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123 lines
4.0 KiB
123 lines
4.0 KiB
#!/bin/bash
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set -e
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. path.sh
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stage=0
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stop_stage=50
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tarfile=asr0_deepspeech2_online_wenetspeech_ckpt_1.0.2.model.tar.gz
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#tarfile=asr0_deepspeech2_online_aishell_fbank161_ckpt_1.0.1.model.tar.gz
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model_prefix=avg_10.jit
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#model_prefix=avg_1.jit
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model=${model_prefix}.pdmodel
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param=${model_prefix}.pdiparams
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. utils/parse_options.sh
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data=data
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exp=exp
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mkdir -p $data $exp
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dir=$data/exp/deepspeech2_online/checkpoints
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# wenetspeech or aishell
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model_type=$(echo $tarfile | cut -d '_' -f 4)
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ];then
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test -f $data/$tarfile || wget -P $data -c https://paddlespeech.bj.bcebos.com/s2t/$model_type/asr0/$tarfile
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# wenetspeech ds2 model
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pushd $data
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tar zxvf $tarfile
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popd
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# ds2 model demo inputs
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pushd $exp
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wget -c http://paddlespeech.bj.bcebos.com/speechx/examples/ds2_ol/onnx/static_ds2online_inputs.pickle
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popd
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fi
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output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0
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if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ];then
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# prune model by outputs
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mkdir -p $exp/prune
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# prune model deps on output_names.
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./local/prune.sh $dir $model $param $output_names $exp/prune
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fi
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# aishell rnn hidden is 1024
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# wenetspeech rnn hiddn is 2048
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if [ $model_type == 'aishell' ];then
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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]}"
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elif [ $model_type == 'wenetspeech' ];then
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input_shape_dict="{'audio_chunk':[1,-1,161], 'audio_chunk_lens':[1], 'chunk_state_c_box':[5, 1, 2048], 'chunk_state_h_box':[5,1,2048]}"
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else
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echo "not support: $model_type"
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exit -1
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fi
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if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ];then
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# infer shape by new shape
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mkdir -p $exp/shape
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echo $input_shape_dict
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python3 local/pd_infer_shape.py \
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--model_dir $dir \
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--model_filename $model \
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--params_filename $param \
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--save_dir $exp/shape \
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--input_shape_dict="${input_shape_dict}"
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fi
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input_file=$exp/static_ds2online_inputs.pickle
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test -e $input_file
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if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ];then
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# to onnx
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./local/tonnx.sh $dir $model $param $exp/model.onnx
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./local/infer_check.py --input_file $input_file --model_type $model_type --model_dir $dir --model_prefix $model_prefix --onnx_model $exp/model.onnx
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fi
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if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ] ;then
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# ort graph optmize
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./local/ort_opt.py --model_in $exp/model.onnx --opt_level 0 --model_out $exp/model.ort.opt.onnx
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./local/infer_check.py --input_file $input_file --model_type $model_type --model_dir $dir --model_prefix $model_prefix --onnx_model $exp/model.ort.opt.onnx
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fi
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if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ];then
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# convert opset_num to 11
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./local/onnx_convert_opset.py --target-opset 11 --model-file $exp/model.ort.opt.onnx --save-model $exp/model.optset11.onnx
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# quant model
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nodes_to_exclude='p2o.Conv.0,p2o.Conv.2'
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./local/ort_dyanmic_quant.py --model-in $exp/model.optset11.onnx --model-out $exp/model.optset11.quant.onnx --nodes-to-exclude "${nodes_to_exclude}"
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./local/infer_check.py --input_file $input_file --model_type $model_type --model_dir $dir --model_prefix $model_prefix --onnx_model $exp/model.optset11.quant.onnx
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fi
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# aishell rnn hidden is 1024
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# wenetspeech rnn hiddn is 2048
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if [ $model_type == 'aishell' ];then
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input_shape="audio_chunk:1,-1,161 audio_chunk_lens:1 chunk_state_c_box:5,1,1024 chunk_state_h_box:5,1,1024"
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elif [ $model_type == 'wenetspeech' ];then
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input_shape="audio_chunk:1,-1,161 audio_chunk_lens:1 chunk_state_c_box:5,1,2048 chunk_state_h_box:5,1,2048"
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else
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echo "not support: $model_type"
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exit -1
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fi
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if [ ${stage} -le 51 ] && [ ${stop_stage} -ge 51 ] ;then
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# wenetspeech ds2 model execed 2GB limit, will error.
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# simplifying onnx model
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./local/onnx_opt.sh $exp/model.onnx $exp/model.opt.onnx "$input_shape"
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./local/infer_check.py --input_file $input_file --model_type $model_type --model_dir $dir --model_prefix $model_prefix --onnx_model $exp/model.opt.onnx
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fi
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