code: def testNegativeSigmaFails(self):
      with self.assertRaisesOpError("Condition x > 0 did not hold"):
          normal = normal_lib.Normal(
              loc=[1.0], scale=[-5.0], validate_args=True, name="G"
          )
          self.evaluate(normal.mean())
  
imports: import importlib
  import math
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.ops.distributions import normal
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 28 for calling the NormalTest obj's underlying member method code with example usage: obj.testNegativeSigmaFails() without return types