Convert TensorFlow Lite models to ONNX models
TFLITE2ONNX - Convert TensorFlow Lite models to ONNX
tflite2onnx converts TensorFlow Lite (TFLite) models (
*.tflite) to ONNX models (
with data layout and quantization semantic properly handled (check the introduction blog for detail).
If you'd like to convert a TensorFlow model (frozen graph
SavedModelor whatever) to ONNX, try
tf2onnx. Or, you can firstly convert it to a TFLite (
*.tflite) model, and then convert the TFLite model to ONNX.
Install via pip
pip install tflite2onnx.
After installation, you may either try either.
import tflite2onnx tflite_path = '/path/to/original/tflite/model' onnx_path = '/path/to/save/converted/onnx/model' tflite2onnx.convert(tflite_path, onnx_path)
tflite2onnx now supports explicit layout, check the
tflite2onnx /path/to/original/tflite/model /path/to/save/converted/onnx/model
Any contribution is welcome to this tool.
- If you think something is wrong, report bugs.
- If some operators are not supported yet, you may request a new operator.
- It would be great if you can help to enable new operators, please join us with How to enable a new operator.
- Feel free to open discussions if you have any great idea to improve this tool.
Apache License Version 2.0.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Hashes for tflite2onnx-0.3.0-py3-none-any.whl