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PaddleSpeech/utils/spm_encode

102 lines
3.4 KiB

#!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in
# https://github.com/pytorch/fairseq/blob/master/LICENSE
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import argparse
import contextlib
import sys
import sentencepiece as spm
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--model", required=True,
help="sentencepiece model to use for encoding")
parser.add_argument("--inputs", nargs="+", default=['-'],
help="input files to filter/encode")
parser.add_argument("--outputs", nargs="+", default=['-'],
help="path to save encoded outputs")
parser.add_argument("--output_format", choices=["piece", "id"], default="piece")
parser.add_argument("--min-len", type=int, metavar="N",
help="filter sentence pairs with fewer than N tokens")
parser.add_argument("--max-len", type=int, metavar="N",
help="filter sentence pairs with more than N tokens")
args = parser.parse_args()
assert len(args.inputs) == len(args.outputs), \
"number of input and output paths should match"
sp = spm.SentencePieceProcessor()
sp.Load(args.model)
if args.output_format == "piece":
def encode(l):
return sp.EncodeAsPieces(l)
elif args.output_format == "id":
def encode(l):
return list(map(str, sp.EncodeAsIds(l)))
else:
raise NotImplementedError
if args.min_len is not None or args.max_len is not None:
def valid(line):
return (
(args.min_len is None or len(line) >= args.min_len) and
(args.max_len is None or len(line) <= args.max_len)
)
else:
def valid(lines):
return True
with contextlib.ExitStack() as stack:
inputs = [
stack.enter_context(open(input, "r", encoding="utf-8"))
if input != "-" else sys.stdin
for input in args.inputs
]
outputs = [
stack.enter_context(open(output, "w", encoding="utf-8"))
if output != "-" else sys.stdout
for output in args.outputs
]
stats = {
"num_empty": 0,
"num_filtered": 0,
}
def encode_line(line):
line = line.strip()
if len(line) > 0:
line = encode(line)
if valid(line):
return line
else:
stats["num_filtered"] += 1
else:
stats["num_empty"] += 1
return None
for i, lines in enumerate(zip(*inputs), start=1):
enc_lines = list(map(encode_line, lines))
if not any(enc_line is None for enc_line in enc_lines):
for enc_line, output_h in zip(enc_lines, outputs):
print(" ".join(enc_line), file=output_h)
if i % 10000 == 0:
print("processed {} lines".format(i), file=sys.stderr)
print("skipped {} empty lines".format(stats["num_empty"]), file=sys.stderr)
print("filtered {} lines".format(stats["num_filtered"]), file=sys.stderr)
if __name__ == "__main__":
main()