Thorough deployment about connxr

[alrevuelta]

Very fair request. We had #30 for this but haven't had time to look into it.

Some quick information that hope you find useful. The inference function runs inference on a model given a set of inputs.

inference(Onnx__ModelProto *model, Onnx__TensorProto **inputs, int nInputs)

That input is propagated towards the output, and in all_context global variable you can access each node output.

So it shouldn't be very difficult to do. Some quick C pseudocode-ish. Have a look to the documentation for more info about the struct Onnx__TensorProto.

int main()
{
  // Create your tensor and alloc some mem
  Onnx__TensorProto *inp0set0 = ...;

  // Allocate memory for dims, float_data,...

  inp0set0->float_data[0] = 10;
  inp0set0->float_data[1] = 10;

  // Note that you have to also fill the n_dims, dims, name
  inp0set0->name = ...;

  /* Open your onnx model */
  Onnx__ModelProto *model = openOnnxFile("model.onnx");

  /* Set the input name */
  inp0set0->name = model->graph->input[0]->name;

  /* Create the array of inputs to the model */
  Onnx__TensorProto *inputs[] = { inp0set0 };

  /* Resolve all inputs and operators */
  resolve(model, inputs, 1);

  /* Run inference on your input */
  Onnx__TensorProto **output = inference(model, inputs, 1);

  /* Print the last output which is the model output */
  for (int i = 0; i < all_context[_populatedIdx].outputs[0]->n_float_data; i++){
      printf("n_float_data[%d] = %f\n", i, all_context[_populatedIdx].outputs[0]->float_data[i]);
  }
}

Let me know if you need further assistance. Have a look into inference.c file and ``connxr.c`, you can reuse some stuff. And btw, if you develop one example would be great to the examples folder or existing documentation.

Edit: The code was wrong. Forgot to call the resolve function.

[alrevuelta]

Just edited the above code, there was a mistake.

[alrevuelta]

Closing this due to inactivity, let us know if you need further support.