oneapi-src / oneDNN

oneAPI Deep Neural Network Library (oneDNN)
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Bnorm tests are mistrusted on aarch64 #1973

Open Ryo-not-rio opened 1 week ago

Ryo-not-rio commented 1 week ago

Summary

When running ./tests/benchdnn/benchdnn -v5 --bnorm --tag=axb --dir=FWD_I --flags=G,GR --attr-post-ops=relu:0.5,linear:3.4:5.0+tanh --inplace=true,false mb1ic19id4ih6iw6nbnorm_3d:2 on aarch64, 2 of the 8 tests are mistrusted.

The same occurs when running with --skip-impl=acl with the simple:any kernels being run, which suggests the cause to be outside of acl.

Version

v3.6.0 (commit 094cc1dda4a24ccf0a54987a34c4475e00a926f9)

Environment

oneDNN includes hardware-specific optimizations and may behave differently on depending on the compiler and build environment. Include the following information to help reproduce the issue:

Steps to reproduce

Run ./tests/benchdnn/benchdnn -v5 --bnorm --tag=axb --dir=FWD_I --flags=G,GR --attr-post-ops=relu:0.5,linear:3.4:5.0+tanh --inplace=true,false mb1ic19id4ih6iw6nbnorm_3d:2

Observed behavior

tests:8 passed:6 skipped:0 mistrusted:2 unimplemented:0 invalid_arguments:0 failed:0 listed:0

Expected behavior

tests:8 passed:8 skipped:0 mistrusted:0 unimplemented:0 invalid_arguments:0 failed:0 listed:0

dzarukin commented 1 week ago

Hi @Ryo-not-rio, this is rather a benchdnn filling peculiarity rather than an issue. The mistrust status just tips that there are more zeros in the output than it should, but the benchmark decides what the number of zeros is expected. It can be treated as passed, it's a suggestion for developers to look into the problem as 100% of zeros can be in the output and it would be impossible to say if the test actually verifies the functionality.