agent-mlflow-skill-selected-run-test

Run test files for machine learning models are generated automatically by converting existing templates like runtest.py into format-specific test scripts. The tool supports sklearn, PyTorch, TensorFlow, and ONNX model formats for consistent testing.

Creating smoke tests for selected ML models is handled by converting a base test template into tailored test files. This approach supports multiple frameworks including sklearn, PyTorch, TensorFlow, and ONNX to ensure consistent testing practices.

Run test file generation works with PyTorch, TensorFlow, sklearn, and ONNX model formats. It adapts existing templates to the specific format of your selected model, ensuring the generated test file matches your framework requirements.

Template conversion creates test files by taking an existing script like runtest.py and transforming it into a new file like runtest_2.py. The resulting file is tailored to validate the specific machine learning model format you selected.

Standardizing ML testing practices across projects is the primary goal of the template conversion process. By generating consistent run test files from a base template, it ensures uniform smoke testing workflows for all selected models.