netron
onnx-tensorflow
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netron | onnx-tensorflow | |
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32 | 6 | |
26,040 | 1,234 | |
- | 1.0% | |
9.9 | 0.0 | |
7 days ago | 29 days ago | |
JavaScript | Python | |
MIT License | GNU General Public License v3.0 or later |
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netron
- Visualizer for neural network, deep learning and machine learning models
- Netron: Visualizer for Machine Learning Models
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
In exploring open-source projects, I've come across several promising tools capable of managing deep-learning models for images. Significantly, tools such as NETRON provide visualization of neural networks, while SHAP can be used for evaluating the significance of outputs.
- Netron is a viewer for neural network, deep learning and machine learning models
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Operationalize TensorFlow Models With ML.NET
We need to find out the exact input and output tensor names. A tool like Netron makes this super easy. Open the original .tflite and/or the ONNX model in Netron and click the Model Properties button in the lower left corner.
- Netron: A viewer for neural network, deep learning and machine learning models
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Visualize PyTorch Models with NNViz
How is this different from e.g Netron https://github.com/lutzroeder/netron
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[P]Visualizing a neural network.
Netron (https://netron.app/) is the best and mostly used NN visualizer. Just save your model and then simply load it via netron to look its layers and weights. If you want a more complex visualization then you can also play with Zetane ( but its paid, also have a free version) engine.
- How do I visualize this NN Architecture?
- FLaNK Stack for 15 May 2023
onnx-tensorflow
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How to Solve "BackendIsNotSupposedToImplementIt: Unsqueeze version 13 is not implemented."?
How to solve this? I found below github issue which they solved i think, but im not to able to find the solution https://github.com/onnx/onnx-tensorflow/pull/1022
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[D] Library to transfer PyTorch to TF
Okay, maybe it worked some years ago. The issue currently is that the trainable weights get lost...which is by design https://github.com/onnx/onnx-tensorflow/issues/1002
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Has anyone successfully converted an onnx model to tensorflow? Here's the problems I'm having...
TLDR: I'm using onnx-tf to convert an onnx model to tensorflow. During the conversion I lose important information such as inputs, outputs and the names of operators. Please read on if you have experience with this library or you've experienced similar issues. :)
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Portability of Rust in 2021
We had a few small issues with ONNX. Export worked but when running with e.g. tflite stumbled for example across this https://github.com/onnx/onnx-tensorflow/issues/853 Also the support for sampling from distributions is generally still pretty weak, but we were able to work around that.
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[D] How to reduce latency of DL models
https://pytorch.org/tutorials/advanced/super\_resolution\_with\_onnxruntime.html https://github.com/onnx/onnx-tensorflow
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Possible to retrain onnx model?
https://github.com/onnx/onnx-tensorflow Haven’t tried it, let me know if it works.
What are some alternatives?
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onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
tokenizers - 💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
models - Models and examples built with TensorFlow
guesslang - Detect the programming language of a source code
pwnagotchi - (⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.
PlotNeuralNet - Latex code for making neural networks diagrams
pytorch2keras - PyTorch to Keras model convertor
Synaptic.js - architecture-free neural network library for node.js and the browser
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x