Welcome to our Support Center

DepthwiseConv2D

Description

Adds the weights of the DepthwiseConv2D layer to the weights table. Type : polymorphic.

 

Input parameters

 

Weights in : array

Β name :Β string,Β name of layer.
Β weights :Β variant,Β weights values.

Β name :Β string,Β name of layer.
Β filters_depthwise :Β array,Β 4D values. filters_depthwise = [channels, 1, size[0], size[1]].
Β biases :Β array,Β 1D values. biases = [channels].

Output parameters

 

Β Weights out : array

Β name :Β string,Β name of layer.
Β weights :Β variant,Β weights values.

Dimension

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

The size of filters_depthwise depends on the input of theΒ DepthwiseConv2DΒ 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 theΒ DepthwiseConv2DΒ 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).

Table of Contents
Index