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PaddleSpeech/speechx/examples/ds2_ol/onnx/run.sh

59 lines
1.6 KiB

#!/bin/bash
set -e
. path.sh
stage=0
stop_stage=100
. utils/parse_options.sh
data=data
exp=exp
mkdir -p $data $exp
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ];then
test -f $data/asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz || wget -c https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr0/asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz -P $data
pushd $data
tar zxvf asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz
popd
fi
dir=$data/exp/deepspeech2_online/checkpoints
model=avg_1.jit.pdmodel
param=avg_1.jit.pdiparams
output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ];then
# prune model by outputs
mkdir -p $exp/prune
# prune model deps on output_names.
./local/prune.sh $dir $model $param $output_names $exp/prune
fi
input_shape_dict="{'audio_chunk':[1,-1,161], 'audio_chunk_lens':[1], 'chunk_state_c_box':[5, 1, 1024], 'chunk_state_h_box':[5,1,1024]}"
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ];then
# infer shape by new shape
mkdir -p $exp/shape
python3 local/pd_infer_shape.py \
--model_dir $dir \
--model_filename $model \
--params_filename $param \
--save_dir $exp/shape \
--input_shape_dict=${input_shape_dict}
fi
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ];then
# to onnx
./local/tonnx.sh $dir $model $param $exp/model.onnx
./local/infer_check.py --input_file 'static_ds2online_inputs.pickle' --model_dir $dir --onnx_model $exp/model.onnx
fi