Convert TensorFlow Lite models to ONNX models
Project description
TFLITE2ONNX - Convert TensorFlow Lite models to ONNX
tflite2onnx
converts TensorFlow Lite (TFLite) models (*.tflite
) to ONNX models (*.onnx
),
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
*.pb
,SavedModel
or whatever) to ONNX, trytf2onnx
. Or, you can firstly convert it to a TFLite (*.tflite
) model, and then convert the TFLite model to ONNX.
Usage
Install via pip pip install tflite2onnx
.
After installation, you may either try either.
Python interface
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
test example.
Command line
tflite2onnx /path/to/original/tflite/model /path/to/save/converted/onnx/model
Contributing
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.
Resources
License
Apache License Version 2.0.
Project details
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