FunASR/funasr/bin/lm_inference_launch.py
2023-02-10 10:54:27 +08:00

131 lines
3.9 KiB
Python

#!/usr/bin/env python3
# Copyright ESPnet (https://github.com/espnet/espnet). All Rights Reserved.
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import logging
import os
import sys
from typing import Union, Dict, Any
from funasr.utils import config_argparse
from funasr.utils.cli_utils import get_commandline_args
from funasr.utils.types import str2bool
from funasr.utils.types import str2triple_str
from funasr.utils.types import str_or_none
from funasr.utils.types import float_or_none
def get_parser():
parser = config_argparse.ArgumentParser(
description="Calc perplexity",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument(
"--log_level",
type=lambda x: x.upper(),
default="INFO",
choices=("CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG", "NOTSET"),
help="The verbose level of logging",
)
parser.add_argument("--output_dir", type=str, required=True)
parser.add_argument("--gpuid_list", type=str, required=True)
parser.add_argument(
"--ngpu",
type=int,
default=0,
help="The number of gpus. 0 indicates CPU mode",
)
parser.add_argument("--seed", type=int, default=0, help="Random seed")
parser.add_argument("--njob", type=int, default=1, help="Random seed")
parser.add_argument(
"--dtype",
default="float32",
choices=["float16", "float32", "float64"],
help="Data type",
)
parser.add_argument(
"--num_workers",
type=int,
default=1,
help="The number of workers used for DataLoader",
)
parser.add_argument(
"--batch_size",
type=int,
default=1,
help="The batch size for inference",
)
parser.add_argument(
"--log_base",
type=float_or_none,
default=10,
help="The base of logarithm for Perplexity. "
"If None, napier's constant is used.",
required=False
)
group = parser.add_argument_group("Input data related")
group.add_argument(
"--data_path_and_name_and_type",
type=str2triple_str,
action="append",
required=False
)
group.add_argument(
"--raw_inputs",
type=str,
required=False
)
group.add_argument("--key_file", type=str_or_none)
group.add_argument("--allow_variable_data_keys", type=str2bool, default=False)
group.add_argument("--split_with_space", type=str2bool, default=False)
group.add_argument("--seg_dict_file", type=str_or_none)
group = parser.add_argument_group("The model configuration related")
group.add_argument("--train_config", type=str)
group.add_argument("--model_file", type=str)
group.add_argument("--mode", type=str, default="lm")
return parser
def inference_launch(mode, **kwargs):
if mode == "transformer":
from funasr.bin.lm_inference import inference_modelscope
return inference_modelscope(**kwargs)
else:
logging.info("Unknown decoding mode: {}".format(mode))
return None
def main(cmd=None):
print(get_commandline_args(), file=sys.stderr)
parser = get_parser()
args = parser.parse_args(cmd)
kwargs = vars(args)
kwargs.pop("config", None)
# set logging messages
logging.basicConfig(
level=args.log_level,
format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s",
)
logging.info("Decoding args: {}".format(kwargs))
# gpu setting
if args.ngpu > 0:
jobid = int(args.output_dir.split(".")[-1])
gpuid = args.gpuid_list.split(",")[(jobid - 1) // args.njob]
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = gpuid
kwargs.pop("gpuid_list", None)
kwargs.pop("njob", None)
results = inference_launch(**kwargs)
if __name__ == "__main__":
main()