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PaddleSpeech/third_party/pymmseg-cpp/bin/pymmseg

159 lines
3.7 KiB

E2E/Streaming Transformer/Conformer ASR (#578) * add cmvn and label smoothing loss layer * add layer for transformer * add glu and conformer conv * add torch compatiable hack, mask funcs * not hack size since it exists * add test; attention * add attention, common utils, hack paddle * add audio utils * conformer batch padding mask bug fix #223 * fix typo, python infer fix rnn mem opt name error and batchnorm1d, will be available at 2.0.2 * fix ci * fix ci * add encoder * refactor egs * add decoder * refactor ctc, add ctc align, refactor ckpt, add warmup lr scheduler, cmvn utils * refactor docs * add fix * fix readme * fix bugs, refactor collator, add pad_sequence, fix ckpt bugs * fix docstring * refactor data feed order * add u2 model * refactor cmvn, test * add utils * add u2 config * fix bugs * fix bugs * fix autograd maybe has problem when using inplace operation * refactor data, build vocab; add format data * fix text featurizer * refactor build vocab * add fbank, refactor feature of speech * refactor audio feat * refactor data preprare * refactor data * model init from config * add u2 bins * flake8 * can train * fix bugs, add coverage, add scripts * test can run * fix data * speed perturb with sox * add spec aug * fix for train * fix train logitc * fix logger * log valid loss, time dataset process * using np for speed perturb, remove some debug log of grad clip * fix logger * fix build vocab * fix logger name * using module logger as default * fix * fix install * reorder imports * fix board logger * fix logger * kaldi fbank and mfcc * fix cmvn and print prarams * fix add_eos_sos and cmvn * fix cmvn compute * fix logger and cmvn * fix subsampling, label smoothing loss, remove useless * add notebook test * fix log * fix tb logger * multi gpu valid * fix log * fix log * fix config * fix compute cmvn, need paddle 2.1 * add cmvn notebook * fix layer tools * fix compute cmvn * add rtf * fix decoding * fix layer tools * fix log, add avg script * more avg and test info * fix dataset pickle problem; using 2.1 paddle; num_workers can > 0; ckpt save in exp dir;fix setup.sh; * add vimrc * refactor tiny script, add transformer and stream conf * spm demo; librisppech scripts and confs * fix log * add librispeech scripts * refactor data pipe; fix conf; fix u2 default params * fix bugs * refactor aishell scripts * fix test * fix cmvn * fix s0 scripts * fix ds2 scripts and bugs * fix dev & test dataset filter * fix dataset filter * filter dev * fix ckpt path * filter test, since librispeech will cause OOM, but all test wer will be worse, since mismatch train with test * add comment * add syllable doc * fix ds2 configs * add doc * add pypinyin tools * fix decoder using blank_id=0 * mmseg with pybind11 * format code
3 years ago
#!/usr/bin/env python3
import cProfile
import getopt
import os
import pstats
import sys
from io import StringIO
from os.path import dirname
from os.path import join
import mmseg
class Dictionary():
dictionaries = (
('chars',
os.path.join(os.path.dirname(__file__), '../mmseg/data', 'chars.dic')),
('words',
os.path.join(os.path.dirname(__file__), '../mmseg/data', 'words.dic')),
)
@staticmethod
def load_dictionaries():
for t, d in Dictionary.dictionaries:
if t == 'chars':
if not mmseg.load_chars(d):
raise IOError("Cannot open '%s'" % d)
elif t == 'words':
if not mmseg.load_words(d):
raise IOError("Cannot open '%s'" % d)
mmseg.dict_load_defaults = Dictionary.load_dictionaries
class Algorithm(object):
def __init__(self, text: str):
"""\
Create an Algorithm instance to segment text.
"""
self.text = text.encode('utf8')
# add a reference to prevent the string buffer from
# being GC-ed
self.algor = mmseg.Algorithm(text)
self.destroied = False
def __iter__(self):
"""\
Iterate through all tokens. Note the iteration has
side-effect: an Algorithm object can only be iterated
once.
"""
while True:
tk = self.next_token()
if tk is None:
raise StopIteration
yield tk
def next_token(self):
"""\
Get next token. When no token available, return None.
"""
if self.destroied:
return None
tk = self.algor.next_token()
if tk.length == 0:
# no token available, the algorithm object
# can be destroied
self._destroy()
return None
else:
return tk
def _destroy(self):
if not self.destroied:
self.destroied = True
def __del__(self):
self._destroy()
def profile(fn):
def wrapper(*args, **kwargs):
profiler = cProfile.Profile()
stream = StringIO()
profiler.enable()
try:
res = fn(*args, **kwargs)
finally:
profiler.disable()
stats = pstats.Stats(profiler, stream=stream)
stats.sort_stats('time')
print("", file=stream)
print("=" * 100, file=stream)
print("Stats:", file=stream)
stats.print_stats()
print("=" * 100, file=stream)
print("Callers:", file=stream)
stats.print_callers()
print("=" * 100, file=stream)
print("Callees:", file=stream)
stats.print_callees()
print(stream.getvalue(), file=sys.stderr)
stream.close()
return res
return wrapper
def print_usage():
print("""
mmseg Segment Chinese text. Read from stdin and print to stdout.
Options:
-h
--help Print this message
-s
--separator Select the separator of the segmented text. Default is space.
""")
sys.exit(0)
separator = " "
optlst, args = getopt.getopt(sys.argv[1:], 'hs:')
for opt, val in optlst:
if opt == '-h':
print_usage()
elif opt == '-s':
separator = val
# load default dictionaries
mmseg.dict_load_defaults()
def process_tokens(stdin, separator):
ret = ''
first = True
algor = Algorithm(stdin)
try:
for tk in algor:
if not first:
ret += separator
ret += tk.text
first = False
except RuntimeError:
pass
return ret
sys.stdout.write(process_tokens(sys.stdin.read(), separator))
sys.stdout.write('\n')