human
Here's a good function header given the following:
I wrote the below code

    if ('image' in data_file_pattern):
        def resize(img, size):
            return tf.to_int64(tf.image.resize_images(img, [size, size]))
        if ('img2img' in data_file_pattern):
            inputs = examples['inputs']
            examples['inputs'] = resize(inputs, 16)
            examples['targets'] = resize(inputs, 64)
        elif ('image_celeba' in data_file_pattern):
            inputs = examples['inputs']
            examples['inputs'] = resize(inputs, 8)
            examples['targets'] = resize(inputs, 32)
    elif ('audio' in data_file_pattern):
        sample_count = tf.to_int32(examples.pop('audio/sample_count'))
        sample_width = tf.to_int32(examples.pop('audio/sample_width'))
        channel_count = 1
        examples['inputs'] = tf.reshape(examples['inputs'], [sample_count, sample_width, channel_count])
        if ('wsj' in data_file_pattern):
            examples['inputs'] = tf.bitcast(examples['inputs'], tf.int32)
    elif ('a2q_20161229' in data_file_pattern):
        examples['targets'] = tf.concat([examples['targets'], [1]], 0)
    return examples

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

def preprocessing(examples, data_file_pattern):