Explain the functions of Link and Chains in chainer in python

This recipe explains what the functions of Link and Chains in chainer in python

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Recipe Objective - Explain the functions of Link and Chains in chainer?

Chainer provides a package "chainer.link" for "link" implementation.

Some Learnable connections Functions:-

1.chainer.links.Bias - This function is used for Broadcasted elementwise summation with learnable parameters.

2.chainer.links.Bilinear - This function is used for Bilinear layer that performs tensor multiplication.

3.chainer.links.ChildSumTreeLSTM - This function is used for Child-Sum TreeLSTM unit.

4.chainer.links.Convolution1D - One-dimensional convolution layer.

5.chainer.links.Convolution2D - Two-dimensional convolution layer.

6.chainer.links.Convolution3D - Three-dimensional convolution layer.

Some Activation/loss/normalization functions with parameters:-

1.chainer.links.BatchNormalization - This function is used for Batch normalization layer on outputs of linear or convolution functions.

2.chainer.links.BatchRenormalization - This function is used for Batch renormalization layer on outputs of linear or convolution functions.

3.chainer.links.DecorrelatedBatchNormalization - This function is used for Decorrelated batch normalization layer.

4.chainer.links.GroupNormalization - This function is used for Group normalization layer on outputs of convolution functions.

5.chainer.links.LayerNormalization - This function is used for Layer normalization layer on outputs of linear functions.

VGG Networks:-

1.chainer.links.VGG16Layers - This is a pre-trained CNN model with 16 layers provided by VGG team.

2.chainer.links.VGG19Layers - This is a pre-trained CNN model with 19 layers provided by VGG team.

3.chainer.links.model.vision.vgg.prepare - This function is used to converts the given image to the numpy array for VGG models.

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