MMdnn
A comprehensive toolset for converting, visualizing, and managing deep learning models across multiple frameworks like TensorFlow, PyTorch, and Caffe.
What is MMdnn?
MMdnn is a comprehensive toolset for managing deep learning models, focusing on cross-framework interoperability. It solves the problem of model portability by allowing conversion between popular frameworks like TensorFlow, PyTorch, Caffe, and others, enabling developers to train in one environment and deploy in another.
Deep learning researchers, engineers, and developers who work with multiple frameworks and need to convert, visualize, or deploy models across different ecosystems.
It provides a universal, tested converter that supports a wide range of frameworks and models, reducing the complexity and time required for model migration and promoting framework-agnostic development.
Overview
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.
Use Cases
Best For
- Converting a TensorFlow model to PyTorch for deployment
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