Feature/neural magic extension of the Elyra Tutorial

[pacospace]

Related Issues and Dependencies

Related-To: #297

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[sesheta]

AICoE CI results

Model and application metrics

The following table shows gathered metrics for model and application on your deployed models.

average_error	average_latency	average_probability	model_version	number_requests	namespace deployment	test URL
0	0.672843	0.991821	pr-446-inference	100	opf-ci-pipelines	https://github.com/AICoE/elyra-aidevsecops-tutorial/blob/9c64fa561d135a728b8c3b19dc99d00233505e0a/features
0.02	0.643769	0.989049	pr-446-pytorch-inference	100	opf-ci-pipelines	https://github.com/AICoE/elyra-aidevsecops-tutorial/blob/9c64fa561d135a728b8c3b19dc99d00233505e0a/features

Platform metrics

The following table shows gathered metrics from platform on your deployed models.

CPU max usage	Memory max usage	model_version
N/A	N/A	pr-446-inference
N/A	N/A	pr-446-pytorch-inference

[sesheta]

AICoE CI results

Model and application metrics

The following table shows gathered metrics for model and application on your deployed models.

average_error	average_latency	average_probability	model_version	number_requests	namespace deployment	test URL
0	0.679479	0.991821	pr-446-inference	100	opf-ci-pipelines	https://github.com/AICoE/elyra-aidevsecops-tutorial/blob/9c64fa561d135a728b8c3b19dc99d00233505e0a/features
0.01	0.60259	0.99216	pr-446-pytorch-inference	100	opf-ci-pipelines	https://github.com/AICoE/elyra-aidevsecops-tutorial/blob/9c64fa561d135a728b8c3b19dc99d00233505e0a/features

Platform metrics

The following table shows gathered metrics from platform on your deployed models.

CPU max usage	Memory max usage	model_version
N/A	N/A	pr-446-inference
N/A	N/A	pr-446-pytorch-inference

[pacospace]

/retest

[pacospace]

/retest

[sesheta]

AICoE CI results

Model and application metrics

The following table shows gathered metrics for model and application on your deployed models.

average_error	average_latency	average_probability	model_version	number_requests	namespace deployment	test URL
0	0.677138	0.991821	pr-446-inference	100	opf-ci-pipelines	https://github.com/AICoE/elyra-aidevsecops-tutorial/blob/519625e90802c18b7e0ea874ab887343cb62ec9b/features
0.02	0.780993	0.989103	pr-446-pytorch-inference	100	opf-ci-pipelines	https://github.com/AICoE/elyra-aidevsecops-tutorial/blob/519625e90802c18b7e0ea874ab887343cb62ec9b/features

Platform metrics

The following table shows gathered metrics from platform on your deployed models.

CPU max usage	Memory max usage	model_version
N/A	N/A	pr-446-inference
N/A	N/A	pr-446-pytorch-inference

[sesheta]

@pacospace: The following test failed, say /retest to rerun all failed tests:

Test name	Commit	Details	Rerun command
aicoe-ci/prow/mypy	635a13c	link	/test thoth-mypy-py38

Full PR test history. Your PR dashboard. Please help us and open an issue when you hit one in your PR.

Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.

[pacospace]

/approve

[sesheta]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: pacospace

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