burn-tensor 0.18.0

Tensor library with user-friendly APIs and automatic differentiation support
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52

#[burn_tensor_testgen::testgen(module_linear)]
mod tests {
    use super::*;
    use burn_tensor::TensorData;
    use burn_tensor::module::linear;
    use burn_tensor::{Tolerance, ops::FloatElem};
    type FT = FloatElem<TestBackend>;

    #[test]
    fn test_linear_1d() {
        let weight = TestTensor::<2>::from([[1.0, 2.0], [3.0, 4.0]]);

        let x = TestTensor::<1>::from([1.0, 2.0]);
        let output = linear(x, weight, None);

        let expected = TensorData::from([7.0, 10.0]);
        output
            .into_data()
            .assert_approx_eq::<FT>(&expected, Tolerance::relative(1e-5));
    }

    #[test]
    fn test_linear_forward_no_bias() {
        let weight = TestTensor::<2>::from([[1.0, 2.0], [3.0, 4.0]]);

        let x = TestTensor::<3>::from([[[1.0, 2.0], [3.0, 4.0]], [[-1.0, -2.0], [-3.0, -4.0]]]);

        let output = linear(x, weight, None);

        let expected =
            TensorData::from([[[7.0, 10.0], [15.0, 22.0]], [[-7.0, -10.0], [-15.0, -22.0]]]);
        output
            .into_data()
            .assert_approx_eq::<FT>(&expected, Tolerance::relative(1e-5));
    }

    #[test]
    fn test_linear_forward_with_bias() {
        let weight = TestTensor::<2>::from([[1.0, 2.0], [3.0, 4.0]]);
        let bias = Some(TestTensor::<1>::from([1.0, -1.0]));

        let x = TestTensor::<3>::from([[[1.0, 2.0], [3.0, 4.0]], [[-1.0, -2.0], [-3.0, -4.0]]]);

        let output = linear(x, weight, bias);

        let expected =
            TensorData::from([[[8.0, 9.0], [16.0, 21.0]], [[-6.0, -11.0], [-14.0, -23.0]]]);
        output
            .into_data()
            .assert_approx_eq::<FT>(&expected, Tolerance::relative(1e-5));
    }
}