tf.keras.utils.SequenceEnqueuer

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Class SequenceEnqueuer

Base class to enqueue inputs.

Aliases:

  • Class tf.compat.v1.keras.utils.SequenceEnqueuer
  • Class tf.compat.v2.keras.utils.SequenceEnqueuer

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.close()

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

__init__

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__init__(
    sequence,
    use_multiprocessing=False
)

Initialize self. See help(type(self)) for accurate signature.

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()

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