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Model Backward compatibility aims to check whether models trained on earlier versions of MXNet are loading fine on the latest version or the latest release candidate. It also aims to do a sanity check for consistency in the inference on these trained models.

3. Approach

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Here's a proposed approach to do this : 

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A first cut of model backwards compatibility using the above approach has been implemented here : https://github.com/apache/incubator-mxnet/pull/11626. We would want to make it more robust and would like to get feedback on the ways in which we can improve this further.