code: def testPassingNoneToLossScale(self):
      opt = gradient_descent.GradientDescentOptimizer(1.0)
      with self.assertRaisesRegex(
          ValueError, r"loss_scale cannot be None"
      ):
          loss_scale_optimizer.MixedPrecisionLossScaleOptimizer(
              opt, None
          )
  
imports: import os
  from absl.testing import parameterized
  from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import mirrored_strategy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import gradient_descent
  from tensorflow.python.training import momentum
  from tensorflow.python.training.experimental import loss_scale
  from tensorflow.python.training.experimental import loss_scale_optimizer
label_desc: Use image node_id 9 for calling the MixedPrecisionLossScaleOptimizerTest obj's underlying member method code with example usage: obj.testPassingNoneToLossScale() without return types