Add checkpoint artifact path prefix to MLflow logger #20538
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Add a new `checkpoint_artifact_path_prefix` parameter to the MLflow logger. * Modify `src/lightning/pytorch/loggers/mlflow.py` to include the new parameter in the `MLFlowLogger` class constructor and use it in the `after_save_checkpoint` method. * Update the documentation in `docs/source-pytorch/visualize/loggers.rst` to include the new `checkpoint_artifact_path_prefix` parameter. * Add a new test in `tests/tests_pytorch/loggers/test_mlflow.py` to verify the functionality of the `checkpoint_artifact_path_prefix` parameter and ensure it is used in the artifact path. --- For more details, open the [Copilot Workspace session](https://copilot-workspace.githubnext.com/Lightning-AI/pytorch-lightning?shareId=XXXX-XXXX-XXXX-XXXX).
benglewis
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Add a new
checkpoint_artifact_path_prefixparameter to the MLflow logger.src/lightning/pytorch/loggers/mlflow.pyto include the new parameter in theMLFlowLoggerclass constructor and use it in theafter_save_checkpointmethod.docs/source-pytorch/visualize/loggers.rstto include the newcheckpoint_artifact_path_prefixparameter.tests/tests_pytorch/loggers/test_mlflow.pyto verify the functionality of thecheckpoint_artifact_path_prefixparameter and ensure it is used in the artifact path.For more details, open the Copilot Workspace session.
📚 Documentation preview 📚: https://pytorch-lightning--20538.org.readthedocs.build/en/20538/