code: def check_backward_zero_input(self, x_data):
      x = chainer.Variable(x_data)
      y = distributions.utils._modified_xlogx(x)
      if numpy.prod(y.shape) > 1:
          y = chainer.functions.sum(y)
      with testing.assert_warns(RuntimeWarning):
          y.backward()
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import distributions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 11 for calling the TestModifiedXLogX obj's underlying member method code with example usage: obj.check_backward_zero_input(x_data) without return types