Depthwise 2D convolution.

Inherits From: Conv2D, Layer, Module

Used in the notebooks

Used in the guide

Depthwise convolution is a type of convolution in which a single convolutional filter is apply to each input channel (i.e. in a depthwise way). You can understand depthwise convolution as being the first step in a depthwise separable convolution.

It is implemented via the following steps:

  • Split the input into individual channels.
  • Convolve each input with the layer's kernel (called a depthwise kernel).
  • Stack the convolved outputs together (along the channels axis).

Unlike a regular 2D convolution, depthwise convolution does not mix information across different input channels.