code: def applyOptimizer(self, opt, steps=5, is_sparse=False):
      if is_sparse:
          var0 = variables.Variable([[1.0], [2.0]])
          var1 = variables.Variable([[3.0], [4.0]])
          grads0 = indexed_slices.IndexedSlices(
              constant_op.constant([0.1], shape=[1, 1]),
              constant_op.constant([0]),
              constant_op.constant([2, 1]),
          )
          grads1 = indexed_slices.IndexedSlices(
              constant_op.constant([0.02], shape=[1, 1]),
              constant_op.constant([1]),
              constant_op.constant([2, 1]),
          )
      else:
          var0 = variables.Variable([1.0, 2.0])
          var1 = variables.Variable([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())
  
      sess = ops.get_default_session()
      v0_val, v1_val = self.evaluate([var0, var1])
      if is_sparse:
          self.assertAllClose([[1.0], [2.0]], v0_val)
          self.assertAllClose([[3.0], [4.0]], v1_val)
      else:
          self.assertAllClose([1.0, 2.0], v0_val)
          self.assertAllClose([3.0, 4.0], v1_val)
  
      # Run ProximalAdagrad for a few steps
      for _ in range(steps):
          update.run()
  
      v0_val, v1_val = self.evaluate([var0, var1])
      return v0_val, 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 8 for calling the ProximalAdagradOptimizerTest obj's underlying member method code with example usage: obj.applyOptimizer(opt, steps, is_sparse) and returns: v0_val,  v1_val