MLflow is an open-source platform designed to manage the machine learning lifecycle, including experimentation, reproducibility, and deployment. It provides tools for tracking experiments, packaging code into reproducible runs, and sharing and deploying models. The MLflow Tracking component is particularly useful for logging and querying experiments, making it easier to manage and compare different runs.
When working with MLflow, you might encounter the error message: mlflow.exceptions.MlflowException: Run '...' not found. This error typically occurs when attempting to access a run that MLflow cannot locate in its tracking server.
The error mlflow.exceptions.MlflowException: Run '...' not found indicates that the specified run ID does not exist in the MLflow tracking server. This can happen due to a typo in the run ID, or if the run has been removed or was never created.
Each run in MLflow is assigned a unique identifier known as a run ID. This ID is crucial for tracking and retrieving specific runs. If the run ID is incorrect or the run has been deleted, MLflow will not be able to find it, resulting in this exception.
To resolve this issue, follow these steps:
Ensure that the run ID you are using is correct. You can list all available runs using the MLflow UI or the MLflow CLI. To list runs via the CLI, use the following command:
mlflow runs list
This command will display all runs, allowing you to verify the correct run ID.
Ensure that the MLflow tracking server is running and accessible. You can start the tracking server using:
mlflow server
Make sure you are connected to the correct tracking server where the runs are logged.
If the run was deleted, it will not be retrievable. Consider checking the logs or any backup to confirm if the run was removed.
For more information on MLflow and managing runs, consider visiting the following resources:
(Perfect for DevOps & SREs)
(Perfect for DevOps & SREs)
