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.
Source framework with version (like Tensorflow 1.4.1 with GPU):
Destination framework with version (like CNTK 2.3 with GPU):
Pre-trained model path (webpath or webdisk path):
Running scripts:
Since i saw mmdnn have the ability to "retain" a model, i do not really got how it works.
Does it mean we still can train our model on the mmdnn's IR or what ?
Sorry, didn't quite get your question. i am afraid that one can not train on the IR level, but once the model is transferred to another framework, then you can just use the model anyway you like.
Platform (like ubuntu 16.04/win10):
Python version:
Source framework with version (like Tensorflow 1.4.1 with GPU):
Destination framework with version (like CNTK 2.3 with GPU):
Pre-trained model path (webpath or webdisk path):
Running scripts: Since i saw mmdnn have the ability to "retain" a model, i do not really got how it works. Does it mean we still can train our model on the mmdnn's IR or what ?