samskalicky commented on a change in pull request #19386:
URL: https://github.com/apache/incubator-mxnet/pull/19386#discussion_r521766129
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File path: python/mxnet/gluon/block.py
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@@ -1087,19 +1087,23 @@ def optimize_for(self, x, *args, backend=None,
backend_opts=None, clear=True, **
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`
- clear : clears any previous optimizations
+ clear : bool, default False
+ Clears any previous optimizations
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.
+ **kwargs: The backend options, optional
+ Passed on to `PrePartition` and `PostPartition` functions of
`SubgraphProperty`
"""
+ if len(kwargs) > 0:
+ self._backend_opts = kwargs
- # do hybrize API call
- self.hybridize(True, backend, backend_opts, clear, **kwargs)
+ if clear or not self._active:
Review comment:
Now, we only call hybridize from optimize_for once the first time (2nd
time _active is set) or if the user sets the clear flag
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