tfmodel_parser

• .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

• python 3.*
• tensorflow 2.*
• flatbuffer
• rich
• bidict

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

start

read .pb file

    with tf.io.gfile.GFile(file, 'rb') as f:
        graph_def = tf.compat.v1.GraphDef()
        graph_def.ParseFromString(f.read())
        tf.compat.v1.import_graph_def(graph_def)

        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 here

• 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 = f.read()
    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()
    res.add(dic.inverse[temp_code])