burn_core/nn/pool/
adaptive_avg_pool1d.rs1use crate as burn;
2
3use crate::config::Config;
4use crate::module::Module;
5use crate::module::{Content, DisplaySettings, ModuleDisplay};
6use crate::tensor::Tensor;
7use crate::tensor::backend::Backend;
8
9use crate::tensor::module::adaptive_avg_pool1d;
10
11#[derive(Config)]
13pub struct AdaptiveAvgPool1dConfig {
14 pub output_size: usize,
16}
17
18#[derive(Module, Clone, Debug)]
22#[module(custom_display)]
23pub struct AdaptiveAvgPool1d {
24 pub output_size: usize,
26}
27
28impl ModuleDisplay for AdaptiveAvgPool1d {
29 fn custom_settings(&self) -> Option<DisplaySettings> {
30 DisplaySettings::new()
31 .with_new_line_after_attribute(false)
32 .optional()
33 }
34
35 fn custom_content(&self, content: Content) -> Option<Content> {
36 content.add("output_size", &self.output_size).optional()
37 }
38}
39
40impl AdaptiveAvgPool1dConfig {
41 pub fn init(&self) -> AdaptiveAvgPool1d {
43 AdaptiveAvgPool1d {
44 output_size: self.output_size,
45 }
46 }
47}
48
49impl AdaptiveAvgPool1d {
50 pub fn forward<B: Backend>(&self, input: Tensor<B, 3>) -> Tensor<B, 3> {
59 adaptive_avg_pool1d(input, self.output_size)
60 }
61}
62
63#[cfg(test)]
64mod tests {
65 use super::*;
66
67 #[test]
68 fn display() {
69 let config = AdaptiveAvgPool1dConfig::new(3);
70 let layer = config.init();
71
72 assert_eq!(
73 alloc::format!("{}", layer),
74 "AdaptiveAvgPool1d {output_size: 3}"
75 );
76 }
77}