burn-tensor 0.18.0

Tensor library with user-friendly APIs and automatic differentiation support
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#[burn_tensor_testgen::testgen(gelu)]
mod tests {
    use super::*;
    use burn_tensor::{Tensor, TensorData, activation};
    use burn_tensor::{Tolerance, ops::FloatElem};
    type FT = FloatElem<TestBackend>;

    #[test]
    fn test_gelu() {
        let tensor = TestTensor::<2>::from([[
            0.5447, 0.9809, 0.4114, 0.1398, 0.8045, 0.4103, 0.2388, 0.5262, 0.6677, 0.6737,
        ]]);
        let output = activation::gelu(tensor);
        let expected = TensorData::from([[
            0.3851, 0.8207, 0.2714, 0.0777, 0.6351, 0.2704, 0.1419, 0.3687, 0.4993, 0.5051,
        ]]);

        // Low precision to allow approximation implementation using tanh
        output.into_data().assert_approx_eq::<FT>(
            &expected,
            Tolerance::default().set_half_precision_absolute(2e-3),
        );
    }
}