in torchbenchmark/models/speech_transformer/speech_transformer/utils/text2token.py [0:0]
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--nchar', '-n', default=1, type=int,
help='number of characters to split, i.e., \
aabb -> a a b b with -n 1 and aa bb with -n 2')
parser.add_argument('--skip-ncols', '-s', default=0, type=int,
help='skip first n columns')
parser.add_argument('--space', default='<space>', type=str,
help='space symbol')
parser.add_argument('--non-lang-syms', '-l', default=None, type=str,
help='list of non-linguistic symobles, e.g., <NOISE> etc.')
parser.add_argument('text', type=str, default=False, nargs='?',
help='input text')
args = parser.parse_args()
rs = []
if args.non_lang_syms is not None:
with open(args.non_lang_syms, 'r') as f:
nls = [unicode(x.rstrip(), 'utf_8') for x in f.readlines()]
rs = [re.compile(re.escape(x)) for x in nls]
if args.text:
f = open(args.text)
else:
f = sys.stdin
line = f.readline()
n = args.nchar
while line:
x = unicode(line, 'utf_8').split()
print ' '.join(x[:args.skip_ncols]).encode('utf_8'),
a = ' '.join(x[args.skip_ncols:])
# get all matched positions
match_pos = []
for r in rs:
i = 0
while i >= 0:
m = r.search(a, i)
if m:
match_pos.append([m.start(), m.end()])
i = m.end()
else:
break
if len(match_pos) > 0:
chars = []
i = 0
while i < len(a):
start_pos, end_pos = exist_or_not(i, match_pos)
if start_pos is not None:
chars.append(a[start_pos:end_pos])
i = end_pos
else:
chars.append(a[i])
i += 1
a = chars
a = [a[i:i + n] for i in range(0, len(a), n)]
a_flat = []
for z in a:
a_flat.append("".join(z))
a_chars = [z.replace(' ', args.space) for z in a_flat]
print ' '.join(a_chars).encode('utf_8')
line = f.readline()