Deep learning: save and load a universal machine model through different libraries
My questions can be divided into two parts.


Is there a format of machine learning model file that can be used through different libraries? For example, I saved a model by pytorch, then load it using tensorflow?
If not, is there a library that can help transfer the formats so that a pytorch machine learning model can be used directly in keras?


The reason why I ask this question is that recently I need to adjust some of my previous trained models in tensorflow to pytorch.

An update for this question:
Facebook and Microsoft are going to launch a model standard called ONNX, which is used for transferring models between different framworks, for example between Pytorch to Caffe2. Link in the following:

https://research.fb.com/facebook-and-microsoft-introduce-new-open-ecosystem-for-interchangeable-ai-frameworks/

An further update for this question:
Tensorflow itself use Protocol Buffer format to store model file, which can be used for transfer between different models. Link in the following:

https://www.tensorflow.org/extend/tool_developers/

Very interesting question. A neural network is a mathematical abstraction consisting of a network of layers (convolution, recurrent, ...), operations (dot product, non-linearity, ...) and their respective parameters (weights, biases).


AFAIK, there's not an universal model file. Nonetheless, different libraries allow users to save their models in a binary format.
There's no library for conversion but there's effort on github repo that addresses this question.

