V7 1539 - Multi Labels Dataset #201
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max_workers is always bound between `MAX_WORKERS` and the current system cpu count. `MAX_WORKERS` has been set to 5
missing `os` import
passing `max_workers` as parameter, if `None` `concurrent.futures.ThreadPoolExecutor` will use the system cpu number * 5. From the [doc](https://docs.python.org/3/library/concurrent.futures.html) Changed in version 3.5: If max_workers is None or not given, it will default to the number of processors on the machine, multiplied by 5, assuming that ThreadPoolExecutor is often used to overlap I/O instead of CPU work and the number of workers should be higher than the number of workers for ProcessPoolExecutor.
removed unused imports
andreaazzini
approved these changes
Sep 21, 2021
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Since the APIs are not test-friendly, the following code is not tested. It should work, please have a look.
ClassificationDatasetnow returns a Tensor of size 1 for single-label classification and a Tensor of size[C,1]for multi-label classification whereCis the number of classes