Hi! I have a sequential model from Keras and I'm trying to deploy it to Arduino Uno using AIfES.

This is my model in Keras:

Model: "sequential_2"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 input (Dense)               (None, 10)                510       
                                                                 
 dense_2 (Dense)             (None, 10)                110       
                                                                 
 output (Dense)              (None, 5)                 55        
                                                                 
=================================================================
Total params: 675
Trainable params: 675
Non-trainable params: 0
________________________________________________________________

However, my outputs are 0. Can you check if my configuration in Arduino is correct?

// Tensor for the input data
  uint16_t input_shape[] = {DATA_COUNT, INPUTS};                      // Definition of the input shape
  aitensor_t input_tensor = AITENSOR_2D_F32(input_shape, input_data); // Creation of the input AIfES tensor with two dimensions and data type F32 (float32)

  // Tensor for the output data
  float output_data[DATA_COUNT * OUTPUTS];          // Output data
  uint16_t output_shape[2] = {DATA_COUNT, OUTPUTS}; // Definition of the output shape
  aitensor_t output_tensor = AITENSOR_2D_F32(output_shape, output_data);

  // ---------------------------------- Layer definition ---------------------------------------

  uint16_t input_layer_shape[] = {1, INPUTS};                                  // Definition of the input layer shape (The 1 must remain here regardless of the number of data sets)
  ailayer_input_f32_t input_layer = AILAYER_INPUT_F32_M(2, input_layer_shape); // Creation of the AIfES input layer
  ailayer_dense_f32_t dense_layer_1 = AILAYER_DENSE_F32_M(NEURONS_1, W0_data, b0_data);
  ailayer_relu_f32_t relu_layer_1 = AILAYER_RELU_F32_M(); // Hidden activation function
  ailayer_dense_f32_t dense_layer_2 = AILAYER_DENSE_F32_M(NEURONS_2, W1_data, b1_data);
  ailayer_relu_f32_t relu_layer_2 = AILAYER_RELU_F32_M(); // Output activation function
  ailayer_dense_f32_t output_layer = AILAYER_DENSE_F32_M(OUTPUTS, W2_data, b2_data);
  ailayer_relu_f32_t relu_output_layer = AILAYER_RELU_F32_M();

  ailoss_mse_t mse_loss; // Loss: mean squared error

  // --------------------------- Define the structure of the model ----------------------------

  aimodel_t model; // AIfES model
  ailayer_t *x;    // Layer object from AIfES, contains the layers

  // Passing the layers to the AIfES model
  model.input_layer = ailayer_input_f32_default(&input_layer);
  x = ailayer_dense_f32_default(&dense_layer_1, model.input_layer);
  x = ailayer_relu_f32_default(&relu_layer_1, x);
  x = ailayer_dense_f32_default(&dense_layer_2, x);
  x = ailayer_relu_f32_default(&relu_layer_2, x);
  x = ailayer_dense_f32_default(&output_layer, x);
  model.output_layer = ailayer_relu_f32_default(&relu_output_layer, x);

  // Add the loss to the AIfES model
  model.loss = ailoss_mse_f32_default(&mse_loss, model.output_layer);

  aialgo_compile_model(&model); // Compile the AIfES model

Thank you!!!

Really impressed with this Arduino Library so far.

Any plans for future support for the Portenta Vision Shields?

I hve some draft examples using Edge Impulse or my own generic ML @rocksetta methods converting from TensorflowJS to TensorflowMicro c header files.

Really appreciate the work you guys are doing here. Library is great and a strong alternative to Tensorflow Lite Micro - arguably even better given how easy it is to load and update new weights. Since a lot of sensor data makes sense with time as a dimension, it begs the question though; is there any chance we are getting support for recurrent neural networks? More specifically GRUs and LSTMs.

Regards.

Hello,

While trying to compile AIfES on an STM32 Nucleo-64 board (STM32L476RG), I got the following error, after including the library in my project:

Description	Resource	Path	Location	Type
expected identifier or '(' before '=' token	ailoss_crossentropy_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/ailoss	line 28	C/C++ Problem
expected identifier or '(' before '=' token	ailoss_crossentropy_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/ailoss	line 52	C/C++ Problem
expected identifier or '(' before '=' token	aimath_f32_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/aimath	line 29	C/C++ Problem
expected identifier or '(' before '=' token	aimath_f32_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/aimath	line 30	C/C++ Problem
expected identifier or '(' before '=' token	aimath_q31_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/aimath	line 28	C/C++ Problem
expected identifier or '(' before '=' token	aimath_q31_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/aimath	line 29	C/C++ Problem
expected identifier or '(' before '=' token	aimath_q31_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/aimath	line 443	C/C++ Problem
expected identifier or '(' before '=' token	aimath_q7_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/aimath	line 28	C/C++ Problem
expected identifier or '(' before '=' token	aimath_q7_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/aimath	line 29	C/C++ Problem
expected identifier or '(' before '=' token	aimath_q7_default.c	/AIfES_TestBug/AIfES_for_Arduino/src/basic/default/aimath	line 30	C/C++ Problem
make: *** [AIfES_for_Arduino/src/basic/default/ailoss/subdir.mk:22: AIfES_for_Arduino/src/basic/default/ailoss/ailoss_crossentropy_default.o] Error 1	AIfES_TestBug		 	C/C++ Problem
make: *** [AIfES_for_Arduino/src/basic/default/aimath/subdir.mk:25: AIfES_for_Arduino/src/basic/default/aimath/aimath_f32_default.o] Error 1	AIfES_TestBug		 	C/C++ Problem
make: *** [AIfES_for_Arduino/src/basic/default/aimath/subdir.mk:25: AIfES_for_Arduino/src/basic/default/aimath/aimath_q31_default.o] Error 1	AIfES_TestBug		 	C/C++ Problem
make: *** [AIfES_for_Arduino/src/basic/default/aimath/subdir.mk:25: AIfES_for_Arduino/src/basic/default/aimath/aimath_q7_default.o] Error 1	AIfES_TestBug		 	C/C++ Problem
make: *** Waiting for unfinished jobs....	AIfES_TestBug		 	C/C++ Problem

Going back to the sources, I found that this is caused by an incomplete macro inside:

AIfES_for_Arduino/src/aifes_config.h
line 96:  #define AISTRING_STORAGE_WRAPPER(S) 

Replacing line 96 with:

#define AISTRING_STORAGE_WRAPPER(S)     const char S[]

seems to fix the problem (which occurs at line 29, 30 of "src/basic/default/aimath/aimath_f32_default.c").

we would like to try out the AIfES framework to evaluate the execution of a model built with Keras. Can BiDirectional network models from Keras be translated into an implementation that runs, for example, on a Portenta H7?

Hello, I would like to ask some questions, forgive my English is not good. When I was doing the linear regression training, the value of the Loss function appeared to be fixed at a certain value. For my case, it will always be 14.25. Of course, the trained model did not succeed, and the the predicted value of the model before training is also always 0. But after several failures, I accidentally touched the analog pin during setup(), and then the training was successful. The following is the log of my training model, one succeeded (random seed: 641), the other failed (random seed: 17) Training fail: training_fail.txt

Training success: training_success.txt

I think it should be the random seed that caused the initial model weight setting problem. Is my idea correct?

Hi I want to train a NN for the MNIST dataset on the PC. How can I implement a training of a NN with multiple output neurons. When I am editing the example (link) and change the output layer to 10 neurons the inference of the model stops with an error (Process returned -1073741819 (0xC0000005) execution time : 0.485 s) Are there any changes I need to be especially aware of?