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onnx / onnx

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ONNX checker doesn't check repeated permutation for Transpose operator

1
GuanLuo
GuanLuo commented Sep 9, 2021

Bug Report

Is the issue related to model conversion?

If the ONNX checker reports issues with this model then this is most probably related to the converter used to convert the original framework model to ONNX. Please create this bug in the appropriate converter's GitHub repo (pytorch, tensorflow-onnx, sklearn-onnx, keras-onnx, onnxmltools) to get the best help.

Describe the bug

T

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bug good first issue shape inference onnx checker
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666DZY666 / micronet

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micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

pytorch pruning convolutional-networks quantization xnor-net tensorrt model-compression bnn neuromorphic-computing group-convolution onnx network-in-network tensorrt-int8-python dorefa twn network-slimming integer-arithmetic-only quantization-aware-training post-training-quantization batch-normalization-fuse
  • Updated Oct 6, 2021
  • Python
AdvBox

advboxes / AdvBox

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Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

security machine-learning deep-learning paddlepaddle adversarial-example adversarial-examples onnx fgsm adversarial-attacks deepfool graphpipe
  • Updated Sep 8, 2021
  • Jupyter Notebook

PINTO0309 / PINTO_model_zoo

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A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]

caffe computer-vision model-zoo tensorflow model models keras pytorch pretrained-models coreml onnx tensorflow-lite tflite tensorflowjs tfjs openvino edgetpu mediapipe tflite-models tf-trt
  • Updated Oct 5, 2021
  • Python

onnx / onnx-tensorflow

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Tensors in list passed to 'values' of 'ConcatV2' Op have types [float64, int64, int64, int64, int64] that don't all match.

6
ansh1204
ansh1204 commented Apr 27, 2020

I am trying to convert a custom pytorch model to tensorflow, I am abe to convert pytorch to onnx but converting onnx to tensorflow gives issue.

The code snippets are as follows-

pytorch to onnx

net = custom pytorch model
net.load_state_dict("pre-trained model")
dummyInput = np.random.uniform(0,1,(1,8,3,256,256))
dummyInput = Variable(torch.FloatTensor(dummyInput))
torch.onnx.export(ne

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good first issue
sparseml

neuralmagic / sparseml

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Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

nlp sparsity tensorflow keras pytorch deep-learning-algorithms image-classification deep-learning-library pruning object-detection automl computer-vision-algorithms onnx deep-learning-models sparsification pruning-algorithms smaller-models model-sparsification sparsification-recipes recipe-driven-approaches
  • Updated Oct 5, 2021
  • Python

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