What are Normalization layers functions in lasagne layers?

This recipe explains what are Normalization layers functions in lasagne layers.

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Recipe Objective - What are Normalization layers functions in lasagne layers?

Normalization layers:-

1. LocalResponseNormalization2DLayer - Cross-channel Local Response Normalization for 2D feature maps.

2. BatchNormLayer - For Batch Normalization.

3. batch_norm - Apply batch normalization to an existing layer.

4. StandardizationLayer - Standardize inputs to zero mean and unit variance.

5. instance_norm - Apply instance normalization to an existing layer.

6. layer_norm - Apply layer normalization to an existing layer.

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Example:-

from lasagne.layers import InputLayer, DenseLayer, batch_norm, instance_norm, layer_norm, Conv2DLayer
from lasagne.nonlinearities import tanh, rectify
ly1 = InputLayer((64, 768))
ly2 = batch_norm(DenseLayer(ly1, num_units=500, nonlinearity=tanh))

from lasagne.layers import get_all_layers
[ly.__class__.__name__ for ly in get_all_layers(ly2)] 

['InputLayer', 'DenseLayer', 'BatchNormLayer', 'NonlinearityLayer']

ly3 = InputLayer((10, 3, 28, 28))
ly4 = instance_norm(Conv2DLayer(ly3, num_filters=64, filter_size=3, nonlinearity=rectify))

from lasagne.layers import get_all_layers
[ly.__class__.__name__ for ly in get_all_layers(ly4)] 

['InputLayer',
 'Conv2DLayer',
 'StandardizationLayer',
 'ScaleLayer',
 'BiasLayer',
 'NonlinearityLayer']

ly5 = InputLayer((10, 28))
ly6 = layer_norm(DenseLayer(ly5, num_units=64, nonlinearity=rectify))

from lasagne.layers import get_all_layers
[ly.__class__.__name__ for ly in get_all_layers(ly6)] 

['InputLayer',
 'DenseLayer',
 'StandardizationLayer',
 'ScaleLayer',
 'BiasLayer',
 'NonlinearityLayer']

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