icefall/.github/scripts/run-librispeech-lstm-transducer-stateless2-2022-09-03.sh

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#!/usr/bin/env bash
#
set -e
log() {
# This function is from espnet
local fname=${BASH_SOURCE[1]##*/}
echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
}
cd egs/librispeech/ASR
repo_url=https://huggingface.co/csukuangfj/icefall-asr-librispeech-lstm-transducer-stateless2-2022-09-03
log "Downloading pre-trained model from $repo_url"
git lfs install
git clone $repo_url
repo=$(basename $repo_url)
abs_repo=$(realpath $repo)
log "Display test files"
tree $repo/
soxi $repo/test_wavs/*.wav
ls -lh $repo/test_wavs/*.wav
pushd $repo/exp
ln -s pretrained-iter-468000-avg-16.pt pretrained.pt
ln -s pretrained-iter-468000-avg-16.pt epoch-99.pt
popd
log "Test exporting with torch.jit.trace()"
./lstm_transducer_stateless2/export.py \
--exp-dir $repo/exp \
--bpe-model $repo/data/lang_bpe_500/bpe.model \
--epoch 99 \
--avg 1 \
--use-averaged-model 0 \
--jit-trace 1
log "Decode with models exported by torch.jit.trace()"
./lstm_transducer_stateless2/jit_pretrained.py \
--bpe-model $repo/data/lang_bpe_500/bpe.model \
--encoder-model-filename $repo/exp/encoder_jit_trace.pt \
--decoder-model-filename $repo/exp/decoder_jit_trace.pt \
--joiner-model-filename $repo/exp/joiner_jit_trace.pt \
$repo/test_wavs/1089-134686-0001.wav \
$repo/test_wavs/1221-135766-0001.wav \
$repo/test_wavs/1221-135766-0002.wav
for sym in 1 2 3; do
log "Greedy search with --max-sym-per-frame $sym"
./lstm_transducer_stateless2/pretrained.py \
--method greedy_search \
--max-sym-per-frame $sym \
--checkpoint $repo/exp/pretrained.pt \
--bpe-model $repo/data/lang_bpe_500/bpe.model \
$repo/test_wavs/1089-134686-0001.wav \
$repo/test_wavs/1221-135766-0001.wav \
$repo/test_wavs/1221-135766-0002.wav
done
for method in modified_beam_search beam_search fast_beam_search; do
log "$method"
./lstm_transducer_stateless2/pretrained.py \
--method $method \
--beam-size 4 \
--checkpoint $repo/exp/pretrained.pt \
--bpe-model $repo/data/lang_bpe_500/bpe.model \
$repo/test_wavs/1089-134686-0001.wav \
$repo/test_wavs/1221-135766-0001.wav \
$repo/test_wavs/1221-135766-0002.wav
done
echo "GITHUB_EVENT_NAME: ${GITHUB_EVENT_NAME}"
echo "GITHUB_EVENT_LABEL_NAME: ${GITHUB_EVENT_LABEL_NAME}"
if [[ x"${GITHUB_EVENT_LABEL_NAME}" == x"shallow-fusion" ]]; then
lm_repo_url=https://huggingface.co/ezerhouni/icefall-librispeech-rnn-lm
log "Download pre-trained RNN-LM model from ${lm_repo_url}"
GIT_LFS_SKIP_SMUDGE=1 git clone $lm_repo_url
lm_repo=$(basename $lm_repo_url)
pushd $lm_repo
git lfs pull --include "exp/pretrained.pt"
mv exp/pretrained.pt exp/epoch-88.pt
popd
mkdir -p lstm_transducer_stateless2/exp
ln -sf $PWD/$repo/exp/pretrained.pt lstm_transducer_stateless2/exp/epoch-999.pt
ln -s $PWD/$repo/data/lang_bpe_500 data/
ls -lh data
ls -lh lstm_transducer_stateless2/exp
log "Decoding test-clean and test-other with RNN LM"
./lstm_transducer_stateless2/decode.py \
--use-averaged-model 0 \
--epoch 999 \
--avg 1 \
--exp-dir lstm_transducer_stateless2/exp \
--max-duration 600 \
--decoding-method modified_beam_search_lm_shallow_fusion \
--beam 4 \
--use-shallow-fusion 1 \
--lm-type rnn \
--lm-exp-dir $lm_repo/exp \
--lm-epoch 88 \
--lm-avg 1 \
--lm-scale 0.3 \
--rnn-lm-num-layers 3 \
--rnn-lm-tie-weights 1
fi
if [[ x"${GITHUB_EVENT_LABEL_NAME}" == x"LODR" ]]; then
bigram_repo_url=https://huggingface.co/marcoyang/librispeech_bigram
log "Download bi-gram LM from ${bigram_repo_url}"
GIT_LFS_SKIP_SMUDGE=1 git clone $bigram_repo_url
bigramlm_repo=$(basename $bigram_repo_url)
pushd $bigramlm_repo
git lfs pull --include "2gram.fst.txt"
cp 2gram.fst.txt $abs_repo/data/lang_bpe_500/.
popd
lm_repo_url=https://huggingface.co/ezerhouni/icefall-librispeech-rnn-lm
log "Download pre-trained RNN-LM model from ${lm_repo_url}"
GIT_LFS_SKIP_SMUDGE=1 git clone $lm_repo_url
lm_repo=$(basename $lm_repo_url)
pushd $lm_repo
git lfs pull --include "exp/pretrained.pt"
mv exp/pretrained.pt exp/epoch-88.pt
popd
mkdir -p lstm_transducer_stateless2/exp
ln -sf $PWD/$repo/exp/pretrained.pt lstm_transducer_stateless2/exp/epoch-999.pt
ln -s $PWD/$repo/data/lang_bpe_500 data/
ls -lh data
ls -lh lstm_transducer_stateless2/exp
log "Decoding test-clean and test-other"
./lstm_transducer_stateless2/decode.py \
--use-averaged-model 0 \
--epoch 999 \
--avg 1 \
--exp-dir lstm_transducer_stateless2/exp \
--max-duration 600 \
--decoding-method modified_beam_search_LODR \
--beam 4 \
--use-shallow-fusion 1 \
--lm-type rnn \
--lm-exp-dir $lm_repo/exp \
--lm-scale 0.4 \
--lm-epoch 88 \
--rnn-lm-avg 1 \
--rnn-lm-num-layers 3 \
--rnn-lm-tie-weights 1 \
--tokens-ngram 2 \
--ngram-lm-scale -0.16
fi
if [[ x"${GITHUB_EVENT_NAME}" == x"schedule" ]]; then
mkdir -p lstm_transducer_stateless2/exp
ln -s $PWD/$repo/exp/pretrained.pt lstm_transducer_stateless2/exp/epoch-999.pt
ln -s $PWD/$repo/data/lang_bpe_500 data/
ls -lh data
ls -lh lstm_transducer_stateless2/exp
log "Decoding test-clean and test-other"
# use a small value for decoding with CPU
max_duration=100
for method in greedy_search fast_beam_search modified_beam_search; do
log "Decoding with $method"
./lstm_transducer_stateless2/decode.py \
--decoding-method $method \
--epoch 999 \
--avg 1 \
--use-averaged-model 0 \
--max-duration $max_duration \
--exp-dir lstm_transducer_stateless2/exp
done
rm lstm_transducer_stateless2/exp/*.pt
fi