TensorFlow

API

 tf.keras / utils / utils.Progbar


Base class to enqueue inputs.

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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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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start

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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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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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