#!/usr/bin/env bash set -ex 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/yesno/ASR log "data preparation" ./prepare.sh log "training" python3 ./tdnn/train.py log "decoding" python3 ./tdnn/decode.py log "export to pretrained.pt" python3 ./tdnn/export.py --epoch 14 --avg 2 python3 ./tdnn/pretrained.py \ --checkpoint ./tdnn/exp/pretrained.pt \ --HLG ./data/lang_phone/HLG.pt \ --words-file ./data/lang_phone/words.txt \ download/waves_yesno/0_0_0_1_0_0_0_1.wav \ download/waves_yesno/0_0_1_0_0_0_1_0.wav log "Test exporting to torchscript" python3 ./tdnn/export.py --epoch 14 --avg 2 --jit 1 python3 ./tdnn/jit_pretrained.py \ --nn-model ./tdnn/exp/cpu_jit.pt \ --HLG ./data/lang_phone/HLG.pt \ --words-file ./data/lang_phone/words.txt \ download/waves_yesno/0_0_0_1_0_0_0_1.wav \ download/waves_yesno/0_0_1_0_0_0_1_0.wav log "Test exporting to onnx" python3 ./tdnn/export_onnx.py --epoch 14 --avg 2 log "Test float32 model" python3 ./tdnn/onnx_pretrained.py \ --nn-model ./tdnn/exp/model-epoch-14-avg-2.onnx \ --HLG ./data/lang_phone/HLG.pt \ --words-file ./data/lang_phone/words.txt \ download/waves_yesno/0_0_0_1_0_0_0_1.wav \ download/waves_yesno/0_0_1_0_0_0_1_0.wav log "Test int8 model" python3 ./tdnn/onnx_pretrained.py \ --nn-model ./tdnn/exp/model-epoch-14-avg-2.int8.onnx \ --HLG ./data/lang_phone/HLG.pt \ --words-file ./data/lang_phone/words.txt \ download/waves_yesno/0_0_0_1_0_0_0_1.wav \ download/waves_yesno/0_0_1_0_0_0_1_0.wav log "Test decoding with H" python3 ./tdnn/export.py --epoch 14 --avg 2 --jit 1 python3 ./tdnn/jit_pretrained_decode_with_H.py \ --nn-model ./tdnn/exp/cpu_jit.pt \ --H ./data/lang_phone/H.fst \ --tokens ./data/lang_phone/tokens.txt \ ./download/waves_yesno/0_0_0_1_0_0_0_1.wav \ ./download/waves_yesno/0_0_1_0_0_0_1_0.wav \ ./download/waves_yesno/0_0_1_0_0_1_1_1.wav log "Test decoding with HL" python3 ./tdnn/export.py --epoch 14 --avg 2 --jit 1 python3 ./tdnn/jit_pretrained_decode_with_HL.py \ --nn-model ./tdnn/exp/cpu_jit.pt \ --HL ./data/lang_phone/HL.fst \ --words ./data/lang_phone/words.txt \ ./download/waves_yesno/0_0_0_1_0_0_0_1.wav \ ./download/waves_yesno/0_0_1_0_0_0_1_0.wav \ ./download/waves_yesno/0_0_1_0_0_1_1_1.wav log "Show generated files" ls -lh tdnn/exp ls -lh data/lang_phone