code: def testProximalAdagradwithoutRegularization2(self):
      with self.session(), self.test_scope():
          var0 = resource_variable_ops.ResourceVariable([1.0, 2.0])
          var1 = resource_variable_ops.ResourceVariable([4.0, 3.0])
          grads0 = constant_op.constant([0.1, 0.2])
          grads1 = constant_op.constant([0.01, 0.02])
  
          opt = proximal_adagrad.ProximalAdagradOptimizer(
              3.0,
              initial_accumulator_value=0.1,
              l1_regularization_strength=0.0,
              l2_regularization_strength=0.0,
          )
          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([4.0, 3.0], self.evaluate(var1))
  
          # Run 3 steps Proximal Adagrad.
          for _ in range(3):
              update.run()
          self.assertAllClose(
              np.array([-1.60261, -2.296985]), self.evaluate(var0)
          )
          self.assertAllClose(
              np.array([3.715679, 2.433051]), 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 2 for calling the ProximalAdagradOptimizerTest obj's underlying member method code with example usage: obj.testProximalAdagradwithoutRegularization2() without return types