human
I wrote the below code

    end_points = {}
    def add_and_check_final(name, net):
        end_points[name] = net
        return (name == final_endpoint)
    with tf.variable_scope(scope, 'InceptionV4', [inputs]):
        with slim.arg_scope([slim.conv2d, slim.max_pool2d, slim.avg_pool2d], stride=1, padding='SAME'):
            net = slim.conv2d(inputs, 32, [3, 3], stride=2, padding='VALID', scope='Conv2d_1a_3x3')
            if add_and_check_final('Conv2d_1a_3x3', net):
                return (net, end_points)
            net = slim.conv2d(net, 32, [3, 3], padding='VALID', scope='Conv2d_2a_3x3')
            if add_and_check_final('Conv2d_2a_3x3', net):
                return (net, end_points)
            net = slim.conv2d(net, 64, [3, 3], scope='Conv2d_2b_3x3')
            if add_and_check_final('Conv2d_2b_3x3', net):
                return (net, end_points)
            with tf.variable_scope('Mixed_3a'):
                with tf.variable_scope('Branch_0'):
                    branch_0 = slim.max_pool2d(net, [3, 3], stride=2, padding='VALID', scope='MaxPool_0a_3x3')
                with tf.variable_scope('Branch_1'):
                    branch_1 = slim.conv2d(net, 96, [3, 3], stride=2, padding='VALID', scope='Conv2d_0a_3x3')
                net = tf.concat(axis=3, values=[branch_0, branch_1])
                if add_and_check_final('Mixed_3a', net):
                    return (net, end_points)
            with tf.variable_scope('Mixed_4a'):
                with tf.variable_scope('Branch_0'):
                    branch_0 = slim.conv2d(net, 64, [1, 1], scope='Conv2d_0a_1x1')
                    branch_0 = slim.conv2d(branch_0, 96, [3, 3], padding='VALID', scope='Conv2d_1a_3x3')
                with tf.variable_scope('Branch_1'):
                    branch_1 = slim.conv2d(net, 64, [1, 1], scope='Conv2d_0a_1x1')
                    branch_1 = slim.conv2d(branch_1, 64, [1, 7], scope='Conv2d_0b_1x7')
                    branch_1 = slim.conv2d(branch_1, 64, [7, 1], scope='Conv2d_0c_7x1')
                    branch_1 = slim.conv2d(branch_1,...

What's a good function header?

=====
Here's a good function header?
assistant
#Here's a good function header.

def inception_v4_base(inputs, final_endpoint='Mixed_7d', scope=None):