undefined reference to `DebugLog' in micro_error_reporter.cpp

[pv-98]

I am working with Arduino_TensorFlowLite-2.4.0-ALPHA-precompiled library and trying to compile my arduino sketch. But I keep getting this error Library Arduino_TensorFlowLite has been declared precompiled: Using precompiled library in C:\Users\prane\Documents\Arduino\libraries\Arduino_TensorFlowLite-2.4.0-ALPHA-precompiled\src\cortex-m4\fpv4-sp-d16-softfp C:\Users\prane\Documents\Arduino\libraries\Arduino_TensorFlowLite-2.4.0-ALPHA-precompiled\src\cortex-m4\fpv4-sp-d16-softfp\libtensorflowlite.a(micro_error_reporter.cpp.o): In functiontflite::MicroErrorReporter::Report(char const*, std::__va_list)': /home/arduino/workspace/Libraries-Google-Tensorflow-scraper/Arduino/libraries/tensorflow_lite_mirror/src/tensorflow/lite/micro/micro_error_reporter.cpp:35: undefined reference to DebugLog' /home/arduino/workspace/Libraries-Google-Tensorflow-scraper/Arduino/libraries/tensorflow_lite_mirror/src/tensorflow/lite/micro/micro_error_reporter.cpp:36: undefined reference toDebugLog' collect2.exe: error: ld returned 1 exit status

exit status 1

Compilation error: exit status 1`

I've included my sketch below. Any help would be greatly helpful. Thanks

`#include "TensorFlowLite.h"

include "tensorflow/lite/micro/all_ops_resolver.h"

include "tensorflow/lite/micro/micro_error_reporter.h"

include "tensorflow/lite/micro/micro_interpreter.h"

//#include "tensorflow/lite/micro/system_setup.h"

include "tensorflow/lite/schema/schema_generated.h"

include "tensorflow/lite/version.h"

include "image_data.h"

include "model_data.h"

const int kInputTensorSize = 1 28 28 1; const int kNumClasses = 10; namespace{ tflite::ErrorReporter error_reporter = nullptr; const tflite::Model model = nullptr; tflite::MicroInterpreter interpreter = nullptr; TfLiteTensor input = nullptr; TfLiteTensor output = nullptr; int inference_count = 0;

constexpr int kTensorArenaSize = 2*1024; uint8_t tensor_arena[kTensorArenaSize]; }

void setup() { Serial.begin(115200); // tflite::InitializeTarget(); // memset(tensor_arena, 0, kTensorArenaSize*sizeof(uint8_t));

// Set up logging. static tflite::MicroErrorReporter micro_error_reporter; error_reporter = µ_error_reporter;

model = tflite::GetModel(model_data); if (model->version() != TFLITE_SCHEMA_VERSION) { Serial.println("Model provided is schema version "

• String(model->version()) + " not equal "
• "to supported version "

• String(TFLITE_SCHEMA_VERSION)); return; } else { Serial.println("Model version: " + String(model->version())); }

  // This pulls in all the operation implementations we need. static tflite::AllOpsResolver resolver;

  // Build an interpreter to run the model with. static tflite::MicroInterpreter static_interpreter( model, resolver, tensor_arena, kTensorArenaSize, error_reporter); interpreter = &static_interpreter;

  // Build an interpreter to run the model with. // tflite::MicroInterpreter* static_interpreter_ptr = new tflite::MicroInterpreter( // model, resolver, tensor_arena, kTensorArenaSize, error_reporter); // interpreter = static_interpreter_ptr;

  // Allocate memory from the tensor_arena for the model's tensors. TfLiteStatus allocate_status = interpreter->AllocateTensors(); if (allocate_status != kTfLiteOk) { Serial.println("AllocateTensors() failed"); return; } else { Serial.println("AllocateTensor() Success"); }

  size_t used_size = interpreter->arena_used_bytes(); Serial.println("Area used bytes: " + String(used_size)); input = interpreter->input(0); output = interpreter->output(0);

  / check input / if (input->type != kTfLiteFloat32) { Serial.println("input type mismatch. expected input type is float32"); return; } else { Serial.println("input type is float32"); }

  Serial.println("Model input:"); Serial.println("input->type: " + String(input->type)); Serial.println("dims->size: " + String(input->dims->size)); for (int n = 0; n < input->dims->size; ++n) { Serial.println("dims->data[n]: " + String(input->dims->data[n])); }

  Serial.println("Model output:"); Serial.println("dims->size: " + String(output->dims->size)); for (int n = 0; n < output->dims->size; ++n) { Serial.println("dims->data[n]: " + String(output->dims->data[n])); }

} void loop() {

// Define the input image array const uint8_t kImageDataPtr = kImageData; // Pointer to start of image data uint8_t input_image[kInputTensorSize]; for (int i = 0; i < kInputTensorSize; i++) { input_image[i] = (kImageDataPtr++); }

for(int i=0; i<kInputTensorSize; i++){ input->data.f[i] = (float)input_image[i] / 255.0; }

// Run inference interpreter->Invoke();

// Print the predicted class int predicted_class = -1; float max_score = -1; for (int i = 0; i < kNumClasses; i++) { float score = output->data.f[i]; if (score > max_score) { predicted_class = i; max_score = score; } } Serial.println(predicted_class);

}`

[HCzou]

I met the same error report, not solved yet...

[istvanzk]

I get the same error when using micro_log (MicroPrintf) instead of micro_error_reporter (MicroErrorReporter), with TensorFlow 2.15:

tensorflow/lite/micro/micro_log.cpp:31: undefined reference to `DebugLog'

[istvanzk]

The problem comes from the Arduino_TensorFlowLite library which is quite outdated compared to the newest TFLM features.

The DeBugLog is defined in tensorflow/lite/micro/system_setup.cpp as:

extern "C" void DebugLog(const char* s) { DEBUG_SERIAL_OBJECT.print(s); }

but is declared in tensorflow/lite/micro/debug_log.h as:

void DebugLog(const char* format, va_list args);

and used in tensorflow/lite/micro/micro_log.cpp as:

DebugLog(format, args);

The implementation in tensorflow/lite/micro/system_setup.cpp seems to be wrong although adding the va_list args as argument does not solve the undefined reference error.

[istvanzk]

I found a solution, although not fully tested yet, my version of micro_speech.ino compiles now without errors, just with many warnings. I hope this will help others trying to solve this error. The problem comes from the Arduino_TensorFlowLite library which is quite outdated compared to the newest TFLM features.

In system_setup.cpp, my first problem and reason for the undefined reference to 'DebugLog' error was due to the lines:

#if defined(ARDUINO) && !defined(ARDUINO_ARDUINO_NANO33BLE) && 
#define ARDUINO_EXCLUDE_CODE
#endif  // defined(ARDUINO) && !defined(ARDUINO_ARDUINO_NANO33BLE)

the ARDUINO_EXCLUDE_CODE was defined and all the rest of the code was not used.

After correcting the above to make sure ARDUINO_EXCLUDE_CODE is not defined:

• First, I have modified the code to have:

  extern "C" void DebugLog(const char* s, va_list args) { DEBUG_SERIAL_OBJECT.print(s); }

  to match the declaration in tensorflow/lite/micro/debug_log.h

• Second, I have added explicit include for the header file where the RingBufferN is defined. Without this I was getting the error about ... error: expected template-name before '<' token.

  #include <api/RingBuffer.h>

  right after the line:

  #include <Arduino.h>