Wrapper for `mlflow run`.
mlflow_run(entry_point = NULL, uri = ".", version = NULL,
param_list = NULL, experiment_id = NULL, experiment_name = NULL,
mode = NULL, cluster_spec = NULL, git_username = NULL,
git_password = NULL, no_conda = FALSE, storage_dir = NULL)Entry point within project, defaults to `main` if not specified.
A directory containing modeling scripts, defaults to the current directory.
Version of the project to run, as a Git commit reference for Git projects.
A list of parameters.
ID of the experiment under which to launch the run.
Name of the experiment under which to launch the run.
Execution mode to use for run.
Path to JSON file describing the cluster to use when launching a run on Databricks.
Username for HTTP(S) Git authentication.
Password for HTTP(S) Git authentication.
If specified, assume that MLflow is running within a Conda environment with the necessary dependencies for the current project instead of attempting to create a new Conda environment. Only valid if running locally.
Valid only when `mode` is local. MLflow downloads artifacts from distributed URIs passed to parameters of type `path` to subdirectories of `storage_dir`.
The run associated with this run.