keras/engine/training_generator.py [290:330]:
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    is_sequence = isinstance(generator, Sequence)
    if not is_sequence and use_multiprocessing and workers > 1:
        warnings.warn(
            UserWarning('Using a generator with `use_multiprocessing=True`'
                        ' and multiple workers may duplicate your data.'
                        ' Please consider using the`keras.utils.Sequence'
                        ' class.'))
    if steps is None:
        if is_sequence:
            steps = len(generator)
        else:
            raise ValueError('`steps=None` is only valid for a generator'
                             ' based on the `keras.utils.Sequence` class.'
                             ' Please specify `steps` or use the'
                             ' `keras.utils.Sequence` class.')
    enqueuer = None

    try:
        if workers > 0:
            if is_sequence:
                enqueuer = OrderedEnqueuer(
                    generator,
                    use_multiprocessing=use_multiprocessing)
            else:
                enqueuer = GeneratorEnqueuer(
                    generator,
                    use_multiprocessing=use_multiprocessing,
                    wait_time=wait_time)
            enqueuer.start(workers=workers, max_queue_size=max_queue_size)
            output_generator = enqueuer.get()
        else:
            if is_sequence:
                output_generator = iter_sequence_infinite(generator)
            else:
                output_generator = generator

        if verbose == 1:
            progbar = Progbar(target=steps)

        while steps_done < steps:
            generator_output = next(output_generator)
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keras/engine/training_generator.py [395:435]:
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    is_sequence = isinstance(generator, Sequence)
    if not is_sequence and use_multiprocessing and workers > 1:
        warnings.warn(
            UserWarning('Using a generator with `use_multiprocessing=True`'
                        ' and multiple workers may duplicate your data.'
                        ' Please consider using the`keras.utils.Sequence'
                        ' class.'))
    if steps is None:
        if is_sequence:
            steps = len(generator)
        else:
            raise ValueError('`steps=None` is only valid for a generator'
                             ' based on the `keras.utils.Sequence` class.'
                             ' Please specify `steps` or use the'
                             ' `keras.utils.Sequence` class.')
    enqueuer = None

    try:
        if workers > 0:
            if is_sequence:
                enqueuer = OrderedEnqueuer(
                    generator,
                    use_multiprocessing=use_multiprocessing)
            else:
                enqueuer = GeneratorEnqueuer(
                    generator,
                    use_multiprocessing=use_multiprocessing,
                    wait_time=wait_time)
            enqueuer.start(workers=workers, max_queue_size=max_queue_size)
            output_generator = enqueuer.get()
        else:
            if is_sequence:
                output_generator = iter_sequence_infinite(generator)
            else:
                output_generator = generator

        if verbose == 1:
            progbar = Progbar(target=steps)

        while steps_done < steps:
            generator_output = next(output_generator)
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