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onnx / onnx

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need tf.random.shuffle supported.

2
chan4cc
chan4cc commented Apr 26, 2021

New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

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operator good first issue enhancement
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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 Jun 16, 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 Jun 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 tensorflow-models coreml onnx tensorflow-lite tflite tensorflowjs tfjs openvino edgetpu mediapipe tf-trt
  • Updated Aug 19, 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

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