#!/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/Zengwei/icefall-asr-librispeech-zipformer-mmi-2022-12-08 log "Downloading pre-trained model from $repo_url" GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url repo=$(basename $repo_url) log "Display test files" tree $repo/ ls -lh $repo/test_wavs/*.wav pushd $repo/exp git lfs pull --include "data/lang_bpe_500/3gram.pt" git lfs pull --include "data/lang_bpe_500/4gram.pt" git lfs pull --include "data/lang_bpe_500/L.pt" git lfs pull --include "data/lang_bpe_500/LG.pt" git lfs pull --include "data/lang_bpe_500/Linv.pt" git lfs pull --include "data/lang_bpe_500/bpe.model" git lfs pull --include "exp/cpu_jit.pt" git lfs pull --include "exp/pretrained.pt" ln -s pretrained.pt epoch-99.pt ls -lh *.pt popd log "Export to torchscript model" ./zipformer_mmi/export.py \ --exp-dir $repo/exp \ --use-averaged-model false \ --bpe-model $repo/data/lang_bpe_500/bpe.model \ --epoch 99 \ --avg 1 \ --jit 1 ls -lh $repo/exp/*.pt log "Decode with models exported by torch.jit.script()" ./zipformer_mmi/jit_pretrained.py \ --bpe-model $repo/data/lang_bpe_500/bpe.model \ --nn-model-filename $repo/exp/cpu_jit.pt \ --lang-dir $repo/data/lang_bpe_500 \ $repo/test_wavs/1089-134686-0001.wav \ $repo/test_wavs/1221-135766-0001.wav \ $repo/test_wavs/1221-135766-0002.wav for method in 1best nbest nbest-rescoring-LG nbest-rescoring-3-gram nbest-rescoring-4-gram; do log "$method" ./zipformer_mmi/pretrained.py \ --method $method \ --checkpoint $repo/exp/pretrained.pt \ --lang-dir $repo/data/lang_bpe_500 \ --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_NAME}" == x"schedule" || x"${GITHUB_EVENT_LABEL_NAME}" == x"run-decode" ]]; then mkdir -p zipformer_mmi/exp ln -s $PWD/$repo/exp/pretrained.pt zipformer_mmi/exp/epoch-999.pt ln -s $PWD/$repo/data/lang_bpe_500 data/ ls -lh data ls -lh zipformer_mmi/exp log "Decoding test-clean and test-other" # use a small value for decoding with CPU max_duration=100 for method in 1best nbest nbest-rescoring-LG nbest-rescoring-3-gram nbest-rescoring-4-gram; do log "Decoding with $method" ./zipformer_mmi/decode.py \ --decoding-method $method \ --epoch 999 \ --avg 1 \ --use-averaged-model 0 \ --nbest-scale 1.2 \ --hp-scale 1.0 \ --max-duration $max_duration \ --lang-dir $repo/data/lang_bpe_500 \ --exp-dir zipformer_mmi/exp done rm zipformer_mmi/exp/*.pt fi