[GitHub] [incubator-mxnet] sxjscience commented on a change in pull request #18876: [Numpy][Bugfix] Add hybridization test to loss layers

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

sxjscience commented on a change in pull request #18876:
URL: https://github.com/apache/incubator-mxnet/pull/18876#discussion_r467322411



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File path: python/mxnet/symbol/numpy/_symbol.py
##########
@@ -8012,7 +8012,7 @@ def diagonal(a, offset=0, axis1=0, axis2=1):
 
 # pylint:disable=redefined-outer-name, too-many-arguments
 @set_module('mxnet.symbol.numpy')
-def sum(a, axis=None, dtype=None, out=None, keepdims=None, initial=None, where=None):
+def sum(a, axis=None, dtype=None, out=None, keepdims=False, initial=None, where=None):

Review comment:
       @szha Figured out a bug in `symbol.sum` which does not hybridization. Minimal reproducible:
   ```python
   import mxnet as mx
   from mxnet.gluon.nn import HybridBlock
   mx.npx.set_np()
   
   class Foo(HybridBlock):
       def hybrid_forward(self, F, x):
           return F.np.sum(x)
   
   foo = Foo()
   foo.hybridize()
   out = foo(mx.np.ones((10, 10)))
   out.asnumpy()
   ```




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