Model-Pivot is a model conversion and visualization tool to help users inter-operate among different deep learning frameworks. Convert models between PyTorch and Tensorflow.
IR is based on the National Information Technology Standardization ```Neural Network Representation and Model Compression Part 1: Convolution Neural Network``.
Requirments
tensorflow==1.8.0
pytorch==0.4.0
torchvision==0.2.0
protobuf>=3.6.1
python>=3.6
flask
How to deploy visualization on Web
If you want to access the deployed web page from an external network, you should first modify the host and port for the ./visualization/app.py file.
You can deploy it on Web by running:
python app.py
Model
Framework
ResNet50
Inception V3
ShuffleNet
FCN
LSTM
TensorFlow
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PyTorch
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Test for Tensorflow and PyTorch
CUDA_VSIBLE_DEVICES=0 python test.py
关于
Model-Pivot is a model conversion and visualization tool to help users inter-operate among different deep learning frameworks. Convert models between PyTorch and Tensorflow.
Model-Pivot
Model-Pivot is a model conversion and visualization tool to help users inter-operate among different deep learning frameworks. Convert models between PyTorch and Tensorflow. IR is based on the National Information Technology Standardization ```Neural Network Representation and Model Compression Part 1: Convolution Neural Network``.
Requirments
How to deploy visualization on Web
If you want to access the deployed web page from an external network, you should first modify the host and port for the ./visualization/app.py file.
You can deploy it on Web by running:
Model
Test for Tensorflow and PyTorch