optimizers_test.py 文件源码

def testUpdateOp(self):
    optimizers = [
        "SGD", gradient_descent.GradientDescentOptimizer,
        gradient_descent.GradientDescentOptimizer(learning_rate=0.1)
    ]
    for optimizer in optimizers:
      with ops.Graph().as_default() as g, self.test_session(graph=g) as session:
        x, var, loss, global_step = _setup_model()
        update_var = variable_scope.get_variable(
            "update", [], initializer=init_ops.constant_initializer(10))
        update_op = state_ops.assign(update_var, 20)
        train = optimizers_lib.optimize_loss(
            loss,
            global_step,
            learning_rate=0.1,
            optimizer=optimizer,
            update_ops=[update_op])
        variables.global_variables_initializer().run()
        session.run(train, feed_dict={x: 5})
        self.assertEqual(9.5, var.eval())
        self.assertEqual(20, update_var.eval())
        self.assertEqual(1, global_step.eval())