)ti ddlZddlZddlmZddlmZddlmZmZm Z m Z ddl m Z m Z mZddlmZdZd Zdd Zd Zd Zed k(reyy)N)ComputeEnvironment)get_cluster_input) cache_dirdefault_config_filedefault_yaml_config_fileload_config_from_file) _ask_field _ask_options_convert_compute_environment)get_sagemaker_inputzLaunches 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 machinec~tdddgt}|tjk(r t }|St }|S)Nz-In which compute environment are you running?z This machinezAWS (Amazon SageMaker))r r rAMAZON_SAGEMAKERr r)compute_environmentconfigs p/Volumes/fast/ai/experiments/MLX_z-image/.venv/lib/python3.12/site-packages/accelerate/commands/config/config.pyget_user_inputrsK&7 12$ 0AAA$& M#$ Mc||jdt}ntjdt}|j ddd||j t |S)Nr) descriptionzAccelerate config commandz --config_fileaTThe 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'.)defaulthelp)func) add_parserrargparseArgumentParser add_argument set_defaultsconfig_command) subparsersparsers rconfig_command_parserr",sm&&x[&I(()DR]^  "  0 MrcRt}|j |j}nBtjj t stj t t}|jdr|j|n|j|td|y)Nz.jsonz"accelerate configuration saved at ) r config_fileospathisdirrmakedirsrendswith to_json_file to_yaml_fileprint)argsrr$s rrrBs|  F #&& ww}}Y' KK ". G$K(K( .{m <=rcNt}|j}t|yN)r" parse_argsr)r!r-s rmainr1Rs " $F    D4r__main__r/)rr%accelerate.utilsrclusterr config_argsrrrr config_utilsr r r sagemakerr rrr"rr1__name__rrr:sR" /&hhPP*p  , >   zFr