use super::*;
use burn_tensor::TensorData;
use burn_tensor::Tolerance;

#[test]
fn should_support_powf_ops() {
    let data = TensorData::from([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
    let tensor = TestTensor::<2>::from_data(data, &Default::default());

    let output = tensor.powf_scalar(0.71);
    let expected = TensorData::from([[0.0, 1.0, 1.6358], [2.1815, 2.67586, 3.13522]]);

    output
        .into_data()
        .assert_approx_eq::<FloatElem>(&expected, Tolerance::default());
}

#[test]
fn should_support_neg_power() {
    let data = TensorData::from([[1.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
    let tensor = TestTensor::<2>::from_data(data, &Default::default());

    let output = tensor.powf_scalar(-0.33);
    let expected = TensorData::from([[1.0, 1.0, 0.79553646], [0.695905, 0.6328783, 0.58794934]]);

    output
        .into_data()
        .assert_approx_eq::<FloatElem>(&expected, Tolerance::default());
}

#[test]
fn should_support_neg_values_with_even_power() {
    let data = TensorData::from([[0.0, -1.0, -2.0], [-3.0, -4.0, -5.0]]);
    let tensor = TestTensor::<2>::from_data(data, &Default::default());

    let output = tensor.powf_scalar(4.0);
    let expected = TensorData::from([[0.0, 1.0, 16.0], [81.0, 256.0, 625.0]]);

    output
        .into_data()
        .assert_approx_eq::<FloatElem>(&expected, Tolerance::default());
}

#[test]
fn should_support_neg_values_with_odd_power() {
    let data = TensorData::from([[0.0, -1.0, -2.0], [-3.0, -4.0, -5.0]]);
    let tensor = TestTensor::<2>::from_data(data, &Default::default());

    let output = tensor.powf_scalar(3.0);
    let expected = TensorData::from([[0.0, -1.0, -8.0], [-27.0, -64.0, -125.0]]);

    output
        .into_data()
        .assert_approx_eq::<FloatElem>(&expected, Tolerance::default());
}
