[GitHub] [incubator-mxnet] umutisik edited a comment on issue #4901: Is it possible to do "broadcast_concat"?

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

umutisik edited a comment on issue #4901: Is it possible to do "broadcast_concat"?
URL: https://github.com/apache/incubator-mxnet/issues/4901#issuecomment-598998912
 
 
   The following works for me:
   ```python
   class TestModel(gluon.HybridBlock):
       def __init__(self, **kwargs):
           super(TestModel, self).__init__(**kwargs)
           # self.c2 = self.params.get_constant('c2', [[1,2,3]])
           self.c2 = self.params.get_constant('c2', np.arange(12).reshape([1,3,2,2]).tolist()) # 1,3,2,2
           self.compa = 1.
           
       def hybrid_forward(self, F, x, **kwargs):
           c = F.broadcast_to(kwargs['c2'], shape=(-1, 0, 0, 0)) 
           return F.concat(c, x, dim=1) 
   
   model = TestModel()
   model.hybridize()
   model.initialize()
   x = np.ones([5,5,2,2])*100.
   x = nd.array(x)
   out = model(x)
   print(out.shape)
   print(out[0, 0])
   print(out[0, 3])
   ```
   
   Shape -1 is not supported in ndarray though.
   But I only needed the non-fixed size in symbol. 

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