[GitHub] sxjscience commented on issue #9264: Some questions about gluon

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sxjscience commented on issue #9264: Some questions about gluon
URL: https://github.com/apache/incubator-mxnet/issues/9264#issuecomment-354569930
 
 
   @kice We cannot use list to store Blocks because they will not be registered correctly. You may refer to this PR for more information https://github.com/apache/incubator-mxnet/pull/9148.
   
   One solution to this problem is to use Sequential or HybridSequential as a container to the Conv Layers. For example:
   ```python
   class Layer(nn.HybridBlock):
       def __init__(self, depth=15, channels=3, **kwargs):
           super(Layer, self).__init__(**kwargs)
           self.conv_layers = nn.HybridSequential
           with self.conv_layers.name_scope():
                for i in range(depth):
                     self.conv_layers.add(nn.Conv2D(128, kernel_size=3, strides=1, padding=1, use_bias=True))
      def hybrid_forward(self, F, x):
          # You can use the layers as self.conv_layers[i]
   ```
   
   @szha @piiswrong In PyTorch, there is an additional ModuleList object (http://pytorch.org/docs/master/nn.html#torch.nn.ModuleList) for this behavoir. Do you think we need to add this? (Sequential and HybridSequential already have the functionality of "BlockList")

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