espnet/bin/asr_enhance.py

#!/usr/bin/env python3
import configargparse
from distutils.util import strtobool
import logging
import os
import random
import sys

import numpy as np

from espnet.asr.pytorch_backend.asr import enhance


# NOTE: you need this func to generate our sphinx doc
def get_parser():
    parser = configargparse.ArgumentParser(
        description="Enhance noisy speech for speech recognition",
        config_file_parser_class=configargparse.YAMLConfigFileParser,
        formatter_class=configargparse.ArgumentDefaultsHelpFormatter,
    )
    # general configuration
    parser.add("--config", is_config_file=True, help="config file path")
    parser.add(
        "--config2",
        is_config_file=True,
        help="second config file path that overwrites the settings in `--config`.",
    )
    parser.add(
        "--config3",
        is_config_file=True,
        help="third config file path that overwrites the settings "
        "in `--config` and `--config2`.",
    )

    parser.add_argument("--ngpu", default=0, type=int, help="Number of GPUs")
    parser.add_argument(
        "--backend",
        default="chainer",
        type=str,
        choices=["chainer", "pytorch"],
        help="Backend library",
    )
    parser.add_argument("--debugmode", default=1, type=int, help="Debugmode")
    parser.add_argument("--seed", default=1, type=int, help="Random seed")
    parser.add_argument("--verbose", "-V", default=1, type=int, help="Verbose option")
    parser.add_argument(
        "--batchsize",
        default=1,
        type=int,
        help="Batch size for beam search (0: means no batch processing)",
    )
    parser.add_argument(
        "--preprocess-conf",
        type=str,
        default=None,
        help="The configuration file for the pre-processing",
    )
    # task related
    parser.add_argument(
        "--recog-json", type=str, help="Filename of recognition data (json)"
    )
    # model (parameter) related
    parser.add_argument(
        "--model", type=str, required=True, help="Model file parameters to read"
    )
    parser.add_argument(
        "--model-conf", type=str, default=None, help="Model config file"
    )

    # Outputs configuration
    parser.add_argument(
        "--enh-wspecifier",
        type=str,
        default=None,
        help="Specify the output way for enhanced speech."
        "e.g. ark,scp:outdir,wav.scp",
    )
    parser.add_argument(
        "--enh-filetype",
        type=str,
        default="sound",
        choices=["mat", "hdf5", "sound.hdf5", "sound"],
        help="Specify the file format for enhanced speech. "
        '"mat" is the matrix format in kaldi',
    )
    parser.add_argument("--fs", type=int, default=16000, help="The sample frequency")
    parser.add_argument(
        "--keep-length",
        type=strtobool,
        default=True,
        help="Adjust the output length to match " "with the input for enhanced speech",
    )
    parser.add_argument(
        "--image-dir", type=str, default=None, help="The directory saving the images."
    )
    parser.add_argument(
        "--num-images",
        type=int,
        default=20,
        help="The number of images files to be saved. "
        "If negative, all samples are to be saved.",
    )

    # IStft
    parser.add_argument(
        "--apply-istft",
        type=strtobool,
        default=True,
        help="Apply istft to the output from the network",
    )
    parser.add_argument(
        "--istft-win-length",
        type=int,
        default=512,
        help="The window length for istft. "
        "This option is ignored "
        "if stft is found in the preprocess-conf",
    )
    parser.add_argument(
        "--istft-n-shift",
        type=str,
        default=256,
        help="The window type for istft. "
        "This option is ignored "
        "if stft is found in the preprocess-conf",
    )
    parser.add_argument(
        "--istft-window",
        type=str,
        default="hann",
        help="The window type for istft. "
        "This option is ignored "
        "if stft is found in the preprocess-conf",
    )
    return parser


def main(args):
    parser = get_parser()
    args = parser.parse_args(args)

    # logging info
    if args.verbose == 1:
        logging.basicConfig(
            level=logging.INFO,
            format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s",
        )
    elif args.verbose == 2:
        logging.basicConfig(
            level=logging.DEBUG,
            format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s",
        )
    else:
        logging.basicConfig(
            level=logging.WARN,
            format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s",
        )
        logging.warning("Skip DEBUG/INFO messages")

    # check CUDA_VISIBLE_DEVICES
    if args.ngpu > 0:
        cvd = os.environ.get("CUDA_VISIBLE_DEVICES")
        if cvd is None:
            logging.warning("CUDA_VISIBLE_DEVICES is not set.")
        elif args.ngpu != len(cvd.split(",")):
            logging.error("#gpus is not matched with CUDA_VISIBLE_DEVICES.")
            sys.exit(1)

        # TODO(kamo): support of multiple GPUs
        if args.ngpu > 1:
            logging.error("The program only supports ngpu=1.")
            sys.exit(1)

    # display PYTHONPATH
    logging.info("python path = " + os.environ.get("PYTHONPATH", "(None)"))

    # seed setting
    random.seed(args.seed)
    np.random.seed(args.seed)
    logging.info("set random seed = %d" % args.seed)

    # recog
    logging.info("backend = " + args.backend)
    if args.backend == "pytorch":
        enhance(args)
    else:
        raise ValueError("Only pytorch is supported.")


if __name__ == "__main__":
    main(sys.argv[1:])