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Tensorflow-lite Model to TNN Nodel

中文版本

To convert Tensorflow-lite model file to TNN, you need to use the corresponding tool to convert from the original format to TNN model.

The Tensorflow-lite model can directly convert to an TNN model. The following document will briefly introduce how to use tflite2tnn to convert.

1. Environment requirements and Compile

Environment requirements

The following environment is suitable for Macos and Linux systems. The example is based on centos7.2.

-Install protobuf (version >= 3.4.0)

Macos:

brew install protobuf

Linux:

For linux systems, we recommend to refer to the official README document of protobuf and install directly from the source code.

If you are using Ubuntu system, you can use the following instructions to install:

sudo apt-get install libprotobuf-dev protobuf-compiler
  • Install python (version >= 3.6)

Macos

brew install python3

Centos:

yum install  python3 python3-devel
  • Install python dependencies numpy>=1.17.0
    protobuf>=3.4.0
pip3 install numpy protobuf
  • cmake （version >= 3.0） Download the latest cmake from official website, and follow the instructions. It is recommended to use the latest cmake.

Compile

The tflite2tnn tool runs directly on Mac and Linux with automatic compilation scripts

cd <path-to-tnn>/tools/convert2tnn
./build.sh

2. How to use tflite2tnn

Check the tool help information

python3 converter.py tflite2tnn  -h

help information shows as follow:

usage: converter.py tflite2tnn [-h] tflitemodel_path [-version VERSION] [-o OUTPUT_DIR]

optional arguments:
  -h, --help              show this help message and exit
  -version VERSION        Algorithm version string
  -o OUTPUT_DIR           the output dir for tnn model
  -align                  align the onnx model with tnn model
  -input_file INPUT_FILE  the input file path which contains the input data for the inference model
  -ref_file   REF_FILE    the reference file path which contains the reference data to compare the results

python3 converter.py tflite2tnn  test.tflite
Parameter:
-version
Version information

-o
output_dir : The directory the model to be saved in，the directory must exit already.

-align
model align, if you want to use it, you can add '-align' in your command

-input_file
input_file : The path of input file, which will be used in model align

-ref_file
reference_file : The path of reference file, which will be used in model align. Compare tnn's output and reference file.

3. Operator support and usage restrictions

List of operators supported by the tool: tflite support list