MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks, which means you can train a model with one framework and deploy it with another. During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform.

Features

  • We provide a model converter to help developers convert models between frameworks through an intermediate representation format
  • MMdnn provides a docker image
  • The model conversion between currently supported frameworks is tested on some ImageNet models
  • One command to achieve the conversion
  • We provide a guide to help you accelerate inference with TensorRT.
  • We provide a local visualizer to display the network architecture of a deep learning model

Project Samples

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License

MIT License

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Additional Project Details

Operating Systems

Android

Programming Language

Python

Related Categories

Python Frameworks, Python Data Visualization Software, Python Machine Learning Software, Python Neural Network Libraries, Python Deep Learning Frameworks

Registered

2021-09-30