1, 10, self.shape).astype(numpy.float32)
          self.params = {"k": k}
          self.scipy_params = {"df": k}
  
          self.support = "positive"
  
      def sample_for_test(self):
          smp = numpy.random.chisquare(
              df=1, size=self.sample_shape + self.shape
          ).astype(numpy.float32)
          return smp
  
  
  testing.run_module(__name__, __file__)
  