optimizers_test.py 文件源码

def testNoGlobalStepWithDecay(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):
        x = array_ops.placeholder(dtypes.float32, [])
        var = variable_scope.get_variable(
            "test", [], initializer=init_ops.constant_initializer(10))
        loss = math_ops.abs(var * x)
        update_var = variable_scope.get_variable(
            "update", [], initializer=init_ops.constant_initializer(10))
        update_op = state_ops.assign(update_var, 20)
        with self.assertRaisesRegexp(
            ValueError, "global_step is required for learning_rate_decay_fn"):
          optimizers_lib.optimize_loss(
              loss,
              global_step=None,
              learning_rate=0.1,
              learning_rate_decay_fn=_no_op_learning_rate_decay_fn,
              optimizer=optimizer,
              update_ops=[update_op])