def read_dataset()

in 10_mlops/model.py [0:0]

• 17 lines of code
• 3 McCabe index (conditional complexity)

def read_dataset(pattern, batch_size, mode=tf.estimator.ModeKeys.TRAIN, truncate=None):
    dataset = tf.data.experimental.make_csv_dataset(
        pattern, batch_size,
        column_names=CSV_COLUMNS,
        column_defaults=CSV_COLUMN_TYPES,
        sloppy=True,
        num_parallel_reads=2,
        ignore_errors=True,
        num_epochs=1)
    dataset = dataset.map(features_and_labels)
    if mode == tf.estimator.ModeKeys.TRAIN:
        dataset = dataset.shuffle(batch_size * 10)
        dataset = dataset.repeat()
    dataset = dataset.prefetch(1)
    if truncate is not None:
        dataset = dataset.take(truncate)
    return dataset