umutisik commented 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.arange(100).reshape([5,5,2,2])*100. 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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