Source code for espnet.bin.mt_trans

#!/usr/bin/env python3
# encoding: utf-8

# Copyright 2019 Kyoto University (Hirofumi Inaguma)
#  Apache 2.0  (

"""Neural machine translation model decoding script."""

import logging
import os
import random
import sys

import configargparse
import numpy as np

# NOTE: you need this func to generate our sphinx doc
[docs]def get_parser(): """Get default arguments.""" parser = configargparse.ArgumentParser( description="Translate text from speech " "using a speech translation model on one CPU or GPU", 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", type=int, default=0, help="Number of GPUs") parser.add_argument( "--dtype", choices=("float16", "float32", "float64"), default="float32", help="Float precision (only available in --api v2)", ) parser.add_argument( "--backend", type=str, default="chainer", choices=["chainer", "pytorch"], help="Backend library", ) parser.add_argument("--debugmode", type=int, default=1, help="Debugmode") parser.add_argument("--seed", type=int, default=1, help="Random seed") parser.add_argument("--verbose", "-V", type=int, default=1, help="Verbose option") parser.add_argument( "--batchsize", type=int, default=1, 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", ) parser.add_argument( "--api", default="v1", choices=["v1", "v2"], help="Beam search APIs " "v1: Default API. It only supports " "the ASRInterface.recognize method and DefaultRNNLM. " "v2: Experimental API. " "It supports any models that implements ScorerInterface.", ) # task related parser.add_argument( "--trans-json", type=str, help="Filename of translation data (json)" ) parser.add_argument( "--result-label", type=str, required=True, help="Filename of result label 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" ) # search related parser.add_argument("--nbest", type=int, default=1, help="Output N-best hypotheses") parser.add_argument("--beam-size", type=int, default=1, help="Beam size") parser.add_argument("--penalty", type=float, default=0.1, help="Incertion penalty") parser.add_argument( "--maxlenratio", type=float, default=3.0, help="""Input length ratio to obtain max output length. If maxlenratio=0.0 (default), it uses a end-detect function to automatically find maximum hypothesis lengths""", ) parser.add_argument( "--minlenratio", type=float, default=0.0, help="Input length ratio to obtain min output length", ) # multilingual related parser.add_argument( "--tgt-lang", default=False, type=str, help="target language ID (e.g., <en>, <de>, and <fr> etc.)", ) return parser
[docs]def main(args): """Run the main decoding function.""" 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(mn5k): support of multiple GPUs if args.ngpu > 1: logging.error("The program only supports ngpu=1.") sys.exit(1) # display PYTHONPATH"python path = " + os.environ.get("PYTHONPATH", "(None)")) # seed setting random.seed(args.seed) np.random.seed(args.seed)"set random seed = %d" % args.seed) # trans"backend = " + args.backend) if args.backend == "pytorch": # Experimental API that supports custom LMs from import trans if args.dtype != "float32": raise NotImplementedError( f"`--dtype {args.dtype}` is only available with `--api v2`" ) trans(args) else: raise ValueError("Only pytorch are supported.")
if __name__ == "__main__": main(sys.argv[1:])