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README.md
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# vgg11
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Implementation of VGG proposed in [Very Deep Convolutional Networks For
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Large-Scale Image Recognition](https://arxiv.org/pdf/1409.1556.pdf)
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``` python
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VGG.vgg11()
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VGG.vgg13()
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VGG.vgg16()
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VGG.vgg19()
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VGG.vgg11_bn()
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VGG.vgg13_bn()
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VGG.vgg16_bn()
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VGG.vgg19_bn()
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```
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Please be aware that the [bn]{.title-ref} models uses BatchNorm but
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they are very old and people back then don\'t know the bias is
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superfluous in a conv followed by a batchnorm.
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Examples:
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``` python
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# change activation
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VGG.vgg11(activation = nn.SELU)
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# change number of classes (default is 1000 )
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VGG.vgg11(n_classes=100)
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# pass a different block
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from nn.models.classification.senet import SENetBasicBlock
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VGG.vgg11(block=SENetBasicBlock)
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# store the features tensor after every block
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```
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