Any tutorial for Gluon models?

4

Let’s take gluon.model_zoo.vision.Resnet_V2 as an example. You can create your own Block (or HybridBlock) with a dummy feature and whatever type of advanced output you need followed by that. Then after initializing your block’s parameters, simply load the pre-trained network from model-zoo and replace your networks’s feature with the pretrained net’s feature. Just remember that if you want to train end-to-end, parameters that are passed to Trainer must be fetched after pre-trained feature is added to your network:

class MyAdvancedNet(gluon.HybridBlock):
    def __init__(self):
        super(MyAdvancedNet, self).__init__()
        with self.name_scope():
            self.feature = None
            self.output = gluon.nn.Dense(10)

    def hybrid_forward(self, F, x):
        return self.output(self.feature(x))

net = MyAdvancedNet()
net.collect_params().initialize()
pretrained_net = gluon.model_zoo.vision.resnet34_v2(pretrained=True)
net.feature = pretrained_net.features

y = net(nd.random.uniform(shape=(16, 3, 224, 224)))
print(y.shape)
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