Narendasan/int8 mixed precision fix #94
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overridden Signed-off-by: Naren Dasan <[email protected]> Signed-off-by: Naren Dasan <[email protected]>
Adds evaluators for: - aten::eq - aten::ne - aten::lt - aten::gt - aten::le - aten::ge - aten::add - aten::sub - aten::mul - aten::Bool - aten::Float - aten::__not__ - aten::__is__ - aten::__isnot__ - aten::numel - aten::dim - aten::div - aten::floordiv - aten::floor - aten::warn - prim::min - prim::max - prim::shape - prim::unchecked_cast - prim::Uninitalized - prim::RaiseException Signed-off-by: Naren Dasan <[email protected]> Signed-off-by: Naren Dasan <[email protected]>
Signed-off-by: Naren Dasan <[email protected]> Signed-off-by: Naren Dasan <[email protected]>
Signed-off-by: Naren Dasan <[email protected]> Signed-off-by: Naren Dasan <[email protected]>
int8 do not enable fp16 kernels Signed-off-by: Naren Dasan <[email protected]> Signed-off-by: Naren Dasan <[email protected]>
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Jan 5, 2023
…g to float (pytorch#94) * Support int inputs to aten::max/min and aten::argmax/argmin by casting to float * correct layer name * address nit, remove local variable
mfeliz-cruise
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Jan 9, 2023
…g to float (pytorch#94) * Support int inputs to aten::max/min and aten::argmax/argmin by casting to float * correct layer name * address nit, remove local variable
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Description
When int8 is enabled, we also need to enable fp16 kernels just in case those kernels provide a faster path. This explains significant performance differences between FP16 and INT8 in cases where most layers are not mapped to INT8 kernels.
Partially addresses #93
Type of change
Please delete options that are not relevant and/or add your own.
Checklist:
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