tbp.monty.frameworks#

tbp.monty.frameworks.run#

main(all_configs, experiments=None)[source]#

Use this as “main” function when running monty experiments.

A typical project run.py should look like this:

# Load all experiment configurations from local project
from experiments import CONFIGS
from tbp.monty.frameworks.run import main

if __name__ == "__main__":
    main(all_configs=CONFIGS)
Parameters:

  • all_configs – Dict containing all available experiment configurations. Usually each project would have its own list of experiment configurations

  • experiments – Optional list of experiments to run, used to bypass the command line args

merge_args(config, cmd_args=None)[source]#

Override experiment “config” parameters with command line args.

Returns:

Updated config with command line args.

print_config(config)[source]#

Print config with nice formatting if config_args.print_config is True.

run(config)[source]#

tbp.monty.frameworks.run_env#

setup_env(monty_logs_dir_default: str = '~/tbp/results/monty/', monty_models_dir_default: str = '~/tbp/results/monty/', monty_data_dir_default: str = '~/tbp/data')[source]#

Setup environment variables for Monty.

Parameters:

  • monty_logs_dir_default (str) – Default directory for Monty logs.

  • monty_models_dir_default (str) – Default directory for Monty pretrained models.

  • monty_data_dir_default (str) – Default directory for Monty experiments data.

tbp.monty.frameworks.run_parallel#