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

#[test]
fn should_support_div_ops() {
    let tensor_1 = QTensor::<2>::int8([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
    let tensor_2 = QTensor::<2>::int8([[1.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

    let output = tensor_1 / tensor_2;
    let expected = TensorData::from([[0.0, 1.0, 1.0], [1.0, 1.0, 1.0]]);

    output
        .dequantize()
        .into_data()
        .assert_approx_eq::<FloatElem>(&expected, Tolerance::absolute(1e-1));
}

#[test]
fn test_div_broadcast() {
    let tensor_1 = QTensor::<2>::int8([[0.0, 1.0, 2.0]]);
    let tensor_2 = QTensor::<2>::int8([[1.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

    let output = tensor_1 / tensor_2;

    output
        .dequantize()
        .into_data()
        .assert_approx_eq::<FloatElem>(
            &TensorData::from([[0.0, 1.0, 1.0], [0.0, 0.25, 0.4]]),
            Tolerance::absolute(1e-1),
        );
}

#[test]
fn should_support_div_scalar_ops() {
    let scalar = 2.0;
    let tensor = QTensor::<2>::int8([[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);

    let output = tensor / scalar;

    output
        .dequantize()
        .into_data()
        .assert_approx_eq::<FloatElem>(
            &TensorData::from([[0.0, 0.5, 1.0], [1.5, 2.0, 2.5]]),
            Tolerance::absolute(1e-1),
        );
}
