How to use the seml.config.read_config function in seml

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github TUM-DAML / seml / seml / main.py View on Github external
logging_level = logging.INFO
    hdlr = logging.StreamHandler(sys.stderr)
    hdlr.setFormatter(LoggingFormatter())
    logging.root.addHandler(hdlr)
    logging.root.setLevel(logging_level)

    if args.func == mongodb_credentials_prompt:  # launch SEML configure.
        del args.db_collection_name
    else:  # otherwise remove the flag as it is not used elsewhere.
        if not args.db_collection_name:
            parser.error("the following arguments are required: db_collection_name")
        else:
            if os.path.isfile(args.db_collection_name):
                logging.warning("Loading the collection name from a config file. This has been deprecated. "
                                "Please instead provide a database collection name in the command line.")
                seml_config, _, _ = read_config(args.db_collection_name)
                if args.func == queue_experiments:
                    args.config_file = args.db_collection_name
                args.db_collection_name = seml_config['db_collection']
            elif args.func == queue_experiments and not args.config_file:
                parser_queue.error("the following arguments are required: config_file")

    f = args.func
    del args.func
    del args.verbose
    if 'filter_states' in args:
        args.filter_states = [state.upper() for state in args.filter_states]
    f(**args.__dict__)
github TUM-DAML / seml / seml / queuing.py View on Github external
def queue_experiments(db_collection_name, config_file, force_duplicates, no_hash=False, no_config_check=False):
    seml_config, slurm_config, experiment_config = read_config(config_file)

    # Use current Anaconda environment if not specified
    if 'conda_environment' not in seml_config:
        if 'CONDA_DEFAULT_ENV' in os.environ:
            seml_config['conda_environment'] = os.environ['CONDA_DEFAULT_ENV']
        else:
            seml_config['conda_environment'] = None

    # Set Slurm config with default parameters as fall-back option
    if slurm_config is None:
        slurm_config = {'sbatch_options': {}}
    for k, v in SETTINGS.SLURM_DEFAULT['sbatch_options'].items():
        if k not in slurm_config['sbatch_options']:
            slurm_config['sbatch_options'][k] = v
    del SETTINGS.SLURM_DEFAULT['sbatch_options']
    for k, v in SETTINGS.SLURM_DEFAULT.items():