class_docstr: Optimizer used for testing the BoltOn optimizer.
class_docstr_tok: ["Optimizer","used","for","testing","the","BoltOn","optimizer","."]
code: def apply_gradients(self, grads_and_vars, name=None):
      return "test"
  
imports: import unittest
  from absl.testing import parameterized
  import tensorflow.compat.v1
  from tensorflow.compat.v1.python import ops
  from tensorflow.compat.v1.python.framework import test_util
  from tensorflow.compat.v1.python.keras import keras_parameterized
  from tensorflow.compat.v1.python.keras import losses
  from tensorflow.compat.v1.python.keras.initializers import constant
  from tensorflow.compat.v1.python.keras.models import Model
  from tensorflow.compat.v1.python.keras.optimizer_v2.optimizer_v2 import OptimizerV2
  from tensorflow.compat.v1.python.keras.regularizers import L1L2
  from tensorflow.compat.v1.python.platform import test
  from tensorflow_privacy.privacy.bolt_on import optimizers
  from tensorflow_privacy.privacy.bolt_on.losses import StrongConvexMixin
label_desc: Use image node_id 9 for calling the TestOptimizer obj's underlying member method code with example usage: obj.apply_gradients(grads_and_vars, name) and returns: str