- Use the InfinStor service dashboard to obtain a token file for authentication
- Configure environment variable MLFLOW_TRACKING_URI
- Use mlflow cli programs or run python programs with MLflow api calls. MLflow example xgboost is shown here
- Use mlflow UI to view the experiment run
Token file for Auth¶
The InfinStor service dashboard is available at https://service.infinstor.com. Login using your provided credentials and click on Configuration -> Manage Token in the sidebar
Create and Download Token File
Pressing the 'Create Token File' button causes a new tab to be opened, and the user will flow through the InfinStor main service' cognito authetication. In the case of Enterprise Licenses, users will have to complete the authentication system configured for that particular Enterprise.
Note that in the case of Enterprise License versions of InfinStor, the service dashboard will be available at a different URL. Please contact your admin for this information
Use Token File for authenticating CLI programs
Once authentication is complete, the browser will download a file named token. This token file must be placed in a sub-directory called .infinstor in the user's home directory.
$ mkdir -p ~/.infinstor $ cp ~/Downloads/token ~/.infinstor
MLFLOW_TRACKING_URI env var¶
InfinStor MLflow backend is activated by setting the environment variable MLFLOW_TRACKING_URI to infinstor://mlflow.infinstor.com/
$ export MLFLOW_TRACKING_URI=infinstor://mlflow.infinstor.com/ $ mlflow experiments list
Note that in the case of Enterprise License versions of InfinStor, the InfinStor mlflow REST endpoint will be different. For example, an Enterprise called xyz.com may have installed InfinStor at mlflowrest.xyz.com. In that case MLFLOW_TRACKING_URI must be set to infinstor://mlflowrest.xyz.com/. Please contact your admin for this information
The example xgboost supplied with open source MLflow is a good quick example. It can be found here: https://github.com/mlflow/mlflow/tree/master/examples/xgboost
Download the files from this directory and edit the conda.yaml by adding infinstor_mlflow_plugin and boto3 to the pip dependencies. The edited file is shown here:
name: xgboost-example channels: - defaults - anaconda - conda-forge dependencies: - python=3.6 - xgboost - pip - pip: - mlflow>=1.6.0 - matplotlib - infinstor_mlflow_plugin - boto3
Now you can run the example as follows:
$ mlflow run .
The MLflow UI is available at https://mlflowui.infinstor.com/
Note that in the case of Enterprise License versions of InfinStor, the InfinStor mlflow UI endpoint will be different. For example, an Enterprise called xyz.com may have installed InfinStor at mlflowui.xyz.com. In that case the UI will be available at https://mlflowui.xyz.com/. Please contact your admin for this information