#!/usr/bin/env python # -*- coding: utf-8 -*- import io import sys import codecs import argparse from .learn_bpe import learn_bpe from .apply_bpe import BPE, read_vocabulary from .get_vocab import get_vocab from .learn_joint_bpe_and_vocab import learn_joint_bpe_and_vocab from .learn_bpe import create_parser as create_learn_bpe_parser from .apply_bpe import create_parser as create_apply_bpe_parser from .get_vocab import create_parser as create_get_vocab_parser from .learn_joint_bpe_and_vocab import create_parser as create_learn_joint_bpe_and_vocab_parser # hack for python2/3 compatibility argparse.open = io.open def main(): parser = argparse.ArgumentParser( formatter_class=argparse.RawTextHelpFormatter, description="subword-nmt: unsupervised word segmentation for neural machine translation and text generation ") subparsers = parser.add_subparsers(dest='command', help="""command to run. Run one of the commands with '-h' for more info. learn-bpe: learn BPE merge operations on input text. apply-bpe: apply given BPE operations to input text. get-vocab: extract vocabulary and word frequencies from input text. learn-joint-bpe-and-vocab: executes recommended workflow for joint BPE.""") learn_bpe_parser = create_learn_bpe_parser(subparsers) apply_bpe_parser = create_apply_bpe_parser(subparsers) get_vocab_parser = create_get_vocab_parser(subparsers) learn_joint_bpe_and_vocab_parser = create_learn_joint_bpe_and_vocab_parser(subparsers) args = parser.parse_args() if args.command == 'learn-bpe': # read/write files as UTF-8 if args.input.name != '': args.input = codecs.open(args.input.name, encoding='utf-8') if args.output.name != '': args.output = codecs.open(args.output.name, 'w', encoding='utf-8') learn_bpe(args.input, args.output, args.symbols, args.min_frequency, args.verbose, is_dict=args.dict_input, total_symbols=args.total_symbols) elif args.command == 'apply-bpe': # read/write files as UTF-8 args.codes = codecs.open(args.codes.name, encoding='utf-8') if args.input.name != '': args.input = codecs.open(args.input.name, encoding='utf-8') if args.output.name != '': args.output = codecs.open(args.output.name, 'w', encoding='utf-8') if args.vocabulary: args.vocabulary = codecs.open(args.vocabulary.name, encoding='utf-8') if args.vocabulary: vocabulary = read_vocabulary(args.vocabulary, args.vocabulary_threshold) else: vocabulary = None if sys.version_info < (3, 0): args.separator = args.separator.decode('UTF-8') if args.glossaries: args.glossaries = [g.decode('UTF-8') for g in args.glossaries] bpe = BPE(args.codes, args.merges, args.separator, vocabulary, args.glossaries) for line in args.input: args.output.write(bpe.process_line(line, args.dropout)) elif args.command == 'get-vocab': if args.input.name != '': args.input = codecs.open(args.input.name, encoding='utf-8') if args.output.name != '': args.output = codecs.open(args.output.name, 'w', encoding='utf-8') get_vocab(args.input, args.output) elif args.command == 'learn-joint-bpe-and-vocab': learn_joint_bpe_and_vocab(args) if sys.version_info < (3, 0): args.separator = args.separator.decode('UTF-8') else: raise Exception('Invalid command provided') # python 2/3 compatibility if sys.version_info < (3, 0): sys.stderr = codecs.getwriter('UTF-8')(sys.stderr) sys.stdout = codecs.getwriter('UTF-8')(sys.stdout) sys.stdin = codecs.getreader('UTF-8')(sys.stdin) else: sys.stderr = codecs.getwriter('UTF-8')(sys.stderr.buffer) sys.stdout = codecs.getwriter('UTF-8')(sys.stdout.buffer) sys.stdin = codecs.getreader('UTF-8')(sys.stdin.buffer)