E2E automation support for XGBoost model #1288
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Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
noopurintel
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Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
teoparvanov
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payalcha
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rahulga1
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Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
Signed-off-by: noopur <[email protected]>
rahulga1
approved these changes
Jan 21, 2025
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We already have automation in place for bare metal and dockerized approaches using pytest framework for various models.
This PR aims to extend that support for XGBoost model as well.
Important: - Currently, it isn't possible to include XGBoost in the GitHub workflows as the regular GitHub runners can't support the huge data size required for this model.
Changes done:
task_runner_dockerized_ws_e2e.yml--> removed 3.9 and added 3.12 python version.federated_runtime.yml--> removed author names, which was missed out in the previous PR.conftest.py--> added function calls to remove docker containers and networks, if any, in pytest_sessionfinish.Successful runs: