exp=exp # Change it to your experiment dir
onnx_dir=onnx
python -m wenet.bin.export_onnx_cpu \
--config $exp/train.yaml \
--checkpoint $exp/final.pt \
--chunk_size 16 \
--output_dir $onnx_dir \
--num_decoding_left_chunks -1
# When it finishes, you can find `encoder.onnx`, `ctc.onnx`, and `decoder.onnx` in the $onnx_dir respectively.
- Step 2. Build. The build requires cmake 3.14 or above.
mkdir build && cd build
cmake -DONNX=ON -DTORCH=OFF -DWEBSOCKET=OFF -DGRPC=OFF ..
cmake --build .
- Step 3. Testing, the RTF(real time factor) is shown in the console.
export GLOG_logtostderr=1
export GLOG_v=2
wav_path=your_test_wav_path
onnx_dir=your_model_dir
units=units.txt # Change it to your model units path
# Make sure that the `chunk_size` and `num_left_chunks` variables are set to the corresponding values used when exporting the ONNX models.
./build/bin/decoder_main \
--chunk_size 16 \
--num_left_chunks -1 \
--wav_path $wav_path \
--onnx_dir $onnx_dir \
--unit_path $units 2>&1 | tee log.txt