[GitHub] [incubator-mxnet] QueensGambit commented on issue #16173: Saving and loading cudNN autotune and graph optimization

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QueensGambit commented on issue #16173: Saving and loading cudNN autotune and graph optimization
URL: https://github.com/apache/incubator-mxnet/issues/16173#issuecomment-531559033
 
 
   Thank you for the reply @pengzhao-intel. I updated the description on MKLDNN.
   
   I see the point about portability and backward compatibility issues.
   Maybe it is better to define `optimize` as a string argument which must be in `{'on_bind', 'save_reload', 'disabled'}`:
   
   ```python
   def bind(self, ctx, args, args_grad=None, grad_req='write',
                  aux_states=None, group2ctx=None, shared_exec=None, optimize='on_bind'):
   """
      # ...
       optimize : str, optional, default 'on_bind'
                       must be in {'on_bind', 'save_reload', 'disabled'}
                       'on_bind': Graph optimization / cuDNN autotune is executed during model binding
                       'save_reload': MXNet attempts to recover previous optimization information. 
                                      Otherwise MXNet will perform optimization and save it to disk.
                       'disabled': No graph optimization / cuDNN autotune is performed
   """
   ```
   
   In the default case `optimize='on_bind'`, it will behave the same way as currently and all previous code will behave the same.
   
   As a different aspect, it might be preferable to treat graph optimization (MKLDNN graph optimization / TensorRT graph fusion) as a different entity compared to cudNN autotune because cudNN autotune might also be performed on fused graphs in future versions.

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