[BYOC] [ACL] 20.05 memory corruption temporarely fix #6724
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d-smirnov
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@merrymercy Please advise on failed Integration Test / docs: GPU. I cannot reproduce failure of tutorials/auto_scheduler/tune_matmul_x86.py locally |
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See #6723 |
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lhutton1
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Oct 22, 2020
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@lhutton Some operations of ACL up to 20.11 requires data to be vector-friendly. In squeezenet there is an avg_pool2d operator with specific tensor layout ((1, 13, 13, 1001), float32). |
Makes sense, thanks for the clarification :) |
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comaniac
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Nov 5, 2020
This workaround prevents execution of operations via ACL runtime in case if arguments or output tensor require memory padding. Workaround is applicable to all ACL versions prior forecoming ACL 20.11 (which will not use data padding).
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Thanks @d-smirnov @lhutton1 |
trevor-m
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This workaround prevents execution of operations via ACL runtime in case if arguments or output tensor require memory padding. Workaround is applicable to all ACL versions prior forecoming ACL 20.11 (which will not use data padding).
trevor-m
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This workaround prevents execution of operations via ACL runtime in case if arguments or output tensor require memory padding. Workaround is applicable to all ACL versions prior forecoming ACL 20.11 (which will not use data padding).
trevor-m
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Dec 4, 2020
This workaround prevents execution of operations via ACL runtime in case if arguments or output tensor require memory padding. Workaround is applicable to all ACL versions prior forecoming ACL 20.11 (which will not use data padding).
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This fix intended to prevent execution of operations via ACL runtime
in case if its arguments require memory padding. This fix is tempоrary
and intended for ACL 20.05 and should be removed after migration
to ACL 20.11