tf.keras.utils.SequenceEnqueuer

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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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/utils/SequenceEnqueuer