Problem with multiple outputs

[alefelipeoliveira]

Thanks for the great Repo! I am trying to use the but fot multiple inputs (3) and outputs(2), However, the output always colleted the same value for both outputs. Example: I changed the inputs, and for each new input sets, the pair of outputs is different from the previous one, but the pair is equal:

float input[3] = { 10, 20, 30 }; float output[2] = { 0 };

ml.predict(input, output);

Serial Console Printed: x: 1.92 y: 1.92

float input[3] = { 20, 10, 30 }; float output[2] = { 0 };

ml.predict(input, output);

Serial Console Printed: x: 1.30 y: 1.30

PS.: This issue do not occured with the model in the Keras notebook.

Notebook Environment: Google Colab Microcontroller: ESP32 - ESP-WROOM-32

Follow my code: https://github.com/alefelipeoliveira/EloquentTinyML_TEST

[eloquentarduino]

I will have to look at this. I honestly don't use Tensorflow, so I have to make some tests to understand your problem.

[alefelipeoliveira]

Hello,

Maybe the problem is in the function float predict(float *input, float *output = NULL) This functions only handle with index 0, but it is interesting to check the lenght of the array output before return: return this->output->data.f[0];

Example: output_1->output->data.f[1] output_n->output->data.f[n]

[eloquentarduino]

It is true that it returns only the first index, but that's just for convenience. The function will still copy the output->data.f array into the output array, however.

I plan to make my tests this afternoon, please be patient.

In the meantime, you can try to inject a print inside the library predict function.

// line 125, before if (output != NULL)

for (int i = 0; i < outputSize; i++)
    Serial.println(this->output->data.f[i]);

Does it prints the two outputs correctly?

[eloquentarduino]

I can confirm it works with multiple outputs. Please see the new example I uploaded. SineCosineExample

Also be sure to use the latest (from Github) version of the library.

[alefelipeoliveira]

I updated the library, and tested with my multiple input/output model, Now it is working fine, Thanks a lot for the support