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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A tool for converting ONNX files to LiteRT/TFLite/TensorFlow, PyTorch native code (nn.Module), TorchScript (.pt), state_dict (.pt), Exported Program (.pt2), and Dynamo ONNX. It also supports direct conversion from LiteRT to PyTorch.
| Date | Stars |
|---|---|
| 2026-07-24 | 984 |
| 2026-07-25 | 984 |
| 2026-07-28 | 984 |
| 2026-07-30 | 984 |
| 2026-08-06 | 984 |
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growth rate 0.00%/day
# onnx2tf A tool for converting ONNX files to LiteRT/TFLite/TensorFlow, PyTorch native code (nn.Module), TorchScript (.pt), state_dict (.pt), Exported Program (.pt2), and Dynamo ONNX. It also supports direct conversion from LiteRT to PyTorch. You should use LiteRT Torch rather than onnx2tf. https://github.com/google-ai-edge/litert-torch and https://github.com/google-ai-edge/ai-edge-quantizer <p align="center"> <img src="https://user-images.githubusercontent.com/33194443/193840307-fa69eace-05a9-4d93-9c5d-999cf88af28e.png" /> </p> [](https://pepy.tech/project/onnx2tf)  [](https://img.shields.io/badge/Python-3.8-2BAF2B) [](https://pypi.org/project/onnx2tf/) [](https://github.com/PINTO0309/onnx2tf/actions?query=workflow%3ACodeQL)  [](https://doi.org/10.5281/zenodo.7230085) [](https://deepwiki.com/PINTO0309/onnx2tf) ## `tf_converter` supported layers - https://github.com/onnx/onnx/blob/main/docs/Operators.md - :heavy_check_mark:: Supported :white_check_mark:: Partial support **Help wanted**: Pull Request are welcome <details><summary>See the list of supported layers</summary><div> |OP|Status| |:-|:-:| |Abs|:heavy_check_mark:| |Acosh|:heavy_check_mark:| |Acos|:heavy_check_mark:| |Add|:heavy_check_mark:| |AffineGrid|:heavy_check_mark:| |And|:heavy_check_mark:| |ArgMax|:heavy_check_mark:| |ArgMin|:heavy_check_mark:| |Asinh|:heavy_check_mark:| |Asin|:heavy_check_mark:| |Atanh|:heavy_check_mark:| |Atan|:heavy_check_mark:| |Attention|:heavy_check_mark:| |AveragePool|:heavy_check_mark:| |BatchNormalization|:heavy_check_mark:| |Bernoulli|:heavy_check_mark:| |BitShift|:heavy_check_mark:| |BitwiseAnd|:heavy_check_mark:| |BitwiseNot|:heavy_check_mark:| |BitwiseOr|:heavy_check_mark:| |BitwiseXor|:heavy_check_mark:| |BlackmanWindow|:heavy_check_mark:| |Cast|:heavy_check_mark:| |Ceil|:heavy_check_mark:| |Celu|:heavy_check_mark:| |CenterCropPad|:heavy_check_mark:| |Clip|:heavy_check_mark:| |Col2Im|:white_check_mark:| |Compress|:heavy_check_mark:| |ConcatFromSequence|:heavy_check_mark:| |Concat|:heavy_check_mark:| |ConstantOfShape|:heavy_check_mark:| |Constant|:heavy_check_mark:| |Conv|:heavy_check_mark:| |ConvInteger|:white_check_mark:| |ConvTranspose|:heavy_check_mark:| |Cosh|:heavy_check_mark:| |Cos|:heavy_check_mark:| |CumProd|:heavy_check_mark:| |CumSum|:heavy_check_mark:| |DeformConv|:white_check_mark:| |DepthToSpace|:heavy_check_mark:| |Det|:heavy_check_mark:| |DequantizeLinear|:heavy_check_mark:| |DFT|:white_check_mark:| |Div|:heavy_check_mark:| |Dropout|:heavy_check_mark:| |DynamicQuantizeLinear|:heavy_check_mark:| |Einsum|:heavy_check_mark:| |Elu|:heavy_check_mark:| |Equal|:heavy_check_mark:| |Erf|:heavy_check_mark:| |Expand|:heavy_check_mark:| |Exp|:heavy_check_mark:| |EyeLike|:heavy_check_mark:| |Flatten|:heavy_check_mark:| |Floor|:heavy_check_mark:| |FusedConv|:heavy_check_mark:| |GatherElements|:heavy_check_mark:| |GatherND|:heavy_check_mark:| |Gather|:heavy_check_mark:| |Gelu|:heavy_check_mark:| |Gemm|:heavy_check_mark:| |GlobalAveragePool|:heavy_check_mark:| |GlobalLpPool|:heavy_check_mark:| |GlobalMaxPool|:heavy_check_mark:| |GreaterOrEqual|:heavy_check_mark:| |Greater|:heavy_check_mark:| |GridSample|:white_check_mark:| |GroupNormalization|:heavy_check_m
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:bd9c6f6fe46e74a0, topic:deep-learning, topic:pytorch, topic:tensorflow