TFLite Segementation Fault by getting inputs and outputs with C++ - c++

Question

I'm trying to run an TfLite Model on a x86_64 system. It seems that all is working fine. But when I try to get the input or output tensor with typed_input_tensor(0) then I get a null pointer.
My model is a simple HelloWorldNN:
import tensorflow as tf
import numpy as np
from tensorflow import keras
model = tf.keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])])
model.compile(optimizer='sgd', loss='mean_squared_error')
xs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)
ys = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)
model.fit(xs, ys, epochs=10)
print(model.predict([10.0]))
model.summary()
converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
open("linear.tflite","wb").write(tflite_model)
For the C++ part I cloned the tensorflow git and checked out the commit d855adfc5a0195788bf5f92c3c7352e638aa1109. This is the commit which is neccessary to using Coral hardware which I plan to use. I build the tensorflow-lite.a and linked it to my application.
std::unique_ptr<tflite::FlatBufferModel> model =
tflite::FlatBufferModel::BuildFromFile("linear.tflite");
if (tflite::InterpreterBuilder(*model, resolver)(&interpreter) != kTfLiteOk) {
std::cerr << "Failed to build interpreter." << std::endl;
}
if (interpreter->AllocateTensors() != kTfLiteOk) {
std::cerr << "Failed to allocate tensors." << std::endl;
}
std::cout << "Number of tensors" << interpreter->tensors_size() <<" Num of Inputs "<<
tflite::PrintInterpreterState(interpreter.get());
float* input = interpreter->typed_input_tensor<float>(0);
interpreter->Invoke();
float* output = interpreter->typed_output_tensor<float>(0);
If I run the code then both input and output pointers are null pointers. The output of interpreter.get() is the follow:
Number of tensors8 Num of Inputs 18446732345621392436
Interpreter has 8 tensors and 3 nodes
Inputs: 4
Outputs: 5
Tensor 0 dense/BiasAdd_int8 kTfLiteInt8 kTfLiteArenaRw 1 bytes ( 0.0 MB) 1 1
Tensor 1 dense/MatMul_bias kTfLiteInt32 kTfLiteMmapRo 4 bytes ( 0.0 MB) 1
Tensor 2 dense/kernel/transpose kTfLiteInt8 kTfLiteMmapRo 1 bytes ( 0.0 MB) 1 1
Tensor 3 dense_input_int8 kTfLiteInt8 kTfLiteArenaRw 1 bytes ( 0.0 MB) 1 1
Tensor 4 dense_input kTfLiteFloat32 kTfLiteArenaRw 4 bytes ( 0.0 MB) 1 1
Tensor 5 dense/BiasAdd kTfLiteFloat32 kTfLiteArenaRw 4 bytes ( 0.0 MB) 1 1
Tensor 6 (null) kTfLiteNoType kTfLiteMemNone 0 bytes ( 0.0 MB) (null)
Tensor 7 (null) kTfLiteNoType kTfLiteMemNone 0 bytes ( 0.0 MB) (null)
Node 0 Operator Builtin Code 114 QUANTIZE
Inputs: 4
Outputs: 3
Node 1 Operator Builtin Code 9 FULLY_CONNECTED
Inputs: 3 2 1
Outputs: 0
Node 2 Operator Builtin Code 6 DEQUANTIZE
Inputs: 0
Outputs: 5`
I've no idea where is my mistake. It worked with tensorflow 1.15. But 1.15 I can't use anymore with Coral hardware. I would be grateful for any help

Answer 1

Ok, I found my problem. I hadn't updated the include files. The files were still from 1.15. :-)