How to convert .pb to TFLite format?

Question

I downloaded a retrained_graph.pb and retrained_labels.txt file of a model I trained in Azure cognitive service. Now I want to make an Android app using that model and to do so I have to convert it to TFLite format. I used toco and I am getting the following error:

ValueError: Invalid tensors 'input' were found.

I am basically following this tutorial and have problem on step 4 and direcly copy pasted the terminal code: https://heartbeat.fritz.ai/neural-networks-on-mobile-devices-with-tensorflow-lite-a-tutorial-85b41f53230c

Answer 1

I am making a wild guess here, maybe you entered input_arrays=input. Which may not be true. Use this script to find the name of the input and output arrays of the frozen inference graph

import tensorflow as tf
gf = tf.GraphDef()   
m_file = open('frozen_inference_graph.pb','rb')
gf.ParseFromString(m_file.read())

with open('somefile.txt', 'a') as the_file:
    for n in gf.node:
        the_file.write(n.name+'\n')

file = open('somefile.txt','r')
data = file.readlines()
print "output name = "
print data[len(data)-1]

print "Input name = "
file.seek ( 0 )
print file.readline()

In my case they are:

output name: SemanticPredictions
input name: ImageTensor

Answer 2

You can use utility tflite_convert which is the part of tensorflow 1.10 (or higher) package.

The simple use for float inference is something like:

tflite_convert \
    --output_file=/tmp/retrained_graph.tflite \
    --graph_def_file=/tmp/retrained_graph.pb \
    --input_arrays=input \
    --output_arrays=output

Where input and output - are input and ouput tensors of your tensorflow graph