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PINTO0309/onnx2tf ★ 996 106 APPLICATION

onnx2tf is a production-ready ONNX to TensorFlow/TFLite conversion framework that employs a sophisticated pass-based optimization pipeline. The system converts ONNX models through preprocessing, lowering to an intermediate representation (ModelIR), applying 50+ optimization passes (layout transformation, operator fusion, quantization), and exporting to target formats including TFLite, SavedModel, PyTorch nn.Module, and TorchScript. Its architecture features clean separation between operator implementations, IR transformation passes, and backend-specific exporters, with the flatbuffer_direct backend providing 100x+ faster conversion by bypassing TensorFlow graph construction. The framework includes comprehensive accuracy validation tools, dynamic shape handling, and model surgery capabilities for intermediate layer extraction.

RATING: 8.8/10 MAINT: active DRIFT: low
#onnx-conversion #tflite-optimization #layout-optimization #operator-fusion #quantization-aware #cross-framework #pass-based-optimization #edge-deployment #deep-learning #machine-learning #model-converter #models #onnx #tensorflow #tensorflow-lite #tflite #docker #tfjs #android #quantization #keras #transformer #coreml #lstm #litert #pytorch #torchscript
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