mlflow (version 0.7.0)

mlflow_run: Run in MLflow

Description

Wrapper for `mlflow run`.

Usage

mlflow_run(entry_point = NULL, uri = ".", version = NULL,
  param_list = NULL, experiment_id = NULL, mode = NULL,
  cluster_spec = NULL, git_username = NULL, git_password = NULL,
  no_conda = FALSE, storage_dir = NULL)

Arguments

entry_point

Entry point within project, defaults to `main` if not specified.

uri

A directory containing modeling scripts, defaults to the current directory.

version

Version of the project to run, as a Git commit reference for Git projects.

param_list

A list of parameters.

experiment_id

ID of the experiment under which to launch the run.

mode

Execution mode to use for run.

cluster_spec

Path to JSON file describing the cluster to use when launching a run on Databricks.

git_username

Username for HTTP(S) Git authentication.

git_password

Password for HTTP(S) Git authentication.

no_conda

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.

storage_dir

Only valid when `mode` is local. MLflow downloads artifacts from distributed URIs passed to parameters of type 'path' to subdirectories of storage_dir.

Value

The run associated with this run.