Classify sample by learn block

Classify a complete file against the specified learn block. This will move the sliding window
(dependent on the sliding window length and the sliding window increase parameters in the impulse)
over the complete file, and classify for every window that is extracted. Depending on the size of your
file, whether your sample is resampled, and whether the result is cached you'll get either the result
or a job back. If you receive a job, then wait for the completion of the job, and then call this
function again to receive the results. The unoptimized (float32) model is used by default, and
classification with an optimized (int8) model can be slower.

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