|
|
|
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() |
|
|
