[GitHub] [incubator-mxnet] rondogency commented on a change in pull request #17623: Dynamic subgraph compile support

[GitBox <gi...@apache.org>]

rondogency commented on a change in pull request #17623: Dynamic subgraph compile support
URL: https://github.com/apache/incubator-mxnet/pull/17623#discussion_r388629152
 
 

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 File path: python/mxnet/gluon/block.py
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 @@ -1026,6 +1030,53 @@ def _call_cached_op(self, *args):
             out = [out]
         return _regroup(out, self._out_format)
 
+    def optimize_for(self, x, *args, backend=None, backend_opts=None, **kwargs):
+        """Activates or deactivates :py:class:`HybridBlock` s recursively. Has no effect on
+        non-hybrid children.
+
+        Parameters
+        ----------
+        x : NDArray
+            first input to model
+        *args : NDArray
+            other inputs to model
+        backend : str
+            The name of backend, as registered in `SubgraphBackendRegistry`, default None
+        backend_opts : dict of user-specified options to pass to the backend for partitioning, optional
+            Passed on to `PrePartition` and `PostPartition` functions of `SubgraphProperty`
+        static_alloc : bool, default False
+            Statically allocate memory to improve speed. Memory usage may increase.
+        static_shape : bool, default False
+            Optimize for invariant input shapes between iterations. Must also
+            set static_alloc to True. Change of input shapes is still allowed
+            but slower.
+        """
+
+        # do hybrize API call
+        self.hybridize(True, backend, backend_opts, **kwargs)
 
 Review comment:
   what if user calls hybridize and then call optimize_for? nothing will happen or it throws on unrelated error message?

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