tf.keras.utils.SequenceEnqueuer

TensorFlow 1 version View source on GitHub

Base class to enqueue inputs.

tf.keras.utils.SequenceEnqueuer(
    sequence, use_multiprocessing=False
)

The task of an Enqueuer is to use parallelism to speed up preprocessing. This is done with processes or threads.

Example:

    enqueuer = SequenceEnqueuer(...)
    enqueuer.start()
    datas = enqueuer.get()
    for data in datas:
        # Use the inputs; training, evaluating, predicting.
        # ... stop sometime.
    enqueuer.stop()

The enqueuer.get() should be an infinite stream of datas.

Methods

get

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get()

Creates a generator to extract data from the queue.

Skip the data if it is None.

Returns

Generator yielding tuples `(inputs, targets)`
    or `(inputs, targets, sample_weights)`.

is_running

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is_running()

start

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start(
    workers=1, max_queue_size=10
)

Starts the handler's workers.

Arguments
workers Number of workers.
max_queue_size queue size (when full, workers could block on put())

stop

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stop(
    timeout=None
)

Stops running threads and wait for them to exit, if necessary.

Should be called by the same thread which called start().

Arguments
timeout maximum time to wait on thread.join()