feevos commented on issue #16736: Bug when iterating over HybridSequential elements URL: https://github.com/apache/incubator-mxnet/issues/16736#issuecomment-550172645 Some additional information: it seems the error relates to how many times the initial input is passed from the conv layers. It is not directly related to the iteration over the HybridSequential container. This works irrespective to what is the length of the kernel_sizes: ```Python class Demo(HybridBlock): def __init__(self, kernel_sizes = [3,3,3,3],**kwards): super().__init__(**kwards) with self.name_scope(): self.net = gluon.nn.HybridSequential() for k in kernel_sizes: tnet = gluon.nn.HybridSequential() for _ in range(3): tnet.add(gluon.nn.Conv2D(32,kernel_size=k,padding=1)) self.net.add(tnet) def hybrid_forward(self, F, input): x = input for conv in self.net: #x = x + conv(input) x = x + conv(x) ## <===== CHANGE HERE return x ``` Runs fine: ```Python nfilters=32 F = 256 net = Demo(kernel_sizes=[3]*100) net.initialize() net.hybridize() xx = nd.random.uniform(shape=[7,nfilters,F,F]) out = net(xx) ```
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