I have trained a DS-CNN model with the same hyperparameters available in the guide. I have also done the fusion of batch normalization layers and after this I have tried to quantize weights and biases with the following command
I read in the guide that the value of act_max that I used, quantizes only the first layer (input layer) and not other layers. Has anyone experienced a good hyperparameters configuration to get a net suitable for Small class? I need a model that runs on a microcontroller with 128 KB of RAM, with an high accuracy.
I have trained a DS-CNN model with the same hyperparameters available in the guide. I have also done the fusion of batch normalization layers and after this I have tried to quantize weights and biases with the following command
I read in the guide that the value of act_max that I used, quantizes only the first layer (input layer) and not other layers. Has anyone experienced a good hyperparameters configuration to get a net suitable for Small class? I need a model that runs on a microcontroller with 128 KB of RAM, with an high accuracy.