Source code for vak.cli.train

import logging
import shutil
from pathlib import Path

from .. import config
from .. import train as train_module
from ..common.logging import config_logging_for_cli, log_version
from ..common.paths import generate_results_dir_name_as_path

logger = logging.getLogger(__name__)




def train(toml_path):
    """train models using training set specified in config.toml file.
    Function called by command-line interface.

    Trains models, saves results in new directory within root_results_dir specified
    in config.toml file, and adds path to that new directory to config.toml file.

    Parameters
    ----------
    toml_path : str, Path
        path to a configuration file in TOML format.
    """
    toml_path = Path(toml_path)
    cfg = config.Config.from_toml_path(toml_path)

    if cfg.train is None:
        raise ValueError(
            f"train called with a config.toml file that does not have a TRAIN section: {toml_path}"
        )

    # ---- set up directory to save output -----------------------------------------------------------------------------
    results_path = generate_results_dir_name_as_path(
        cfg.train.root_results_dir
    )
    results_path.mkdir(parents=True)
    # copy config file into results dir now that we've made the dir
    shutil.copy(toml_path, results_path)

    # ---- set up logging ----------------------------------------------------------------------------------------------
    config_logging_for_cli(
        log_dst=results_path, log_stem="train", level="INFO", force=True
    )
    log_version(logger)
    logger.info("Logging results to {}".format(results_path))

    if cfg.train.dataset.path is None:
        raise ValueError(
            "No value is specified for 'dataset_path' in this .toml config file."
            f"To generate a .csv file that represents the dataset, "
            f"please run the following command:\n'vak prep {toml_path}'"
        )

    train_module.train(
        model_config=cfg.train.model.asdict(),
        dataset_config=cfg.train.dataset.asdict(),
        trainer_config=cfg.train.trainer.asdict(),
        batch_size=cfg.train.batch_size,
        num_epochs=cfg.train.num_epochs,
        num_workers=cfg.train.num_workers,
        checkpoint_path=cfg.train.checkpoint_path,
        frames_standardizer_path=cfg.train.frames_standardizer_path,
        results_path=results_path,
        standardize_frames=cfg.train.standardize_frames,
        shuffle=cfg.train.shuffle,
        val_step=cfg.train.val_step,
        ckpt_step=cfg.train.ckpt_step,
        patience=cfg.train.patience,
    )