skip passed work

[causten]

Still testing, but the idea is to skip a passed test if the current commit hash matches is marked as passed already

[pfultz2]

We should skip the entire stage including docker/cmake builds and even possibly checkout. This should probably be done in the node(name) section below, or before if possible since we are just checking a commit hash.

[pfultz2]

Even better would be to do it in(or around) the Check image stage. Set an env variable to a list of the contexes that are success, and then we can check that variable before we even allocate a node. It would also reduce the number github API calls we need to make(it would be once per build instead of once per build per stage).

[pfultz2]

I dont think storing it locally in the workspace is useful since it wont exist on every node. Instead you should check the github commit status, something like this:

    withCredentials([string(credentialsId: "${env.migraphx_ci_creds}", variable: 'GITHUB_TOKEN')]) {
        def commit_hash = sh(script: 'git rev-parse --short HEAD', returnStdout: true).trim()
        def response = sh(
            script: """curl -H "Accept: application/vnd.github+json" \
                           -H "Authorization: token ${GITHUB_TOKEN}" \
                           https://api.github.com/repos/ROCm/AMDMIGraphX/commits/${commit_hash}/status""",
            returnStdout: true
        ).trim()
        def statuses = response.statuses
        def contextStatus = statuses.find { it.context == "Jenkins - ${variant}"
        env.COMMIT_PASSED = contextStatus != null && contextStatus.state == 'success'
    }

[causten]

interesting, I was trying to use archieveAritfact since it would be shared across nodes, but I hadn't figured out a way to pull the file down. I like your idea and will try that

[migraphx-bot]

Test	Batch	Rate new 078757	Rate old 538898	Diff	Compare
torchvision-resnet50	64	3,260.03	3,259.25	0.02%	✅
torchvision-resnet50_fp16	64	6,978.06	6,987.98	-0.14%	✅
torchvision-densenet121	32	2,435.35	2,435.18	0.01%	✅
torchvision-densenet121_fp16	32	4,073.17	4,107.65	-0.84%	✅
torchvision-inceptionv3	32	1,637.92	1,638.45	-0.03%	✅
torchvision-inceptionv3_fp16	32	2,764.77	2,765.03	-0.01%	✅
cadene-inceptionv4	16	776.82	776.04	0.10%	✅
cadene-resnext64x4	16	811.14	811.47	-0.04%	✅
slim-mobilenet	64	7,537.11	7,532.97	0.05%	✅
slim-nasnetalarge	64	211.55	211.47	0.04%	✅
slim-resnet50v2	64	3,505.06	3,506.08	-0.03%	✅
bert-mrpc-onnx	8	1,151.78	1,145.67	0.53%	✅
bert-mrpc-tf	1	461.35	464.12	-0.60%	✅
pytorch-examples-wlang-gru	1	434.27	415.28	4.57%	🔆
pytorch-examples-wlang-lstm	1	387.14	382.85	1.12%	✅
torchvision-resnet50_1	1	761.93	775.95	-1.81%	✅
cadene-dpn92_1	1	406.74	403.42	0.82%	✅
cadene-resnext101_1	1	376.14	383.63	-1.95%	✅
onnx-taau-downsample	1	342.37	341.73	0.19%	✅
dlrm-criteoterabyte	1	33.35	33.34	0.04%	✅
dlrm-criteoterabyte_fp16	1	52.74	52.72	0.05%	✅
agentmodel	1	8,473.71	8,136.83	4.14%	🔆
unet_fp16	2	58.96	58.73	0.39%	✅
resnet50v1_fp16	1	1,001.92	968.97	3.40%	🔆
resnet50v1_int8	1	988.66	1,017.05	-2.79%	✅
bert_base_cased_fp16	64	1,172.25	1,171.55	0.06%	✅
bert_large_uncased_fp16	32	363.57	363.37	0.05%	✅
bert_large_fp16	1	200.60	199.99	0.30%	✅
distilgpt2_fp16	16	2,202.81	2,203.14	-0.02%	✅
yolov5s	1	540.11	530.68	1.78%	✅
tinyllama	1	43.44	43.42	0.05%	✅
vicuna-fastchat	1	174.56	178.25	-2.07%	✅
whisper-tiny-encoder	1	418.36	417.77	0.14%	✅
whisper-tiny-decoder	1	437.11	435.63	0.34%	✅

Check results before merge 🔆

[migraphx-bot]

     ✅ bert-mrpc-onnx: PASSED: MIGraphX meets tolerance

     ✅ bert-mrpc-tf: PASSED: MIGraphX meets tolerance

     ✅ pytorch-examples-wlang-gru: PASSED: MIGraphX meets tolerance

     ✅ pytorch-examples-wlang-lstm: PASSED: MIGraphX meets tolerance

     ✅ torchvision-resnet50_1: PASSED: MIGraphX meets tolerance

     ✅ cadene-dpn92_1: PASSED: MIGraphX meets tolerance

     ✅ cadene-resnext101_1: PASSED: MIGraphX meets tolerance

     ✅ dlrm-criteoterabyte: PASSED: MIGraphX meets tolerance

     ✅ agentmodel: PASSED: MIGraphX meets tolerance

     ✅ unet: PASSED: MIGraphX meets tolerance

     ✅ resnet50v1: PASSED: MIGraphX meets tolerance

     ✅ bert_base_cased_fp16: PASSED: MIGraphX meets tolerance

🔴bert_large_uncased_fp16: FAILED: MIGraphX is not within tolerance - check verbose output

     ✅ bert_large: PASSED: MIGraphX meets tolerance

     ✅ yolov5s: PASSED: MIGraphX meets tolerance

     ✅ tinyllama: PASSED: MIGraphX meets tolerance

     ✅ vicuna-fastchat: PASSED: MIGraphX meets tolerance

     ✅ whisper-tiny-encoder: PASSED: MIGraphX meets tolerance

     ✅ whisper-tiny-decoder: PASSED: MIGraphX meets tolerance

     ✅ distilgpt2_fp16: PASSED: MIGraphX meets tolerance