def setup_keyring(keyring_name):
    '''Setup the keyring'''
    keyring_path = os.path.join("test", "outputdata", keyring_name)
    # Delete the entire keyring
    shutil.rmtree(keyring_path, ignore_errors=True)
    os.makedirs(keyring_path)
    gpg = GPG(gnupghome=keyring_path, gpgbinary="gpg")
    for key_name in ["key1_private", "key1_public"]:
        with open(os.path.join("test", "inputdata", key_name + ".txt"), "r") as keyfile:
            key_str = "".join(keyfile.readlines())
        import_result = gpg.import_keys(key_str)
        print("Import result:", type(import_result))
        print(import_result.__dict__)
        if import_result.count == 1 and len(set(import_result.fingerprints)) == 1:
            print("Got one import result")
    return gpg
def testDense(self, dtype, param_value):
    (learning_rate, decay, momentum, epsilon, centered, use_resource) = tuple(
        param_value)
    with self.session(use_gpu=True):
      # Initialize variables for numpy implementation.
      var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype)
      grads0_np = np.array([0.1, 0.2], dtype=dtype.as_numpy_dtype)
      var1_np = np.array([3.0, 4.0], dtype=dtype.as_numpy_dtype)
      grads1_np = np.array([0.01, 0.2], dtype=dtype.as_numpy_dtype)

      if use_resource:
        var0 = resource_variable_ops.ResourceVariable(var0_np)
        var1 = resource_variable_ops.ResourceVariable(var1_np)
      else:
        var0 = variables.Variable(var0_np)
        var1 = variables.Variable(var1_np)
      grads0 = constant_op.constant(grads0_np)
      grads1 = constant_op.constant(grads1_np)
      opt = rmsprop.RMSPropOptimizer(
          learning_rate=learning_rate,
          decay=decay,
          momentum=momentum,
          epsilon=epsilon,
          centered=centered)

      update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
      variables.global_variables_initializer().run()

      mg0 = opt.get_slot(var0, "mg")
      self.assertEqual(mg0 is not None, centered)
      mg1 = opt.get_slot(var1, "mg")
      self.assertEqual(mg1 is not None, centered)
      rms0 = opt.get_slot(var0, "rms")
      self.assertIsNotNone(rms0)
      rms1 = opt.get_slot(var1, "rms")
      self.assertIsNotNone(rms1)
      mom0 = opt.get_slot(var0, "momentum")
      self.assertIsNotNone(mom0)
      mom1 = opt.get_slot(var1, "momentum")
      self.assertIsNotNone(mom1)

      mg0_np = np.array([0.0, 0.0], dtype=dtype.as_numpy_dtype)
      mg1_np = np.array([0.0, 0.0], dtype=dtype.as_numpy_dtype)
      rms0_np = np.array([epsilon, epsilon], dtype=dtype.as_numpy_dtype)
      rms1_np = np.array([epsilon, epsilon], dtype=dtype.as_numpy_dtype)
      mom0_np = np.array([0.0, 0.0], dtype=dtype.as_numpy_dtype)
      mom1_np = np.array([0.0, 0.0], dtype=dtype.as_numpy_dtype)

      # Fetch params to validate initial values
      self.assertAllClose([1.0, 2.0], var0.eval())
      self.assertAllClose([3.0, 4.0], var1.eval())

      # Run 4 steps of RMSProp
      for _ in range(4):
        update.run()

        var0_np, mg0_np, rms0_np, mom0_np = self._rmsprop_update_numpy(
            var0_np, grads0_np, mg0_np, rms0_np, mom0_np, learning_rate,
            decay, momentum, centered)
        var1_np, mg1_np, rms1_np, mom1_np = self._rmsprop_update_numpy(
            var1_np, grads1_np, mg1_np, rms1_np, mom1_np, learning_rate,
            decay, momentum, centered)

        # Validate updated params
        if centered:
          self.assertAllCloseAccordingToType(mg0_np, mg0.eval())
          self.assertAllCloseAccordingToType(mg1_np, mg1.eval())
        self.assertAllCloseAccordingToType(rms0_np, rms0.eval())
        self.assertAllCloseAccordingToType(rms1_np, rms1.eval())
        self.assertAllCloseAccordingToType(mom0_np, mom0.eval())
        self.assertAllCloseAccordingToType(mom1_np, mom1.eval())
        # TODO(b/117393988): Reduce tolerances for float16.
        self.assertAllCloseAccordingToType(
            var0_np, var0.eval(), half_rtol=3e-3, half_atol=3e-3)
        self.assertAllCloseAccordingToType(
            var1_np, var1.eval(), half_rtol=3e-3, half_atol=3e-3)