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PReLU 4D
Description
Gets the weights of the PReLU4D selected by the name. Type : polymorphic.

Input parameters
 Model in : model architecture.
 Model in : model architecture. name : string, name of layer.
 name : string, name of layer.
Output parameters
 Model out : model architecture.
 Model out : model architecture.
 weights_info : cluster
 weights_info : cluster
 index : integer, index of layer.
 index : integer, index of layer. name : string, name of layer.
 name : string, name of layer. weights : cluster
 weights : cluster
 alpha : array, 3D alpha values.  alpha = [input_dim1, input_dim2, input_dim3].
 alpha : array, 3D alpha values.  alpha = [input_dim1, input_dim2, input_dim3].
 
			Dimension
- alpha = [input_dim1, input_dim2, input_dim3]
Its size depends on the input of the PReLU layer.
For example, if the layer has an entry [batch_size = 10, input_dim1 = 7, input_dim2 = 5, input_dim3 = 3] then alpha will have a size [input_dim1 = 7, input_dim2 = 5, input_dim3 = 3].
The size can also depend on the “shared_axis” parameter that you set to the PReLU layer. Each axis specified in this param is represented by a 1 in the weights.
For example, if you set the parameter with the values [2], alpha will have a size [input_dim1 = 7, 1, input_dim3 = 3].
Another example, if you define the parameter with the values [2, 3], alpha will have a size [input_dim1 = 7, 1, 1].
Example
All these exemples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Deep Learning library to run it).

