[tensorflow-pytorch-aarch64--r22.09] TensorFlow docker images are broken about tool-solutions HOT 2 OPEN

Thanks for the report @snadampal, we'll look into it.
Our builds include a few accuracy tests, on the Python examples, on the CPP examples, and on the MLCommons examples - however, the MLCommons accuracy test employs --count=1 expecting 100% accuracy.

Could you provide more details of the failure? Run lines, logs etc. and environment (what platform, is 'fast maths' enabled, etc.)

Many thanks.

from tool-solutions.

Hi @nSircombe , the issue was observed only for fast math enabled with bf16 kernels.

export DNNL_DEFAULT_FPMATH_MODE=BF16
run commands:
MLCommons/inference/vision/classification_detection: ./run_local.sh tf resnet50 cpu --accuracy

Failing scenario log: (r22.09 tag)
TestScenario.SingleStream qps=68.64, mean=0.0144, time=7.284, acc=2.600%, queries=500, tiles=50.0:0.0144,80.0:0.0145,90.0:0.0146,95.0:0.0147,99.0:0.0148,99.9:0.0151

Passing scenario logs: (r22.08 tag)
TestScenario.SingleStream qps=66.96, mean=0.0148, time=7.467, acc=76.200%, queries=500, tiles=50.0:0.0147,80.0:0.0149,90.0:0.0150,95.0:0.0151,99.0:0.0153,99.9:0.0159

from tool-solutions.