parameterize the finetuning test cases

[jayesh-tanna]

Description

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• The pull request does not introduce [breaking changes]
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Testing Guidelines

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[Copilot]

Pull request overview

This pull request refactors finetuning test cases by parametrizing them to reduce code duplication. The changes consolidate multiple individual test methods into single parametrized test methods using pytest.mark.parametrize, reducing the overall test code while maintaining the same test coverage.

Changes:

• Introduced new constants for method types (SUPERVISED_METHOD_TYPE, DPO_METHOD_TYPE, REINFORCEMENT_METHOD_TYPE) and model types (OPENAI_MODEL_TYPE, OSS_MODEL_TYPE) in test_base.py
• Consolidated 10+ individual create job tests into a single parametrized test_create_job method
• Consolidated 3 retrieve job tests into a single parametrized test_retrieve_job method
• Consolidated 10 cancel job tests into a single parametrized test_cancel_job method
• Consolidated 4 deploy and infer tests into a single parametrized test_deploy_and_infer_job method
• Applied the same refactoring pattern to both sync and async test files
• Removed unused os import from both test files
• Updated test recording assets (assets.json)

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

File	Description
sdk/ai/azure-ai-projects/tests/test_base.py	Added new constants for method types and model types to support parametrization
sdk/ai/azure-ai-projects/tests/finetuning/test_finetuning_async.py	Refactored async tests to use parametrization, added decorator wrappers for pytest compatibility, removed unused import
sdk/ai/azure-ai-projects/tests/finetuning/test_finetuning.py	Refactored sync tests to use parametrization with critical decorator ordering issue, added decorator wrappers, removed unused import
sdk/ai/azure-ai-projects/assets.json	Updated test recording assets tag to reflect new test structure