Onnx configuration.

[grinay]

Hello @sdcb. I wanted to inquire about something. I'm in the process of transitioning from GPU to CPU, and for this, I've built a custom version of Paddle tailored for CPU usage, incorporating ONNX runtime. Here are the cmake configuration flags I used:

cmake \
    -DWITH_GPU=OFF \
    -DWITH_MKL=ON \
    -DWITH_MKLDNN=ON \
    -DWITH_ONNXRUNTIME=ON \
    -DWITH_AVX=ON \
    -DWITH_PYTHON=OFF \
    -DWITH_TESTING=OFF \
    -DWITH_ARM=OFF \
    -DWITH_NCCL=OFF \
    -DWITH_RCCL=OFF \
    -DON_INFER=ON \
    ..

Following this, I employed the setup as follows:

var recognitionModel = LocalRecognizationModel.EnglishV3;
var config = PaddleDevice.Onnx();
var predictor = recognitionModel.CreateConfig().Apply(config).CreatePredictor();

I'm uncertain if this is the correct method for configuring ONNX. While it seems to function, I'm not completely sure if it's actually running the ONNX version. I didn't perform any explicit model conversions and couldn't locate any ONNX files on the machine where this code is executed. Could you offer some guidance? Should I carry out an explicit model conversion and then instantiate a recognition model using this ONNX file, or is the code I have already sufficient, with Paddle handling the rest?

Additional into:
I found in a logs:

It seems to be converting by itself.
However where can I find this model? is there ay way to set the caching folder for it? As I running everything in Lambda, and don't want to consume time for conversion each lambda call, and store it in cache. May you advice?

[sdcb]

It's happening in memory, you can't find this model.