I am new to tensorflow lite, and I have noticed that many examples are using static tflite::MicroMutableOpResolver < > micro_op_resolver;
So, my question is: how many layers can we add here when deploying the model? Or can the layers be exactly the same as described in the machine learning model? What if there are any layers that repeat?
As mentioned here: https://github.com/tensorflow/tflite-micro/blob/main/tensorflow/lite/micro/micro_mutable_op_resolver.h The Add* functions, as mentioned in the above link, add the various built-in operators to the MicroMutableOpResolver object. How can I add Conv1D and Maxpool1D to the main_functions.cc code? This is still not clear to me. What if my model contains a layer structure like this?
Conv1D Conv1D Dropout Dense Dropout Flatten Dense
Could you please explain that to me?
Also, would you mind sharing the detailed link or document for MicroMutableOpResolver?
Regards, Divya
