Use multiprocessing instead of torch for MPFuture#668
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #668 +/- ##
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- Coverage 85.39% 85.31% -0.09%
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Files 81 96 +15
Lines 8006 8609 +603
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+ Hits 6837 7345 +508
- Misses 1169 1264 +95
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- Revert hivemind/averaging/control.py to torch-based implementation (averaging module already depends on torch, no benefit from SharedMemory) - Move torch.multiprocessing.set_sharing_strategy() call from mpfuture.py to hivemind/__init__.py (global setting for all torch shared memory)
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