| |
| |
| |
| |
| |
| |
|
|
| from __future__ import absolute_import, division, print_function, 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(input): |
| return sp.EncodeAsPieces(input) |
|
|
| elif args.output_format == "id": |
|
|
| def encode(input): |
| return list(map(str, sp.EncodeAsIds(input))) |
|
|
| 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() |
|
|