human
Solve the following python programming problem given the following code:
# Create input function for train and eval
def read_dataset(filename, mode, batch_size = 512):
    def _input_fn():
        def decode_csv(value_column):
            columns = tf.decode_csv(records = value_column, record_defaults = DEFAULTS)
            features = dict(zip(CSV_COLUMNS, columns))          
            label = features.pop(LABEL_COLUMN)         
            return features, label

        # Create list of files that match pattern
        file_list = tf.gfile.Glob(filename = filename)

        # Create dataset from file list
        dataset = tf.data.TextLineDataset(filenames = file_list).map(map_func = decode_csv)

        if mode == tf.estimator.ModeKeys.TRAIN:
            num_epochs = None # indefinitely
            dataset = dataset.shuffle(buffer_size = 10 * batch_size)
        else:
            num_epochs = 1 # end-of-input after this

        dataset = dataset.repeat(count = num_epochs).batch(batch_size = batch_size)
        return dataset.make_one_shot_iterator().get_next()
    return _input_fn
Given the above code, generate some markdown instructions for it.
assistant
#Here is the Python program you requested.

Create input function for training and evaluation to read from our preprocessed CSV files.