code: def testProximalAdagradWithL1_L2(self):
      # ProximalAdagradOptimizer is supported only in V1.
      with ops.Graph().as_default(), self.cached_session():
          var0 = variables.Variable([1.0, 2.0])
          var1 = variables.Variable([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=0.001,
              l2_regularization_strength=2.0,
          )
          update = opt.apply_gradients(
              zip([grads0, grads1], [var0, var1])
          )
          self.evaluate(variables.global_variables_initializer())
  
          v0_val, v1_val = self.evaluate([var0, var1])
          self.assertAllClose([1.0, 2.0], v0_val)
          self.assertAllClose([4.0, 3.0], v1_val)
  
          # Run 10 steps Proximal Adagrad.
          for _ in range(10):
              update.run()
  
          v0_val, v1_val = self.evaluate([var0, var1])
          self.assertAllClose(np.array([-0.0495, -0.0995]), v0_val)
          self.assertAllClose(np.array([-0.0045, -0.0095]), v1_val)
  
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import embedding_ops
  from tensorflow.python.ops import math_ops
  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 7 for calling the ProximalAdagradOptimizerTest obj's underlying member method code with example usage: obj.testProximalAdagradWithL1_L2() without return types