code: def applyOptimizer(self, opt, steps=5):
      var0 = resource_variable_ops.ResourceVariable([1.0, 2.0])
      var1 = resource_variable_ops.ResourceVariable([3.0, 4.0])
      grads0 = constant_op.constant([0.1, 0.2])
      grads1 = constant_op.constant([0.01, 0.02])
  
      update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
      self.evaluate(variables.global_variables_initializer())
  
      self.assertAllClose([1.0, 2.0], self.evaluate(var0))
      self.assertAllClose([3.0, 4.0], self.evaluate(var1))
  
      # Run ProximalAdagrad for a few steps
      for _ in range(steps):
          update.run()
  
      return self.evaluate(var0), self.evaluate(var1)
  
file_path: tensorflow/tensorflow/compiler/tests/proximal_adagrad_test.py
imports: import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.framework import constant_op
  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 adagrad
  from tensorflow.python.training import proximal_adagrad
label_desc: Use image node_id 5 for calling the ProximalAdagradOptimizerTest obj's underlying member method code with example usage: obj.applyOptimizer(opt, steps) and returns: self,  self