def main():
parser = argparse.ArgumentParser(
description='eflomal: efficient low-memory aligner')
parser.add_argument('-v',
'--verbose',
dest='verbose',
action='store_true',
help='Enable verbose output')
parser.add_argument('--debug',
dest='debug',
action='store_true',
help='Enable gdb debugging of eflomal binary')
parser.add_argument('--overwrite',
dest='overwrite',
action='store_true',
help='Overwrite existing output files')
parser.add_argument('--null-prior',
dest='null_prior',
default=0.2,
metavar='X',
type=float,
help='Prior probability of NULL alignment')
parser.add_argument(
'-m',
'--model',
dest='model',
default=3,
metavar='N',
type=int,
help='Model (1 = IBM1, 2 = IBM1+HMM, 3 = IBM1+HMM+fertility)')
parser.add_argument('-M',
'--score-model',
dest='score_model',
default=0,
metavar='N',
type=int,
help='Model used for sentence scoring '
'(1 = IBM1, 2 = IBM1+HMM, 3 = IBM1+HMM+fertility)')
parser.add_argument('--source-prefix',
dest='source_prefix_len',
default=0,
metavar='N',
type=int,
help='Length of prefix for stemming (source)')
parser.add_argument('--source-suffix',
dest='source_suffix_len',
default=0,
metavar='N',
type=int,
help='Length of suffix for stemming (source)')
parser.add_argument('--target-prefix',
dest='target_prefix_len',
default=0,
metavar='N',
type=int,
help='Length of prefix for stemming (target)')
parser.add_argument('--target-suffix',
dest='target_suffix_len',
default=0,
metavar='N',
type=int,
help='Length of suffix for stemming (target)')
parser.add_argument('-l',
'--length',
dest='length',
default=1.0,
metavar='X',
type=float,
help='Relative number of sampling iterations')
parser.add_argument('-1',
'--ibm1-iters',
dest='iters1',
default=None,
metavar='X',
type=int,
help='Number of IBM1 iterations (overrides --length)')
parser.add_argument('-2',
'--hmm-iters',
dest='iters2',
default=None,
metavar='X',
type=int,
help='Number of HMM iterations (overrides --length)')
parser.add_argument(
'-3',
'--fert-iters',
dest='iters3',
default=None,
metavar='X',
type=int,
help='Number of HMM+fertility iterations (overrides --length)')
parser.add_argument('--n-samplers',
dest='n_samplers',
default=3,
metavar='X',
type=int,
help='Number of independent samplers to run')
parser.add_argument('-s',
'--source',
dest='source_filename',
type=str,
metavar='filename',
help='Source text filename')
parser.add_argument('-t',
'--target',
dest='target_filename',
type=str,
metavar='filename',
help='Target text filename')
parser.add_argument('-i',
'--input',
dest='joint_filename',
type=str,
metavar='filename',
help='fast_align style ||| separated file')
parser.add_argument(
'-f',
'--forward-links',
dest='links_filename_fwd',
type=str,
metavar='filename',
help='Filename to write forward direction alignments to')
parser.add_argument(
'-r',
'--reverse-links',
dest='links_filename_rev',
type=str,
metavar='filename',
help='Filename to write reverse direction alignments to')
parser.add_argument(
'-F',
'--forward-scores',
dest='scores_filename_fwd',
type=str,
metavar='filename',
help='Filename to write alignment scores to (generation '
'probability of target sentences)')
parser.add_argument(
'-R',
'--reverse-scores',
dest='scores_filename_rev',
type=str,
metavar='filename',
help='Filename to write alignment scores to (generation '
'probability of source sentences)')
parser.add_argument('-p',
'--priors',
dest='priors_filename',
type=str,
metavar='filename',
help='File to read priors from')
args = parser.parse_args()
if not (args.joint_filename or
(args.source_filename and args.target_filename)):
print('ERROR: need to specify either -s and -t, or -i',
file=sys.stderr,
flush=True)
sys.exit(1)
for filename in ((args.joint_filename, ) if args.joint_filename else
(args.source_filename, args.target_filename)):
if not os.path.exists(filename):
print('ERROR: input file %s does not exist!' % filename,
file=sys.stderr,
flush=True)
sys.exit(1)
for filename in (args.links_filename_fwd, args.links_filename_rev):
if (not args.overwrite) and (filename is not None) \
and os.path.exists(filename):
print('ERROR: output file %s exists, will not overwrite!' % \
filename,
file=sys.stderr, flush=True)
sys.exit(1)
if args.priors_filename:
if args.verbose:
print('Reading lexical priors from %s...' % args.priors_filename,
file=sys.stderr,
flush=True)
priors_list = [] # list of (srcword, trgword, alpha)
ferf_priors = [] # list of (wordform, alpha)
ferr_priors = [] # list of (wordform, alpha)
hmmf_priors = {} # dict of jump: alpha
hmmr_priors = {} # dict of jump: alpha
with open(args.priors_filename, 'r', encoding='utf-8') as f:
# 5 types of lines valid:
#
# LEX srcword trgword alpha | lexical prior
# HMMF jump alpha | target-side HMM prior
# HMMR jump alpha | source-side HMM prior
# FERF srcword fert alpha | source-side fertility p.
# FERR trgword fert alpha | target-side fertility p.
for i, line in enumerate(f):
fields = line.rstrip('\n').split('\t')
try:
alpha = float(fields[-1])
except ValueError:
print('ERROR: priors file %s line %d contains alpha '
'value of "%s" which is not numeric' %
(args.priors_filename, i + 1, fields[2]),
file=sys.stderr,
flush=True)
sys.exit(1)
if fields[0] == 'LEX' and len(fields) == 4:
priors_list.append((fields[1], fields[2], alpha))
elif fields[0] == 'HMMF' and len(fields) == 3:
hmmf_priors[int(fields[1])] = alpha
elif fields[0] == 'HMMR' and len(fields) == 3:
hmmr_priors[int(fields[1])] = alpha
elif fields[0] == 'FERF' and len(fields) == 4:
ferf_priors.append((fields[1], int(fields[2]), alpha))
elif fields[0] == 'FERR' and len(fields) == 4:
ferr_priors.append((fields[1], int(fields[2]), alpha))
else:
print('ERROR: priors file %s line %d is invalid ' %
(args.priors_filename, i + 1),
file=sys.stderr,
flush=True)
sys.exit(1)
if args.joint_filename:
if args.verbose:
print('Reading source/target sentences from %s...' %
args.joint_filename,
file=sys.stderr,
flush=True)
with open(args.joint_filename, 'r', encoding='utf-8') as f:
src_sents_text = []
trg_sents_text = []
for i, line in enumerate(f):
fields = line.strip().split(' ||| ')
if len(fields) != 2:
print('ERROR: line %d of %s does not contain a single |||'
' separator, or sentence(s) are empty!' %
(i + 1, args.joint_filename),
file=sys.stderr,
flush=True)
sys.exit(1)
src_sents_text.append(fields[0])
trg_sents_text.append(fields[1])
src_text = '\n'.join(src_sents_text) + '\n'
trg_text = '\n'.join(trg_sents_text) + '\n'
src_sents_text = None
trg_sents_text = None
with io.StringIO(src_text) as f:
src_sents, src_index = read_text(f, True, args.source_prefix_len,
args.source_suffix_len)
n_src_sents = len(src_sents)
src_voc_size = len(src_index)
srcf = NamedTemporaryFile('wb', delete=False)
write_text(srcf, tuple(src_sents), src_voc_size)
src_sents = None
src_text = None
scrf.close()
with io.StringIO(trg_text) as f:
trg_sents, trg_index = read_text(f, True, args.target_prefix_len,
args.target_suffix_len)
trg_voc_size = len(trg_index)
n_trg_sents = len(trg_sents)
trgf = NamedTemporaryFile('wb', delete=False)
write_text(trgf, tuple(trg_sents), trg_voc_size)
trg_sents = None
trg_text = None
trgf.close()
else:
if args.verbose:
print('Reading source text from %s...' % args.source_filename,
file=sys.stderr,
flush=True)
with open(args.source_filename, 'r', encoding='utf-8') as f:
src_sents, src_index = read_text(f, True, args.source_prefix_len,
args.source_suffix_len)
n_src_sents = len(src_sents)
src_voc_size = len(src_index)
srcf = NamedTemporaryFile('wb', delete=False)
write_text(srcf, tuple(src_sents), src_voc_size)
src_sents = None
srcf.close()
if args.verbose:
print('Reading target text from %s...' % args.target_filename,
file=sys.stderr,
flush=True)
with open(args.target_filename, 'r', encoding='utf-8') as f:
trg_sents, trg_index = read_text(f, True, args.target_prefix_len,
args.target_suffix_len)
trg_voc_size = len(trg_index)
n_trg_sents = len(trg_sents)
trgf = NamedTemporaryFile('wb', delete=False)
write_text(trgf, tuple(trg_sents), trg_voc_size)
trg_sents = None
trgf.close()
if n_src_sents != n_trg_sents:
print(
'ERROR: number of sentences differ in input files (%d vs %d)' %
(n_src_sents, n_trg_sents),
file=sys.stderr,
flush=True)
sys.exit(1)
def get_src_index(src_word):
src_word = src_word.lower()
if args.source_prefix_len != 0:
src_word = src_word[:args.source_prefix_len]
if args.source_suffix_len != 0:
src_word = src_word[-args.source_suffix_len:]
e = src_index.get(src_word)
if e is not None:
e = e + 1
return e
def get_trg_index(trg_word):
trg_word = trg_word.lower()
if args.target_prefix_len != 0:
trg_word = trg_word[:args.target_prefix_len]
if args.target_suffix_len != 0:
trg_word = trg_word[-args.target_suffix_len:]
f = trg_index.get(trg_word)
if f is not None:
f = f + 1
return f
if args.priors_filename:
priors_indexed = {}
for src_word, trg_word, alpha in priors_list:
if src_word == '<NULL>':
e = 0
else:
e = get_src_index(src_word)
if trg_word == '<NULL>':
f = 0
else:
f = get_trg_index(trg_word)
if (e is not None) and (f is not None):
priors_indexed[(e,f)] = priors_indexed.get((e,f), 0.0) \
+ alpha
ferf_indexed = {}
for src_word, fert, alpha in ferf_priors:
e = get_src_index(src_word)
if e is not None:
ferf_indexed[(e, fert)] = \
ferf_indexed.get((e, fert), 0.0) + alpha
ferr_indexed = {}
for trg_word, fert, alpha in ferr_priors:
f = get_trg_index(trg_word)
if f is not None:
ferr_indexed[(f, fert)] = \
ferr_indexed.get((f, fert), 0.0) + alpha
if args.verbose:
print('%d (of %d) pairs of lexical priors used' %
(len(priors_indexed), len(priors_list)),
file=sys.stderr)
priorsf = NamedTemporaryFile('w', encoding='utf-8', delete=False)
print('%d %d %d %d %d %d %d' %
(len(src_index) + 1, len(trg_index) + 1, len(priors_indexed),
len(hmmf_priors), len(hmmr_priors), len(ferf_indexed),
len(ferr_indexed)),
file=priorsf)
for (e, f), alpha in sorted(priors_indexed.items()):
print('%d %d %g' % (e, f, alpha), file=priorsf)
for jump, alpha in sorted(hmmf_priors.items()):
print('%d %g' % (jump, alpha), file=priorsf)
for jump, alpha in sorted(hmmr_priors.items()):
print('%d %g' % (jump, alpha), file=priorsf)
for (e, fert), alpha in sorted(ferf_indexed.items()):
print('%d %d %g' % (e, fert, alpha), file=priorsf)
for (f, fert), alpha in sorted(ferr_indexed.items()):
print('%d %d %g' % (f, fert, alpha), file=priorsf)
priorsf.flush()
priorsf.close()
trg_index = None
src_index = None
iters = (args.iters1, args.iters2, args.iters3)
if any(x is None for x in iters[:args.model]):
iters = None
if args.verbose:
print('Aligning %d sentences...' % n_src_sents,
file=sys.stderr,
flush=True)
align(srcf.name,
trgf.name,
links_filename_fwd=args.links_filename_fwd,
links_filename_rev=args.links_filename_rev,
statistics_filename=None,
scores_filename_fwd=args.scores_filename_fwd,
scores_filename_rev=args.scores_filename_rev,
priors_filename=(None
if args.priors_filename is None else priorsf.name),
model=args.model,
score_model=args.score_model,
n_iterations=iters,
n_samplers=args.n_samplers,
quiet=not args.verbose,
rel_iterations=args.length,
null_prior=args.null_prior,
use_gdb=args.debug)
srcf.close()
trgf.close()
if args.priors_filename:
priorsf.close()
def do_align(f_name, rev_f_name, seed=None):
print('Reading source/target sentences from %s...' %
f_name,
file=sys.stderr, flush=True)
with open(f_name, 'r', encoding='utf-8') as f:
src_sents_text = []
trg_sents_text = []
for i, line in enumerate(f):
fields = line.strip().split(' ||| ')
if len(fields) != 2:
print('ERROR: line %d of %s does not contain a single |||'
' separator, or sentence(s) are empty!' % (
i+1, args.joint_filename),
file=sys.stderr, flush=True)
sys.exit(1)
src_sents_text.append(fields[0])
trg_sents_text.append(fields[1])
src_text = '\n'.join(src_sents_text) + '\n'
trg_text = '\n'.join(trg_sents_text) + '\n'
src_sents_text = None
trg_sents_text = None
source_prefix_len = 0
source_suffix_len = 0
target_prefix_len = 0
target_suffix_len = 0
with io.StringIO(src_text) as f:
src_sents, src_index = read_text(
f, True, source_prefix_len, source_suffix_len)
n_src_sents = len(src_sents)
src_voc_size = len(src_index)
srcf = NamedTemporaryFile('wb')
write_text(srcf, tuple(src_sents), src_voc_size)
src_sents = None
src_text = None
with io.StringIO(trg_text) as f:
trg_sents, trg_index = read_text(
f, True, target_prefix_len, target_suffix_len)
trg_voc_size = len(trg_index)
n_trg_sents = len(trg_sents)
trgf = NamedTemporaryFile('wb')
write_text(trgf, tuple(trg_sents), trg_voc_size)
trg_sents = None
trg_text = None
"""
print("source")
with open(f_name, 'r', encoding='utf-8') as f:
src_sents, src_index = read_text(
f, True, 0, 0)
n_src_sents = len(src_sents)
src_voc_size = len(src_index)
srcf = NamedTemporaryFile('wb')
write_text(srcf, tuple(src_sents), src_voc_size)
src_sents = None
print("target")
with open(rev_f_name, 'r', encoding='utf-8') as f:
trg_sents, trg_index = read_text(
f, True, 0, 0)
trg_voc_size = len(trg_index)
n_trg_sents = len(trg_sents)
trgf = NamedTemporaryFile('wb')
write_text(trgf, tuple(trg_sents), trg_voc_size)
trg_sents = None
"""
fwd_links_file = NamedTemporaryFile('r+')
rev_links_file = NamedTemporaryFile('r+')
stat_file = NamedTemporaryFile('r+')
print("start align")
align(srcf.name, trgf.name, statistics_filename = stat_file.name, quiet=False, links_filename_fwd=fwd_links_file.name, links_filename_rev=rev_links_file.name)
# Not using stat_file at the moment
result = fwd_links_file.readlines()
rev_result = rev_links_file.readlines()
fwd_links_file.close()
rev_links_file.close()
stat_file.close()
srcf.close()
trgf.close()
"""
if discretize:
ibm_print(aaa, reverse, output.fileno())
else: # Not used at the moment, but keeping this for the future
with open(output_prob, 'wb') as f:
pickle.dump(aaa, f, -1)
output.seek(0)
result = []
for line in output:
result.append(line.decode('ascii').strip())
"""
return result, rev_result
def main():
parser = argparse.ArgumentParser(
description='eflomal: efficient low-memory aligner')
parser.add_argument('-v',
'--verbose',
dest='verbose',
action='store_true',
help='Enable verbose output')
parser.add_argument('--debug',
dest='debug',
action='store_true',
help='Enable gdb debugging of eflomal binary')
parser.add_argument('--overwrite',
dest='overwrite',
action='store_true',
help='Overwrite existing output files')
parser.add_argument('--null-prior',
dest='null_prior',
default=0.2,
metavar='X',
type=float,
help='Prior probability of NULL alignment')
parser.add_argument(
'-m',
'--model',
dest='model',
default=3,
metavar='N',
type=int,
help='Model (1 = IBM1, 2 = IBM1+HMM, 3 = IBM1+HMM+fertility)')
parser.add_argument('--source-prefix',
dest='source_prefix_len',
default=0,
metavar='N',
type=int,
help='Length of prefix for stemming (source)')
parser.add_argument('--source-suffix',
dest='source_suffix_len',
default=0,
metavar='N',
type=int,
help='Length of suffix for stemming (source)')
parser.add_argument('--target-prefix',
dest='target_prefix_len',
default=0,
metavar='N',
type=int,
help='Length of prefix for stemming (target)')
parser.add_argument('--target-suffix',
dest='target_suffix_len',
default=0,
metavar='N',
type=int,
help='Length of suffix for stemming (target)')
parser.add_argument('-l',
'--length',
dest='length',
default=1.0,
metavar='X',
type=float,
help='Relative number of sampling iterations')
parser.add_argument('-1',
'--ibm1-iters',
dest='iters1',
default=None,
metavar='X',
type=int,
help='Number of IBM1 iterations (overrides --length)')
parser.add_argument('-2',
'--hmm-iters',
dest='iters2',
default=None,
metavar='X',
type=int,
help='Number of HMM iterations (overrides --length)')
parser.add_argument(
'-3',
'--fert-iters',
dest='iters3',
default=None,
metavar='X',
type=int,
help='Number of HMM+fertility iterations (overrides --length)')
parser.add_argument('--n-samplers',
dest='n_samplers',
default=3,
metavar='X',
type=int,
help='Number of independent samplers to run')
parser.add_argument('-s',
'--source',
dest='source_filename',
type=str,
metavar='filename',
help='Source text filename',
required=True)
parser.add_argument('-t',
'--target',
dest='target_filename',
type=str,
metavar='filename',
help='Target text filename',
required=True)
parser.add_argument(
'-f',
'--forward-links',
dest='links_filename_fwd',
type=str,
metavar='filename',
help='Filename to write forward direction alignments to')
parser.add_argument(
'-r',
'--reverse-links',
dest='links_filename_rev',
type=str,
metavar='filename',
help='Filename to write reverse direction alignments to')
args = parser.parse_args()
for filename in (args.source_filename, args.target_filename):
if not os.path.exists(filename):
print('ERROR: input file %s does not exist!' % filename,
file=sys.stderr,
flush=True)
sys.exit(1)
for filename in (args.links_filename_fwd, args.links_filename_rev):
if (not args.overwrite) and (filename is not None) \
and os.path.exists(filename):
print('ERROR: output file %s exists, will not overwrite!' % \
filename,
file=sys.stderr, flush=True)
sys.exit(1)
if args.verbose:
print('Reading source text from %s...' % args.source_filename,
file=sys.stderr,
flush=True)
with open(args.source_filename, 'r', encoding='utf-8') as f:
src_sents, src_index = read_text(f, True, args.source_prefix_len,
args.source_suffix_len)
n_src_sents = len(src_sents)
src_voc_size = len(src_index)
src_index = None
srcf = NamedTemporaryFile('wb')
write_text(srcf, tuple(src_sents), src_voc_size)
src_sents = None
if args.verbose:
print('Reading target text from %s...' % args.target_filename,
file=sys.stderr,
flush=True)
with open(args.target_filename, 'r', encoding='utf-8') as f:
trg_sents, trg_index = read_text(f, True, args.target_prefix_len,
args.target_suffix_len)
trg_voc_size = len(trg_index)
n_trg_sents = len(trg_sents)
trg_index = None
trgf = NamedTemporaryFile('wb')
write_text(trgf, tuple(trg_sents), trg_voc_size)
trg_sents = None
if n_src_sents != n_trg_sents:
print('ERROR: number of sentences differ in input files (%d vs %d)' %
(n_src_sents, n_trg_sents),
file=sys.stderr,
flush=True)
sys.exit(1)
iters = (args.iters1, args.iters2, args.iters3)
if any(x is None for x in iters[:args.model]):
iters = None
if args.verbose:
print('Aligning %d sentences...' % n_src_sents,
file=sys.stderr,
flush=True)
align(srcf.name,
trgf.name,
links_filename_fwd=args.links_filename_fwd,
links_filename_rev=args.links_filename_rev,
statistics_filename=None,
scores_filename=None,
model=args.model,
n_iterations=iters,
n_samplers=args.n_samplers,
quiet=not args.verbose,
rel_iterations=args.length,
null_prior=args.null_prior,
use_gdb=args.debug)
srcf.close()
trgf.close()
def main():
parser = argparse.ArgumentParser(
description=
'mkmodel.py: compute IBM-1 translation probabilties using eflomal, the efficient low-memory aligner'
)
parser.add_argument('-v',
'--verbose',
dest='verbose',
action="count",
default=0,
help='Enable verbose output')
parser.add_argument('--debug',
dest='debug',
action='store_true',
help='Enable gdb debugging of eflomal binary')
parser.add_argument('--no-lowercase',
dest='lowercase',
action='store_false',
default=True,
help='Do not lowercase input text')
parser.add_argument('--overwrite',
dest='overwrite',
action='store_true',
help='Overwrite existing output files')
parser.add_argument('--null-prior',
dest='null_prior',
default=0.2,
metavar='X',
type=float,
help='Prior probability of NULL alignment')
parser.add_argument(
'-m',
'--model',
dest='model',
default=3,
metavar='N',
type=int,
help='Model (1 = IBM1, 2 = IBM1+HMM, 3 = IBM1+HMM+fertility)')
parser.add_argument('--source-prefix',
dest='source_prefix_len',
default=0,
metavar='N',
type=int,
help='Length of prefix for stemming (source)')
parser.add_argument('--source-suffix',
dest='source_suffix_len',
default=0,
metavar='N',
type=int,
help='Length of suffix for stemming (source)')
parser.add_argument('--target-prefix',
dest='target_prefix_len',
default=0,
metavar='N',
type=int,
help='Length of prefix for stemming (target)')
parser.add_argument('--target-suffix',
dest='target_suffix_len',
default=0,
metavar='N',
type=int,
help='Length of suffix for stemming (target)')
parser.add_argument('-l',
'--length',
dest='length',
default=1.0,
metavar='X',
type=float,
help='Relative number of sampling iterations')
parser.add_argument('-1',
'--ibm1-iters',
dest='iters1',
default=None,
metavar='X',
type=int,
help='Number of IBM1 iterations (overrides --length)')
parser.add_argument('-2',
'--hmm-iters',
dest='iters2',
default=None,
metavar='X',
type=int,
help='Number of HMM iterations (overrides --length)')
parser.add_argument(
'-3',
'--fert-iters',
dest='iters3',
default=None,
metavar='X',
type=int,
help='Number of HMM+fertility iterations (overrides --length)')
parser.add_argument('--n-samplers',
dest='n_samplers',
default=3,
metavar='X',
type=int,
help='Number of independent samplers to run')
parser.add_argument('-s',
'--source',
dest='source_filename',
type=str,
metavar='filename',
help='Source text filename',
required=True)
parser.add_argument('-t',
'--target',
dest='target_filename',
type=str,
metavar='filename',
help='Target text filename',
required=True)
parser.add_argument(
'-f',
'--forward-probabilities',
dest='p_filename_fwd',
type=str,
metavar='filename',
help=
'Filename to write forward direction probabilities to, as pickle dump')
parser.add_argument(
'-r',
'--reverse-probabilities',
dest='p_filename_rev',
type=str,
metavar='filename',
help=
'Filename to write reverse direction probabilities to, as pickle dump')
parser.add_argument(
'-F',
'--forward-probabilities-human',
dest='p_filename_fwd_h',
type=str,
metavar='filename',
help=
'Filename to write forward direction probabilities to, as human readable dump'
)
parser.add_argument(
'-R',
'--reverse-probabilities-human',
dest='p_filename_rev_h',
type=str,
metavar='filename',
help=
'Filename to write reverse direction probabilities to, as human readable dump'
)
args = parser.parse_args()
logger = Logger(args.verbose)
if args.p_filename_fwd is None and args.p_filename_rev is None:
print('ERROR: no file to save probabilities (-f/-r), will do nothing.',
file=sys.stderr,
flush=True)
sys.exit(1)
for filename in (args.source_filename, args.target_filename):
if not os.path.exists(filename):
print('ERROR: input file %s does not exist!' % filename,
file=sys.stderr,
flush=True)
sys.exit(1)
for filename in (args.p_filename_fwd, args.p_filename_rev):
if (not args.overwrite) and (filename is not None) \
and os.path.exists(filename):
print('ERROR: output file %s exists, will not overwrite!' % \
filename,
file=sys.stderr, flush=True)
sys.exit(1)
if args.verbose:
print('Reading source text from %s...' % args.source_filename,
file=sys.stderr,
flush=True)
with xopen(args.source_filename, 'r', encoding='utf-8') as f:
src_sents, src_index = read_text(f, args.lowercase,
args.source_prefix_len,
args.source_suffix_len)
n_src_sents = len(src_sents)
src_voc_size = len(src_index)
src_index = None
srcf = NamedTemporaryFile('wb')
write_text(srcf, tuple(src_sents), src_voc_size)
src_sents = None
if args.verbose:
print('Reading target text from %s...' % args.target_filename,
file=sys.stderr,
flush=True)
with xopen(args.target_filename, 'r', encoding='utf-8') as f:
trg_sents, trg_index = read_text(f, args.lowercase,
args.target_prefix_len,
args.target_suffix_len)
trg_voc_size = len(trg_index)
n_trg_sents = len(trg_sents)
trg_index = None
trgf = NamedTemporaryFile('wb')
write_text(trgf, tuple(trg_sents), trg_voc_size)
trg_sents = None
if n_src_sents != n_trg_sents:
print('ERROR: number of sentences differ in input files (%d vs %d)' %
(n_src_sents, n_trg_sents),
file=sys.stderr,
flush=True)
sys.exit(1)
iters = (args.iters1, args.iters2, args.iters3)
if any(x is None for x in iters[:args.model]):
iters = None
if args.verbose:
print('Aligning %d sentences...' % n_src_sents,
file=sys.stderr,
flush=True)
fwd_alignment_file = NamedTemporaryFile('w')
rev_alignment_file = NamedTemporaryFile('w')
align(srcf.name,
trgf.name,
links_filename_fwd=fwd_alignment_file.name,
links_filename_rev=rev_alignment_file.name,
statistics_filename=None,
scores_filename=None,
model=args.model,
n_iterations=iters,
n_samplers=args.n_samplers,
quiet=not args.verbose,
rel_iterations=args.length,
null_prior=args.null_prior,
use_gdb=args.debug)
srcf.close()
trgf.close()
# split and, if requested, lowercase tokens
logger.info("Preprocessing sentences for probability estimation...")
with xopen(args.source_filename, 'r',
encoding='utf-8') as fsrc, xopen(args.target_filename,
'r',
encoding='utf-8') as ftgt:
src_sents = preprocess(fsrc.readlines(), args.lowercase)
trg_sents = preprocess(ftgt.readlines(), args.lowercase)
# extract token --> index hash table
logger.info("Extracting vocabulary...")
voc_s = make_voc(src_sents)
voc_t = make_voc(trg_sents)
if args.p_filename_fwd is not None:
logger.info("Estimating forward counts...")
counts, s_counts = compute_counts_fwd(voc_s, voc_t, src_sents,
trg_sents,
fwd_alignment_file.name,
args.lowercase)
logger.info("Estimating forward probabilities...")
p = compute_p(voc_s, voc_t, counts, s_counts)
logger.info("Saving forward probabilities...")
model = IBM1(p, voc_s, voc_t)
save_p(model, args.p_filename_fwd)
if args.p_filename_fwd_h is not None:
with xopen(args.p_filename_fwd_h, "w") as f:
model.dump(f)
if args.p_filename_rev is not None:
logger.info("Estimating reverse counts...")
counts, t_counts = compute_counts_rev(voc_s, voc_t, src_sents,
trg_sents,
rev_alignment_file.name,
args.lowercase)
logger.info("Estimating reverse probabilities...")
p = compute_p(voc_t, voc_s, counts, t_counts)
logger.info("Saving reverse probabilities...")
model = IBM1(p, voc_t, voc_s)
save_p(model, args.p_filename_rev)
if args.p_filename_rev_h is not None:
with xopen(args.p_filename_rev_h, "w") as f:
model.dump(f)
fwd_alignment_file.close()
rev_alignment_file.close()