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":
if args.num_spkrs == 1:
from espnet.asr.pytorch_backend.asr import enhance
enhance(args)
else:
from espnet.asr.pytorch_backend.asr_mix import enhance
enhance(args)
else:
raise ValueError("Only pytorch is supported.")
def main(args):
parser = configargparse.ArgumentParser(
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')
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.")