Mock ML Flow Run Data

Generate somewhat realistic ML Flow data without actually training a model.

To generate mock ML Flow data, execute python mock-train.py with the following optional parameters:

• experiment_name: The default is test. Name of experiment. If creating multiple experiments, unique names will be generated from string.
• num_experiments: The default is 1. Number of experiments to generate.
• num_runs: The default is 1. Number of runs to generate per experiment and/or parent".
• nested_runs: The default is False. Whether to generated nested runs or not.

Example Usage

To generate a single run:

python mock-train.py

To customize the experiment name:

python mock-train.py --experiment_name customExperiment

To generate multiple runs within an experiment:

python mock-train.py --num_runs 4

To generate nested runs within an experiment:

python mock-train.py --num_runs 4 --nested_runs True

To generate multiple experiments with multiple runs:

python mock-train.py --num_experiments 2 --num_runs 4

To generate multiple experiments with nested runs:

python mock-train.py --num_experiments 2 --num_runs 4 nested_runs True