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DepthwiseConv2D

Description

Returns the DepthwiseConv2D layer weights. Type : polymorphic.

 

Input parameters

 

 weights : cluster

 index : integer, index of layer.
 name : string, name of layer.
 weight : variant, weight of layer.

Output parameters

 

 weights_info : cluster

 index : integer, index of layer.
 name : string, name of layer.
 weights : cluster

filters_depthwise : array, 4D values. filters_depthwise = [channels, 1, size[0], size[1]].
biases : array, 1D values. biases = [channels].

Dimension

  • filters_depthwise = [channels, 1, size[0], size[1]]

The size of filters_depthwise depends on the input of the DepthwiseConv2D layer and the parameters size.
For example if the input of the layer has a size of [batch_size = 10, channels = 8, rows = 5, cols = 5] and size the value [3, 3] then filters will have a size of [channels = 8, 1, size[0] = 3, size[1] = 3].

 

  • biases = [channels]

The size of biases depends on the parameter size of the DepthwiseConv2D layer.
For example, if the input of the layer has a size of [batch_size = 10, channels = 8, rows = 5, cols = 5] then biases will have a size of [channels = 8].

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 HAIBAL library to run it).

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