burn-tensor 0.16.1

Tensor library with user-friendly APIs and automatic differentiation support
Documentation 
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#[burn_tensor_testgen::testgen(sort_argsort)]
mod tests {
    use super::*;
    use burn_tensor::{Shape, Tensor, TensorData};

    #[test]
    fn test_sort_1d_int() {
        // Skip with u8
        if (IntType::MAX as u32) < 1000u32 {
            return;
        }

        let tensor = TestTensorInt::<1>::from([1, 4, 7, 2, 5, 6, 3, 0, 9, 8, 2, 8, -10, 42, 1000]);

        // Sort along dim=0
        let values = tensor.sort(0);
        let values_expected = TensorData::from([-10, 0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 8, 9, 42, 1000]);

        values.into_data().assert_eq(&values_expected, false);
    }

    #[test]
    fn test_argsort_1d_int() {
        // Skip with u8
        if (IntType::MAX as u32) < 1000u32 {
            return;
        }

        let tensor = TestTensorInt::<1>::from([1, 4, 7, 2, 5, 6, 3, 0, 9, 8, -10, 42, 1000]);

        // Sort along dim=0
        let indices = tensor.argsort(0);
        let indices_expected = TensorData::from([10, 7, 0, 3, 6, 1, 4, 5, 2, 9, 8, 11, 12]);

        indices.into_data().assert_eq(&indices_expected, false);
    }

    #[test]
    fn test_sort_with_indices_descending_int() {
        // Skip with u8
        if (IntType::MAX as u32) >= 1000u32 {
            // 1D
            let tensor = TestTensorInt::<1>::from([1, 4, 7, 2, 5, 6, 3, 0, 9, 8, -10, 42, 1000]);

            // Sort along dim=0
            let (values, indices) = tensor.sort_descending_with_indices(0);

            let values_expected = TensorData::from([1000, 42, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -10]);
            values.into_data().assert_eq(&values_expected, false);

            let indices_expected = TensorData::from([12, 11, 8, 9, 2, 5, 4, 1, 6, 3, 0, 7, 10]);
            indices.into_data().assert_eq(&indices_expected, false);
        }

        // 2D
        let tensor = TestTensorInt::<3>::from([[[1, 4, 7], [2, 5, 6]], [[3, 0, 9], [8, 2, 8]]]);

        // Sort along dim=1
        let (values, indices) = tensor.sort_descending_with_indices(1);

        let values_expected = TensorData::from([[[2, 5, 7], [1, 4, 6]], [[8, 2, 9], [3, 0, 8]]]);
        values.into_data().assert_eq(&values_expected, false);

        let indices_expected = TensorData::from([[[1, 1, 0], [0, 0, 1]], [[1, 1, 0], [0, 0, 1]]]);
        indices.into_data().assert_eq(&indices_expected, false);
    }

    #[test]
    fn test_sort_int() {
        let tensor = TestTensorInt::<3>::from([[[1, 4, 7], [2, 5, 6]], [[3, 0, 9], [8, 2, 8]]]);

        // Sort along dim=0
        let values = tensor.clone().sort(0);

        let values_expected = TensorData::from([[[1, 0, 7], [2, 2, 6]], [[3, 4, 9], [8, 5, 8]]]);
        values.into_data().assert_eq(&values_expected, false);

        // Sort along dim=1
        let values = tensor.clone().sort(1);

        let values_expected = TensorData::from([[[1, 4, 6], [2, 5, 7]], [[3, 0, 8], [8, 2, 9]]]);
        values.into_data().assert_eq(&values_expected, false);

        // Sort along dim=2
        let values = tensor.sort(2);

        let values_expected = TensorData::from([[[1, 4, 7], [2, 5, 6]], [[0, 3, 9], [2, 8, 8]]]);
        values.into_data().assert_eq(&values_expected, false);
    }

    #[test]
    fn test_sort_with_indices_int() {
        let tensor = TestTensorInt::<3>::from([[[1, 4, 7], [2, 5, 6]], [[3, 0, 9], [7, 2, 8]]]);

        // Sort along dim=0
        let (values, indices) = tensor.clone().sort_with_indices(0);

        let values_expected = TensorData::from([[[1, 0, 7], [2, 2, 6]], [[3, 4, 9], [7, 5, 8]]]);
        values.into_data().assert_eq(&values_expected, false);

        let indices_expected = TensorData::from([[[0, 1, 0], [0, 1, 0]], [[1, 0, 1], [1, 0, 1]]]);
        indices.into_data().assert_eq(&indices_expected, false);

        // Sort along dim=1
        let (values, indices) = tensor.clone().sort_with_indices(1);

        let values_expected = TensorData::from([[[1, 4, 6], [2, 5, 7]], [[3, 0, 8], [7, 2, 9]]]);
        values.into_data().assert_eq(&values_expected, false);

        let indices_expected = TensorData::from([[[0, 0, 1], [1, 1, 0]], [[0, 0, 1], [1, 1, 0]]]);
        indices.into_data().assert_eq(&indices_expected, false);

        // Sort along dim=2
        let (values, indices) = tensor.sort_with_indices(2);

        let values_expected = TensorData::from([[[1, 4, 7], [2, 5, 6]], [[0, 3, 9], [2, 7, 8]]]);
        values.into_data().assert_eq(&values_expected, false);

        let indices_expected = TensorData::from([[[0, 1, 2], [0, 1, 2]], [[1, 0, 2], [1, 0, 2]]]);
        indices.into_data().assert_eq(&indices_expected, false);
    }

    #[test]
    fn test_argsort_int() {
        let tensor = TestTensorInt::<3>::from([[[1, 4, 7], [2, 5, 6]], [[3, 0, 9], [7, 2, 8]]]);

        // Sort along dim=0
        let indices = tensor.clone().argsort(0);

        let indices_expected = TensorData::from([[[0, 1, 0], [0, 1, 0]], [[1, 0, 1], [1, 0, 1]]]);
        indices.into_data().assert_eq(&indices_expected, false);

        // Sort along dim=1
        let indices = tensor.clone().argsort(1);

        let indices_expected = TensorData::from([[[0, 0, 1], [1, 1, 0]], [[0, 0, 1], [1, 1, 0]]]);
        indices.into_data().assert_eq(&indices_expected, false);

        // Sort along dim=2
        let indices = tensor.argsort(2);

        let indices_expected = TensorData::from([[[0, 1, 2], [0, 1, 2]], [[1, 0, 2], [1, 0, 2]]]);
        indices.into_data().assert_eq(&indices_expected, false);
    }

    #[test]
    fn test_sort_1d_float() {
        let tensor = TestTensor::<1>::from([
            0.5, 1.2, -0.21, 0., 2.1, 0.94, -0.3, 2.3, 199.412, 4., 0.99, 3., -8.1,
        ]);

        // Sort along dim=0
        let values = tensor.sort(0);

        let values_expected = TensorData::from([
            -8.1, -0.3, -0.21, 0., 0.5, 0.94, 0.99, 1.2, 2.1, 2.3, 3., 4., 199.412,
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.04);
    }

    #[test]
    fn test_argsort_1d_float() {
        let tensor = TestTensor::<1>::from([
            0.5, 1.2, -0.21, 0., 2.1, 0.94, -0.3, 2.3, 199.412, 4., 0.99, 3., -8.1,
        ]);

        // Sort along dim=0
        let indices = tensor.argsort(0);

        let indices_expected = TensorData::from([12, 6, 2, 3, 0, 5, 10, 1, 4, 7, 11, 9, 8]);
        indices.into_data().assert_eq(&indices_expected, false);
    }

    #[test]
    fn test_sort_with_indices_descending_float() {
        // 1D
        let tensor = TestTensor::<1>::from([
            0.5, 1.2, -0.21, 0., 2.1, 0.94, -0.3, 2.3, 199.412, 4., 0.99, 3., -8.1,
        ]);

        // Sort along dim=0
        let (values, indices) = tensor.sort_descending_with_indices(0);

        let values_expected = TensorData::from([
            199.412, 4., 3., 2.3, 2.1, 1.2, 0.99, 0.94, 0.5, 0., -0.21, -0.3, -8.1,
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.04);

        let indices_expected = TensorData::from([8, 9, 11, 7, 4, 1, 10, 5, 0, 3, 2, 6, 12]);
        indices.into_data().assert_eq(&indices_expected, false);

        // 2D
        let tensor = TestTensor::<3>::from([
            [[-0.5, 1.2, -0.21], [0., 2.1, 0.94]],
            [[-0.3, 2.3, 4.], [0.99, 3., -8.1]],
        ]);

        // Sort along dim=1
        let (values, indices) = tensor.sort_descending_with_indices(1);

        let values_expected = TensorData::from([
            [[0., 2.1, 0.94], [-0.5, 1.2, -0.21]],
            [[0.99, 3., 4.], [-0.3, 2.3, -8.1]],
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.04);

        let indices_expected = TensorData::from([[[1, 1, 1], [0, 0, 0]], [[1, 1, 0], [0, 0, 1]]]);
        indices.into_data().assert_eq(&indices_expected, false);
    }

    #[test]
    fn test_sort_float() {
        let tensor = TestTensor::<3>::from([
            [[-0.5, 1.2, -0.21], [0., 2.1, 0.94]],
            [[-0.3, 2.3, 4.], [0.99, 3., -8.1]],
        ]);

        // Sort along dim=0
        let values = tensor.clone().sort(0);

        let values_expected = TensorData::from([
            [[-0.5, 1.2, -0.21], [0., 2.1, -8.1]],
            [[-0.3, 2.3, 4.], [0.99, 3., 0.94]],
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.002);

        // Sort along dim=1
        let values = tensor.clone().sort(1);

        let values_expected = TensorData::from([
            [[-0.5, 1.2, -0.21], [0., 2.1, 0.94]],
            [[-0.3, 2.3, -8.1], [0.99, 3., 4.]],
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.002);

        // Sort along dim=2
        let values = tensor.sort(2);

        let values_expected = TensorData::from([
            [[-0.5, -0.21, 1.2], [0., 0.94, 2.1]],
            [[-0.3, 2.3, 4.], [-8.1, 0.99, 3.]],
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.002);
    }

    #[test]
    fn test_sort_with_indices_float() {
        let tensor = TestTensor::<3>::from([
            [[-0.5, 1.2, -0.21], [0., 2.1, 0.94]],
            [[-0.3, 2.3, 4.], [0.99, 3., -8.1]],
        ]);

        // Sort along dim=0
        let (values, indices) = tensor.clone().sort_with_indices(0);
        let values_expected = TensorData::from([
            [[-0.5, 1.2, -0.21], [0., 2.1, -8.1]],
            [[-0.3, 2.3, 4.], [0.99, 3., 0.94]],
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.002);

        let indices_expected = TensorData::from([[[0, 0, 0], [0, 0, 1]], [[1, 1, 1], [1, 1, 0]]]);
        indices.into_data().assert_eq(&indices_expected, false);

        // Sort along dim=1
        let (values, indices) = tensor.clone().sort_with_indices(1);

        let values_expected = TensorData::from([
            [[-0.5, 1.2, -0.21], [0., 2.1, 0.94]],
            [[-0.3, 2.3, -8.1], [0.99, 3., 4.]],
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.002);

        let indices_expected = TensorData::from([[[0, 0, 0], [1, 1, 1]], [[0, 0, 1], [1, 1, 0]]]);
        indices.into_data().assert_eq(&indices_expected, false);

        // Sort along dim=2
        let (values, indices) = tensor.sort_with_indices(2);

        let values_expected = TensorData::from([
            [[-0.5, -0.21, 1.2], [0., 0.94, 2.1]],
            [[-0.3, 2.3, 4.], [-8.1, 0.99, 3.]],
        ]);
        values
            .into_data()
            .assert_approx_eq_diff(&values_expected, 0.002);

        let indices_expected = TensorData::from([[[0, 2, 1], [0, 2, 1]], [[0, 1, 2], [2, 0, 1]]]);
        indices.into_data().assert_eq(&indices_expected, false);
    }

    #[test]
    fn test_argsort_float() {
        let tensor = TestTensor::<3>::from([
            [[-0.5, 1.2, -0.21], [0., 2.1, 0.94]],
            [[-0.3, 2.3, 4.], [0.99, 3., -8.1]],
        ]);

        // Sort along dim=0
        let indices = tensor.clone().argsort(0);

        let indices_expected = TensorData::from([[[0, 0, 0], [0, 0, 1]], [[1, 1, 1], [1, 1, 0]]]);
        indices.into_data().assert_eq(&indices_expected, false);

        // Sort along dim=1
        let indices = tensor.clone().argsort(1);

        let indices_expected = TensorData::from([[[0, 0, 0], [1, 1, 1]], [[0, 0, 1], [1, 1, 0]]]);
        indices.into_data().assert_eq(&indices_expected, false);

        // Sort along dim=2
        let indices = tensor.argsort(2);

        let indices_expected = TensorData::from([[[0, 2, 1], [0, 2, 1]], [[0, 1, 2], [2, 0, 1]]]);
        indices.into_data().assert_eq(&indices_expected, false);
    }

    #[test]
    fn test_sort_float_nan() {
        let tensor = TestTensor::<2>::from([[-0.5, f32::NAN], [0., 0.94], [-0.3, f32::NAN]]);

        // Sort along dim=0
        let values = tensor.sort(0);

        let values_expected = TensorData::from([[-0.5, 0.94], [-0.3, f32::NAN], [0., f32::NAN]]);
        values.into_data().assert_approx_eq(&values_expected, 4);
    }

    #[test]
    fn test_sort_descending_1d() {
        let tensor = TestTensorInt::<1>::from([1, 2, 3, 4, 5]);

        // Sort along dim=0
        let values = tensor.sort_descending(0);

        let values_expected = TensorData::from([5, 4, 3, 2, 1]);
        values.into_data().assert_eq(&values_expected, false);

        let tensor = TestTensor::<1>::from([1., 2., 3., 4., 5.]);

        // Sort along dim=0
        let values = tensor.sort_descending(0);

        let values_expected = TensorData::from([5., 4., 3., 2., 1.]);
        values.into_data().assert_approx_eq(&values_expected, 5);
    }
}