code: def testEquivAdagradwithoutRegularization(self):
      steps = 5
      for dtype in self.float_types:
          with self.session(), self.test_scope():
              val0, val1 = self.equivAdagradTest_FtrlPart(steps, dtype)
          with self.session(), self.test_scope():
              val2, val3 = self.equivAdagradTest_AdagradPart(
                  steps, dtype
              )
  
      self.assertAllCloseAccordingToType(
          val0, val2, rtol=1e-4, half_rtol=1e-2
      )
      self.assertAllCloseAccordingToType(
          val1, val3, rtol=1e-4, half_rtol=1e-2
      )
  
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 ftrl
  from tensorflow.python.training import gradient_descent
label_desc: Use image node_id 12 for calling the FtrlOptimizerTest obj's underlying member method code with example usage: obj.testEquivAdagradwithoutRegularization() without return types