Spatial Attention

Basic spatial attention as presented in arxiv

Class - SpatialAttention2D

Simple SpatialAttention for 2D filters.

Parameter	type	Description
in_channels	int	Number of input channels
kernel_size	int, default=7	Filter size for convolution filter
batch_norm	bool, default=True	If true batch normalization is applied

Return Value

The returned value is the spatial attention map. This map is not applied to the original input in any way.

Example

A simple usage example without context:

import torch
import useful_layers as ul


layer = ul.layers.SpatialAttention2D(in_channels=5,
                                     kernel_size=2)

Class - SpatialAttention3D

Simple SpatialAttention for 3D filters.

Parameter	type	Description
in_channels	int	Number of input channels
kernel_size	int, default=7	Filter size for convolution filter
batch_norm	bool, default=True	If true batch normalization is applied

Return Value

The returned value is the spatial attention map. This map is not applied to the original input in any way.

Example

A simple usage example without context:

import torch
import useful_layers as ul


layer = ul.layers.SpatialAttention3D(in_channels=5,
                                     kernel_size=2)