human
I wrote the below code

    if ((output_stride != 8) and (output_stride != 16)):
        raise ValueError('output_stride    must    be    8    or    16.')
    padding = ('SAME' if align_feature_maps else 'VALID')
    end_points = {}
    def add_and_check_final(name, net):
        end_points[name] = net
        return (name == final_endpoint)
    with tf.variable_scope(scope, 'InceptionResnetV2', [inputs]):
        with slim.arg_scope([slim.conv2d, slim.max_pool2d, slim.avg_pool2d], stride=1, padding='SAME'):
            net = slim.conv2d(inputs, 32, 3, stride=2, padding=padding, scope='Conv2d_1a_3x3')
            if add_and_check_final('Conv2d_1a_3x3', net):
                return (net, end_points)
            net = slim.conv2d(net, 32, 3, padding=padding, scope='Conv2d_2a_3x3')
            if add_and_check_final('Conv2d_2a_3x3', net):
                return (net, end_points)
            net = slim.conv2d(net, 64, 3, scope='Conv2d_2b_3x3')
            if add_and_check_final('Conv2d_2b_3x3', net):
                return (net, end_points)
            net = slim.max_pool2d(net, 3, stride=2, padding=padding, scope='MaxPool_3a_3x3')
            if add_and_check_final('MaxPool_3a_3x3', net):
                return (net, end_points)
            net = slim.conv2d(net, 80, 1, padding=padding, scope='Conv2d_3b_1x1')
            if add_and_check_final('Conv2d_3b_1x1', net):
                return (net, end_points)
            net = slim.conv2d(net, 192, 3, padding=padding, scope='Conv2d_4a_3x3')
            if add_and_check_final('Conv2d_4a_3x3', net):
                return (net, end_points)
            net = slim.max_pool2d(net, 3, stride=2, padding=padding, scope='MaxPool_5a_3x3')
            if add_and_check_final('MaxPool_5a_3x3', net):
                return (net, end_points)
            with tf.variable_scope('Mixed_5b'):
                with tf.variable_scope('Branch_0'):
                    tower_conv = slim.conv2d(net, 96, 1, scope='Conv2d_1x1')
                with tf.variable_scope('Branch_1'):
                    tower_conv1_0 =...

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

def inception_resnet_v2_base(inputs, final_endpoint='Conv2d_7b_1x1', output_stride=16, align_feature_maps=False, scope=None):