• .pb file is the format of tensorflow model

  • .tflite file is the format of tflite model, which usually used in mobile devices

before started

make sure you have installed these packages or tools

The best way to test is typing this code on your terminal

  • test flatbuffer

flatc --version 
# if you have installed flatbuffer correctly,you will see 
flatc version 2.0.0
  • test python packages

python # or whatever version you use

import tensorflow
import rich
import bidict


read .pb file

    with, 'rb') as f:
        graph_def = tf.compat.v1.GraphDef()

        for node in graph_def.node:
            res.add(node.op) # get node attr from subgraph

read .tflite file

construct base file

  • find .fbs file you can get the default fbs file

  • transfer fbs to python

    flatc --python your.fbs

then you get a folder full of .py, move it to your project ; in this project , you may need the ‘tflite’ folder

using flatbuffer on your code

example : read op from tflite model

open fbs file , find ‘root_type’, here is model .

  • get model

 with open(file, 'rb') as f:
    buf =
    model_inner = tflite.Model.Model.GetRootAs(buf, 0)
  • get subgraph

In the table Model , Subgraphs is a vector containing a few subgraphs . So when we get subgraph, must set the index of Subgraph

subgraph = model_inner.Subgraphs(0) # 0 is the index
  • get op

Here we need all ops to save, we must traverse the vector of op

op_length = subgraph.OperatorsLength()
for index in range(op_length):
    temp_code = subgraph.Operators(index).OpcodeIndex()


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