burn_core/nn/
leaky_relu.rs

1use crate as burn;
2use crate::config::Config;
3use crate::module::Module;
4use crate::module::{Content, DisplaySettings, ModuleDisplay};
5use crate::tensor::backend::Backend;
6use crate::tensor::Tensor;
7
8use crate::tensor::activation::leaky_relu;
9
10/// Leaky ReLu layer.
11///
12/// Should be created with [LeakyReluConfig](LeakyReluConfig).
13#[derive(Module, Clone, Debug)]
14#[module(custom_display)]
15pub struct LeakyRelu {
16    /// The negative slope.
17    pub negative_slope: f64,
18}
19/// Configuration to create a [Leaky Relu](LeakyRelu) layer using the [init function](LeakyReluConfig::init).
20#[derive(Config, Debug)]
21pub struct LeakyReluConfig {
22    /// The negative slope. Default is 0.01
23    #[config(default = "0.01")]
24    pub negative_slope: f64,
25}
26impl LeakyReluConfig {
27    /// Initialize a new [Leaky Relu](LeakyRelu) Layer
28    pub fn init(&self) -> LeakyRelu {
29        LeakyRelu {
30            negative_slope: self.negative_slope,
31        }
32    }
33}
34
35impl ModuleDisplay for LeakyRelu {
36    fn custom_settings(&self) -> Option<DisplaySettings> {
37        DisplaySettings::new()
38            .with_new_line_after_attribute(false)
39            .optional()
40    }
41
42    fn custom_content(&self, content: Content) -> Option<Content> {
43        content
44            .add("negative_slope", &self.negative_slope)
45            .optional()
46    }
47}
48
49impl LeakyRelu {
50    /// Forward pass for the Leaky ReLu layer.
51    ///
52    /// See [leaky_relu](crate::tensor::activation::leaky_relu) for more information.
53    ///
54    /// # Shapes
55    /// - input: `[..., any]`
56    /// - output: `[..., any]`
57    pub fn forward<B: Backend, const D: usize>(&self, input: Tensor<B, D>) -> Tensor<B, D> {
58        leaky_relu(input, self.negative_slope)
59    }
60}
61
62#[cfg(test)]
63mod tests {
64    use super::*;
65    use crate::tensor::TensorData;
66    use crate::TestBackend;
67
68    #[test]
69    fn test_leaky_relu_forward() {
70        let device = <TestBackend as Backend>::Device::default();
71        let model: LeakyRelu = LeakyReluConfig::new().init();
72        let input =
73            Tensor::<TestBackend, 2>::from_data(TensorData::from([[0.4410, -0.2507]]), &device);
74        let out = model.forward(input);
75        let expected = TensorData::from([[0.4410, -0.002507]]);
76        out.to_data().assert_eq(&expected, false);
77    }
78    #[test]
79    fn test_leaky_relu_forward_multi_dim() {
80        let input = [
81            [
82                [-1.0222, 1.5810, 0.3457, -1.3530],
83                [0.0231, 0.8681, 0.2473, -0.0377],
84                [0.3520, -1.1199, 1.2219, 0.2804],
85            ],
86            [
87                [1.0002, 0.7259, 0.8779, 0.2084],
88                [1.5615, -0.1057, -0.4886, -1.5184],
89                [-0.5523, -0.2741, -0.0210, -1.1352],
90            ],
91        ];
92        let expected = TensorData::from([
93            [
94                [-1.0222e-02, 1.5810e+00, 3.457e-01, -1.3530e-02],
95                [2.31e-02, 8.681e-01, 2.473e-01, -3.77e-04],
96                [3.52e-01, -1.1199e-02, 1.2219e+00, 2.804e-01],
97            ],
98            [
99                [1.0002e+00, 7.259e-01, 8.779e-01, 2.084e-01],
100                [1.5615e+00, -1.057e-03, -4.886e-03, -1.5184e-02],
101                [-5.523e-03, -2.741e-03, -2.1e-04, -1.1352e-02],
102            ],
103        ]);
104
105        let device = <TestBackend as Backend>::Device::default();
106        let model: LeakyRelu = LeakyReluConfig::new().init();
107        let input_data = Tensor::<TestBackend, 3>::from_data(TensorData::from(input), &device);
108        let actual_output = model.forward(input_data);
109        actual_output.to_data().assert_approx_eq(&expected, 4)
110    }
111
112    #[test]
113    fn display() {
114        let config = LeakyReluConfig::new().init();
115        assert_eq!(
116            alloc::format!("{}", config),
117            "LeakyRelu {negative_slope: 0.01}"
118        );
119    }
120}
burn_core/nn/leaky_relu.rs

burn_core/nn/
leaky_relu.rs
