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Convolution 3D


Adds the weights of the Conv3D layer to the weights table. Type : polymorphic.


Input parameters


Weights in : array

Β index :Β integer,Β index of layer.
Β weights :Β variant,Β weights values.

Β index :Β integer,Β index of layer.
Β filters :Β array,Β 5D values. filters = [n_filters, channel, size[0], size[1], size[2]].
Β biases :Β array,Β 1D values. biases = [n_filters].

Output parameters


Β Weights out : array

Β index :Β integer,Β index of layer.
Β weights :Β variant,Β weights values.


  • filters = [n_filters, channel, size[0], size[1], size[2]]

The size of filters depends on the input of theΒ Conv3DΒ layer and the parameters n_filters and size.
For example, if the input of the layer has a size of [batch_size = 10, channel = 8, conv_dim1 = 7, conv_dim2 = 5, conv_dim3 = 5], n_filters has the value 6 and size the value [3, 3, 3] then filters will have a size of [n_filters = 6, channel = 8, size[0] = 3, size[1] = 3, size[2] = 3].


  • biases = [n_filters].

The size of biases depends on the parameter n_filters of theΒ Conv3DΒ layer.


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 HAIBAL library to run it).

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