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97
egs/librispeech/conformer/local/download_and_untar.sh
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97
egs/librispeech/conformer/local/download_and_untar.sh
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#!/usr/bin/env bash
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# Copyright 2014 Johns Hopkins University (author: Daniel Povey)
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# Apache 2.0
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remove_archive=false
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if [ "$1" == --remove-archive ]; then
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remove_archive=true
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shift
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fi
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if [ $# -ne 3 ]; then
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echo "Usage: $0 [--remove-archive] <data-base> <url-base> <corpus-part>"
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echo "e.g.: $0 /export/a15/vpanayotov/data www.openslr.org/resources/11 dev-clean"
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echo "With --remove-archive it will remove the archive after successfully un-tarring it."
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echo "<corpus-part> can be one of: dev-clean, test-clean, dev-other, test-other,"
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echo " train-clean-100, train-clean-360, train-other-500."
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exit 1
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fi
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data=$1
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url=$2
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part=$3
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if [ ! -d "$data" ]; then
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echo "$0: no such directory $data"
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exit 1
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fi
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part_ok=false
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list="dev-clean test-clean dev-other test-other train-clean-100 train-clean-360 train-other-500"
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for x in $list; do
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if [ "$part" == $x ]; then part_ok=true; fi
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done
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if ! $part_ok; then
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echo "$0: expected <corpus-part> to be one of $list, but got '$part'"
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exit 1
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fi
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if [ -z "$url" ]; then
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echo "$0: empty URL base."
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exit 1
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fi
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if [ -f $data/LibriSpeech/$part/.complete ]; then
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echo "$0: data part $part was already successfully extracted, nothing to do."
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exit 0
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fi
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# sizes of the archive files in bytes. This is some older versions.
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sizes_old="371012589 347390293 379743611 361838298 6420417880 23082659865 30626749128"
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# sizes_new is the archive file sizes of the final release. Some of these sizes are of
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# things we probably won't download.
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sizes_new="337926286 314305928 695964615 297279345 87960560420 33373768 346663984 328757843 6387309499 23049477885 30593501606"
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if [ -f $data/$part.tar.gz ]; then
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size=$(/bin/ls -l $data/$part.tar.gz | awk '{print $5}')
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size_ok=false
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for s in $sizes_old $sizes_new; do if [ $s == $size ]; then size_ok=true; fi; done
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if ! $size_ok; then
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echo "$0: removing existing file $data/$part.tar.gz because its size in bytes $size"
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echo "does not equal the size of one of the archives."
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rm $data/$part.tar.gz
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else
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echo "$data/$part.tar.gz exists and appears to be complete."
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fi
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fi
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if [ ! -f $data/$part.tar.gz ]; then
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if ! which wget >/dev/null; then
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echo "$0: wget is not installed."
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exit 1
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fi
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full_url=$url/$part.tar.gz
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echo "$0: downloading data from $full_url. This may take some time, please be patient."
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if ! wget -P $data --no-check-certificate $full_url; then
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echo "$0: error executing wget $full_url"
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exit 1
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fi
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fi
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if ! tar -C $data -xvzf $data/$part.tar.gz; then
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echo "$0: error un-tarring archive $data/$part.tar.gz"
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exit 1
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fi
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touch $data/LibriSpeech/$part/.complete
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echo "$0: Successfully downloaded and un-tarred $data/$part.tar.gz"
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if $remove_archive; then
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echo "$0: removing $data/$part.tar.gz file since --remove-archive option was supplied."
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rm $data/$part.tar.gz
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fi
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98
egs/librispeech/conformer/local/spm_encode.py
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egs/librispeech/conformer/local/spm_encode.py
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#!/usr/bin/env python
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# Copyright (c) Facebook, Inc. and its affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the license found in
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# https://github.com/pytorch/fairseq/blob/master/LICENSE
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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("--model", required=True,
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help="sentencepiece model to use for encoding")
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parser.add_argument("--inputs", nargs="+", default=['-'],
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help="input files to filter/encode")
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parser.add_argument("--outputs", nargs="+", default=['-'],
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help="path to save encoded outputs")
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parser.add_argument("--output_format", choices=["piece", "id"], default="piece")
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parser.add_argument("--min-len", type=int, metavar="N",
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help="filter sentence pairs with fewer than N tokens")
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parser.add_argument("--max-len", type=int, metavar="N",
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help="filter sentence pairs with more than N tokens")
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args = parser.parse_args()
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assert len(args.inputs) == len(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 (
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(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 != "-" 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 != "-" 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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12
egs/librispeech/conformer/local/spm_train.py
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12
egs/librispeech/conformer/local/spm_train.py
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#!/usr/bin/env python3
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# Copyright (c) Facebook, Inc. and its affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the license found in the
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# https://github.com/pytorch/fairseq/blob/master/LICENSE
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import sys
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import sentencepiece as spm
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if __name__ == "__main__":
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spm.SentencePieceTrainer.Train(" ".join(sys.argv[1:]))
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