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b08-rpc-m4-hello-world-sine.ino
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/*
* my02g-analogRead-m4-rpc.ino for the Portenta H7
*
* The PortentaH7 M4 core can not print to the serial monitor
* On the M4 core if you do a Serial.Println it goes to the TX RX UART output pins
* This program uses RPC to redirect Serial.println to the M7 core
* so that regular sketches still work with serial monitor output from the M4 core
*
*
* updated August 2nd, 2020
* by Jeremy Ellis
* Twitter @rocksetta
* Website https://www.rocksetta.com
*
*I have re-written this to make larger programs easier
*by seperating the M7 and M4 code completely.
*
*/
#include "RPC_internal.h" // comes with the mbed board installation, see note above
#ifdef CORE_CM7 // Start M7 programming
void setup() {
bootM4();
Serial.begin(115200);
RPC1.begin();
}
void loop() {
// Serial.println("Hello from M7 regular Serial");
while (RPC1.available()) {
Serial.write(RPC1.read());
}
// delay(1);
}
#endif // End all M7 core programming
/////////////////////////////////////////////////////////////////////////////////////////////
#ifdef CORE_CM4 // Start M4 programming
/*
* b01_makerML_hello_world.ino
* simplifying TensorflowLite Micro Machine Learning for all makers
*
*
*
* By Jeremy Ellis
* Twitter @rocksetta
* Website https://rocksetta.com
* created Aug 20th, 2020
* Github https://github.com/hpssjellis/my-examples-for-the-arduino-portentaH7/tree/master/m09-Tensoflow
*
*
* Hashtags
* #TensorflowLiteMicro
* #TensorflowLiteForArduino
* #TinyMY
* #MakerML
*/
// By putting this model.h file here we can load everything as one file into the arduino IDER.
// Once it is working it is best to seperate this as a model.h file into it's own tabThis allows only one file for Arduino IDE, but you should seperate the following
// #include "model.h" // uncomment when below has been put into it's own tab
/////////////////////////////////// cut and paste to model.h tab /////////////////////////////////////////////////////////////////
#pragma once
const unsigned char model_tflite[] = {
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};
unsigned int model_tflite_len = 2640;
//////////////////////////////////// end cut and paste to model.h tab ///////////////////////////////////////////////////////////////
#include "Arduino.h"
//#include <TensorFlowLite.h>
#include <RocksettaTensorFlowLite.h>
/*================= Start Advanced Area ===============================*/
#include "tensorflow/lite/micro/all_ops_resolver.h"
//#include "tensorflow/lite/micro/kernels/micro_ops.h"
//#include "tensorflow/lite/micro/micro_mutable_op_resolver.h"
#include "tensorflow/lite/micro/micro_error_reporter.h" // may have issues on M4 core
#include "tensorflow/lite/micro/micro_interpreter.h"
#include "tensorflow/lite/schema/schema_generated.h"
#include "tensorflow/lite/version.h"
#include "tensorflow/lite/c/common.h"
//#include "tensorflow/lite/c/c_api.h" // has interesting funcitons, not in main library
// Start Debug.cc information ----------------------------------------------------------
#if defined (CORE_CM7) || defined (CORE_CM4) || defined (TEENSYDUINO) || defined (ARDUINO_NANO33BLE) || defined (YOUR_BOARD1) // CORE_CM7 is for the PortentaH7 outer core
// do abosolutely nothing the default works
// Note: NANO_33_BLE deprecated as MBED of 1.30, new name: ARDUINO_NANO33BLE
// Note: CORE_CM4 MBED of 1.30, moved above
#elif defined (NANO_33_BLE) || defined (YOUR_BOARD2) // CORE_CM4 is for the PortentaH7 inner core
#define DEBUG_SERIAL_OBJECT (Serial)
extern "C" void DebugLog(const char* s) {
static bool is_initialized = false;
if (!is_initialized) {
DEBUG_SERIAL_OBJECT.begin(9600);
is_initialized = true;
}
DEBUG_SERIAL_OBJECT.print(s);
}
#elif defined (__SAM3X8E__) || defined (YOUR_BOARD3) // Arduino UNO style boards
#define DEBUG_SERIAL_OBJECT (SerialUSB)
extern "C" void DebugLog(const char* s) {
static bool is_initialized = false;
if (!is_initialized) {
DEBUG_SERIAL_OBJECT.begin(9600);
is_initialized = true;
}
DEBUG_SERIAL_OBJECT.print(s);
}
#elif defined (SEEED_XIAO_M0) || defined (YOUR_BOARD4) // The new $5 USD Seeeduino XIAO board
#define CFG_TUSB_DEBUG
#else
// don't do any debugging until you figure out your board
extern "C" void DebugLog(const char* s) {
// Do not log debug info
}
#endif
/*
* nano_33_iot.build.board=SAMD_NANO_33_IOT // have not got it working yet
*
*/
// End Debug.cc information ----------------------------------------------------------
namespace { // Start namespace----------------------------------------------------------
// define needed variables
tflite::ErrorReporter* error_reporter = nullptr;
const tflite::Model* model = nullptr;
tflite::MicroInterpreter* interpreter = nullptr;
TfLiteTensor* input = nullptr;
TfLiteTensor* output = nullptr;
// Create an area of memory to use for input, output, and intermediate arrays.
constexpr int kTensorArenaSize = 2 * 1024; // I like 20 * 1024;
uint8_t tensor_arena[kTensorArenaSize];
} // END namespace----------------------------------------------------------
/*================= End Advanced Area ===============================*/
/*================= Start Smart Area ================================*/
void modelSetup(const unsigned char theModel[]){
// NOLINTNEXTLINE(runtime-global-variables)
static tflite::MicroErrorReporter micro_error_reporter;
error_reporter = µ_error_reporter;
// Map the model into a usable data structure. This doesn't involve any
// copying or parsing, it's a very lightweight operation.
model = tflite::GetModel(theModel); // name from the tflite converter model.h file
if (model->version() != TFLITE_SCHEMA_VERSION) {
TF_LITE_REPORT_ERROR(error_reporter,
"Model provided is schema version %d not equal "
"to supported version %d.",
model->version(), TFLITE_SCHEMA_VERSION);
return;
}
// This pulls in all the operation implementations we need.
// NOLINTNEXTLINE(runtime-global-variables)
static tflite::AllOpsResolver resolver;
/* // replace the above line if you know each operation to save space
static tflite::MicroMutableOpResolver<5> micro_op_resolver; // NOLINT
micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_DEPTHWISE_CONV_2D,tflite::ops::micro::Register_DEPTHWISE_CONV_2D() );
micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_MAX_POOL_2D,tflite::ops::micro::Register_MAX_POOL_2D() );
micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_CONV_2D,tflite::ops::micro::Register_CONV_2D() );
micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_FULLY_CONNECTED,tflite::ops::micro::Register_FULLY_CONNECTED() );
micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_SOFTMAX,tflite::ops::micro::Register_SOFTMAX() );
*
*/
// Build an interpreter to run the model with.
static tflite::MicroInterpreter static_interpreter(model, resolver, tensor_arena, kTensorArenaSize, error_reporter);
interpreter = &static_interpreter;
// Allocate memory from the tensor_arena for the model's tensors.
TfLiteStatus allocate_status = interpreter->AllocateTensors();
if (allocate_status != kTfLiteOk) {
TF_LITE_REPORT_ERROR(error_reporter, "AllocateTensors() failed");
return;
}
// Obtain pointers to the model's input and output tensors.
input = interpreter->input(0);
output = interpreter->output(0);
}
float modelPredict(float myInput){ // like tensorflowJS const myPredictArray = await model.predict(xTrainingData).data()
input->data.f[0] = myInput; // may have to edit this
// Run inference, and report any error
TfLiteStatus invoke_status = interpreter->Invoke();
// if (invoke_status != kTfLiteOk) {
// Serial.print("Error with input: " + String(myInput));
// }
return output->data.f[0]; // may have to edit this
}
/*================= End Smart Area ======================================*/
/*================= Start Maker Area ======================================*/
#define Serial RPC1 // So the M4 regular serial prints to RPC
int myCounter = 0;
int myLed = LED_BUILTIN; //or 7 or 5 or LED_BUILTIN or LEDB
void setup() {
Serial.begin();
pinMode(myLed, OUTPUT);
modelSetup(model_tflite); // name of the model in the tab model.h
}
void loop() {
myCounter +=1;
if (myCounter >= 360){
myCounter = 0;
}
float x_val = myCounter * 3.14/180; // degrees to radians
float y_val = sin(x_val);
// This uses your model to make a prediction
float predicted = modelPredict(x_val);
Serial.println("sin(" +String(x_val)+ ") = " + String(y_val) + "\t predicted: " + String(predicted) );
// y=1 LED is fully on. The LED's brightness can range from 0-255.
int brightness = (int)(127.5f * (predicted+1));
#if defined (CORE_CM7) || defined (CORE_CM4)
if (brightness <= 128){
digitalWrite(myLed, HIGH); // means off
} else {
digitalWrite(myLed, LOW); // means on
}
#else
analogWrite(myLed, brightness); // not on Porttenta
#endif
delay(3); // slows the process down a bit to see the sine wave
}
/*================= End Maker Area ======================================*/
#endif // End all M4 core programming