samskalicky commented on issue #17623: Dynamic subgraph compile support URL: https://github.com/apache/incubator-mxnet/pull/17623#issuecomment-589858094 > It sounds like the goal for passing data is to allow data to be compiled into the bin (example tensort bin) for that subgraph to avoid an init step. > > If the weights are in the bin, then we structuring this such that weights can not be changed with calling optimize_for again using new weights ? Using the weights in `optimize_for` is a one-way flow. You cannot call `optimize_for` again with new weights. You would need to call it on the original graph with new weights. The assumption is that weights would only be used for inference. So presumably the model is already trained, and the weights are frozen. > Is there any reason why we only do this for args and not auxs ? Thanks for pointing this out. I'll add them too
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