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