tf_lite_simple_model.py

import numpy as np
import tensorflow as tf

# manually put back imported modules - bug?
import tempfile
import subprocess
tf.contrib.lite.tempfile = tempfile
tf.contrib.lite.subprocess = subprocess

with tf.name_scope("inputs"):
    X = tf.placeholder(tf.float32, [2], name="X-input")

with tf.name_scope("outputs"):
    Y = tf.add(X[0], X[1], name="Y-output")

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())

    tflite_model = tf.contrib.lite.toco_convert(sess.graph_def, [X], [Y])
    with open('fm.lite', "wb") as f:
        f.write(tflite_model)

I'm getting java.lang.IllegalArgumentException: Invalid handle to Interpreter. when trying to use fm.lite in android app.

Android code:

void run(MappedByteBuffer byteBuffer) {
        Interpreter interpreter = new Interpreter(byteBuffer);
        float[] input = new float[]{1.0f, 1.0f};
        float output = 0.0f;
        interpreter.run(input, output);
        Log.e("TAG", "OUTPUT: " + output);
}

It's working properly with some samples found in github (after altering input/output size).

I also tried to freeze graph, save it as pb and then convert with toco:
toco --input_file=frozen_model.pb --input_format=TENSORFLOW_GRAPHDEF --output_format=TFLITE --output_file=frozen_model.lite --inference_type=FLOAT --input_arrays=inputs/X-input --output_arrays=outputs/Y-output --input_shapes=2 --output_shapes=1
Unfortunately same error is thrown.