How to give multi-dimensional inputs to tflite via C++ API

Question

I am trying out tflite C++ API for running a model that I built. I converted the model to tflite format by following snippet:

import tensorflow as tf
converter = tf.lite.TFLiteConverter.from_keras_model_file('model.h5') 
tfmodel = converter.convert() 
open("model.tflite", "wb").write(tfmodel)

I am following the steps provided at tflite official guide, and my code upto this point looks like this

// Load the model
std::unique_ptr<tflite::FlatBufferModel> model = tflite::FlatBufferModel::BuildFromFile("model.tflite");

// Build the interpreter
tflite::ops::builtin::BuiltinOpResolver resolver;
std::unique_ptr<tflite::Interpreter> interpreter;

tflite::InterpreterBuilder builder(*model, resolver);
builder(&interpreter);
interpreter->AllocateTensors();

// Check interpreter state
tflite::PrintInterpreterState(_interpreter.get());

This shows my input layer has a shape of (1, 2050, 6). For giving input from C++, I followed this thread, and my input code looks like this:

std::vector<std::vector<double>> tensor;     // I filled this vector, (dims are 2050, 6)

int input = interpreter->inputs()[0];
float* input_data_ptr = interpreter->typed_input_tensor<float>(input);
for (int i = 0; i < 2050; ++i) {
    for (int j = 0; j < 6; j++) {
        *(input_data_ptr) = (float)tensor[i][j];
        input_data_ptr++;
    }
}

Last layer of this model returns a single floating point(a probability). I get output from following code.

interpreter->Invoke();
int output_idx = interpreter->outputs()[0];
float* output = interpreter->typed_output_tensor<float>(output_idx);
std::cout << "OUTPUT: " << *output << std::endl;

My problem is that I am getting same output for different inputs. Moreover, the outputs are not matching with tensorflow-python outputs.

I don't understand why it's behaving this way. Also, can anyone confirm if this is the right way to give inputs to the model?

Some extra information:

1. I built tflite from source, v1.14.0, using command: bazel build -c opt //tensorflow/contrib/lite:libtensorflowLite.so --cxxopt="-std=c++11" --verbose_failures

2. I trained my model and converted it to tflite on a different machine, with tensorflow v2.0

Answer 1

This is wrong API usage.

Changing typed_input_tensor to typed_tensor and typed_output_tensor to typed_tensor resolved the issue for me.

For anyone else having the same issue,

int input_tensor_idx = 0;
int input = interpreter->inputs()[input_tensor_idx];
float* input_data_ptr = interpreter->typed_input_tensor<float>(input_tensor_idx);

and

int input_tensor_idx = 0;
int input = interpreter->inputs()[input_tensor_idx];
float* input_data_ptr = interpreter->typed_tensor<float>(input);

are identical.

This can be verified by looking at implementation of typed_input_tensor.

  template <class T>
  T* typed_input_tensor(int index) {
    return typed_tensor<T>(inputs()[index]);
  }