Tensorflow lite example of fibonacci

tflfib.py

import numpy as np
import tensorflow as tf
import tflite_runtime.interpreter as tflite

# Fib function

@tf.function
def fibonacci(n):
    a = 0
    b = 1
    i = 0

    def cond(i, a, b):
        return i < 10

    def body(i, a, b):
        return (i + 1, b, a + b)

    i, a, b = tf.while_loop(
            cond = cond,
            body = body,
            loop_vars = (i,a,b))
    return b

# Convert to tflite
 
converter = tf.lite.TFLiteConverter.from_concrete_functions([
    fibonacci.get_concrete_function(n=tf.TensorSpec((), tf.int32))])
tflite_model = converter.convert()

with open('converted_model.tflite', 'wb') as f:
  f.write(tflite_model)

# Load the TFLite model and allocate tensors.
interpreter = tf.lite.Interpreter(model_path='converted_model.tflite')
interpreter.allocate_tensors()

input_details = interpreter.get_input_details()
#       [{'name': 'n',
#         'index': 0,
#         'shape': array([], dtype=int32),
#         'shape_signature': array([], dtype=int32),
#         'dtype': numpy.int32,
#         'quantization': (0.0, 0),
#         'quantization_parameters': {'scales': array([], dtype=float32),
#          'zero_points': array([], dtype=int32),
#          'quantized_dimension': 0},
#         'sparsity_parameters': {}}]

output_details = interpreter.get_output_details()
#       [{'name': 'Identity',
#         'index': 6,
#         'shape': array([], dtype=int32),
#         'shape_signature': array([], dtype=int32),
#         'dtype': numpy.int32,
#         'quantization': (0.0, 0),
#         'quantization_parameters': {'scales': array([], dtype=float32),
#          'zero_points': array([], dtype=int32),
#          'quantized_dimension': 0},
#         'sparsity_parameters': {}}]

def tflfib(n):
    input_data = np.int32(n)
    interpreter.set_tensor(input_details[0]['index'], input_data)
    interpreter.invoke()
    output_data = interpreter.get_tensor(output_details[0]['index'])
    return output_data

tfllib_simple.py

import numpy as np
import tensorflow as tf

@tf.function(input_signature=(tf.TensorSpec(shape=(), dtype=tf.int32),))
def fibonacci(n: np.int32):
    a, b = 0, 1
    for i in range(n):
        a, b = b, a + b
    return b

tflite_model = tf.lite.TFLiteConverter.from_concrete_functions([fibonacci.get_concrete_function()]).convert()

interpreter = tf.lite.Interpreter(model_content=tflite_model)
interpreter.allocate_tensors()

input_idx  = interpreter.get_input_details()[0]['index']
output_idx = interpreter.get_output_details()[0]['index']

def tflfib(n):
    interpreter.set_tensor(input_idx, np.int32(n))
    interpreter.invoke()
    output_data = interpreter.get_tensor(output_idx)
    return output_data

for i in range(10):
    print(tflfib(i))

In [*]: for i in range(10):
    ...:     print(f'{i: 4d} {tflfib(i)}')
    ...:
   0 1
   1 1
   2 2
   3 3
   4 5
   5 8
   6 13
   7 21
   8 34
   9 55