| |
| description = "Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine" |
| def get_user_input(): |
| compute_environment = _ask_options( |
| "In which compute environment are you running?", |
| ["This machine", "AWS (Amazon SageMaker)"], |
| _convert_compute_environment, |
| ) |
| if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER: |
| config = get_sagemaker_input() |
| else: |
| config = get_cluster_input() |
| return config |
| def config_command_parser(subparsers=None): |
| if subparsers is not None: |
| parser = subparsers.add_parser("config", description=description) |
| else: |
| parser = argparse.ArgumentParser("Accelerate config command", description=description) |
| parser.add_argument( |
| "--config_file", |
| default=None, |
| help=( |
| "The path to use to store the config file. Will default to a file named default_config.yaml in the cache " |
| "location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have " |
| "such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed " |
| "with 'huggingface'." |
| ), |
| ) |
| if subparsers is not None: |
| parser.set_defaults(func=config_command) |
| return parser |
| def config_command(args): |
| config = get_user_input() |
| if args.config_file is not None: |
| config_file = args.config_file |
| else: |
| if not os.path.isdir(cache_dir): |
| os.makedirs(cache_dir) |
| config_file = default_yaml_config_file |
| if config_file.endswith(".json"): |
| config.to_json_file(config_file) |
| else: |
| config.to_yaml_file(config_file) |
| print(f"accelerate configuration saved at {config_file}") |
| def main(): |
| parser = config_command_parser() |
| args = parser.parse_args() |
| config_command(args) |
| if __name__ == "__main__": |
| main() |
|
|
