tensorlogic_train/loss/
hingeloss_traits.rs

1//! # HingeLoss - Trait Implementations
2//!
3//! This module contains trait implementations for `HingeLoss`.
4//!
5//! ## Implemented Traits
6//!
7//! - `Default`
8//! - `Loss`
9
10use crate::{TrainError, TrainResult};
11use scirs2_core::ndarray::{Array, ArrayView, Ix2};
12
13use super::functions::Loss;
14use super::types::HingeLoss;
15
16impl Default for HingeLoss {
17    fn default() -> Self {
18        Self { margin: 1.0 }
19    }
20}
21
22impl Loss for HingeLoss {
23    fn compute(
24        &self,
25        predictions: &ArrayView<f64, Ix2>,
26        targets: &ArrayView<f64, Ix2>,
27    ) -> TrainResult<f64> {
28        if predictions.shape() != targets.shape() {
29            return Err(TrainError::LossError(format!(
30                "Shape mismatch: predictions {:?} vs targets {:?}",
31                predictions.shape(),
32                targets.shape()
33            )));
34        }
35        let mut total_loss = 0.0;
36        let n = predictions.nrows() as f64;
37        for i in 0..predictions.nrows() {
38            for j in 0..predictions.ncols() {
39                let pred = predictions[[i, j]];
40                let target = targets[[i, j]];
41                let loss = (self.margin - target * pred).max(0.0);
42                total_loss += loss;
43            }
44        }
45        Ok(total_loss / n)
46    }
47    fn gradient(
48        &self,
49        predictions: &ArrayView<f64, Ix2>,
50        targets: &ArrayView<f64, Ix2>,
51    ) -> TrainResult<Array<f64, Ix2>> {
52        let mut grad = Array::zeros(predictions.raw_dim());
53        let n = predictions.nrows() as f64;
54        for i in 0..predictions.nrows() {
55            for j in 0..predictions.ncols() {
56                let pred = predictions[[i, j]];
57                let target = targets[[i, j]];
58                if self.margin - target * pred > 0.0 {
59                    grad[[i, j]] = -target / n;
60                }
61            }
62        }
63        Ok(grad)
64    }
65}
tensorlogic_train/loss/hingeloss_traits.rs

tensorlogic_train/loss/
hingeloss_traits.rs
