extern crate easy_ml;

#[cfg(test)]
mod tensors {
    use easy_ml::tensors::Tensor;

    #[test]
    #[rustfmt::skip]
    fn from_fn_test() {
        let tensor = Tensor::from_fn([("a", 3), ("b", 2)], |[i, j]| format!("{:?}x{:?}", i, j));
        assert_eq!(
            tensor,
            Tensor::from(
                [("a", 3), ("b", 2)],
                vec![
                    "0x0", "0x1",
                    "1x0", "1x1",
                    "2x0", "2x1"
                ]
            ).map(|str| str.to_string())
        )
    }

    #[test]
    fn indexing_test() {
        let tensor = Tensor::from([("x", 2), ("y", 2)], vec![1, 2, 3, 4]);
        let xy = tensor.index_by(["x", "y"]);
        let yx = tensor.index_by(["y", "x"]);
        assert_eq!(xy.get([0, 0]), 1);
        assert_eq!(xy.get([0, 1]), 2);
        assert_eq!(xy.get([1, 0]), 3);
        assert_eq!(xy.get([1, 1]), 4);
        assert_eq!(yx.get([0, 0]), 1);
        assert_eq!(yx.get([0, 1]), 3);
        assert_eq!(yx.get([1, 0]), 2);
        assert_eq!(yx.get([1, 1]), 4);
        use easy_ml::tensors::views::{DataLayout, TensorRef};
        assert_eq!(xy.data_layout(), DataLayout::Linear(["x", "y"]));
        assert_eq!(yx.data_layout(), DataLayout::Linear(["x", "y"]));
    }

    #[test]
    fn higher_dimensional_indexing_test() {
        let tensor = Tensor::from([("a", 3), ("b", 3), ("c", 3)], (0..27).collect());
        let tensor = tensor.map_with_index(|index, _| index);

        let abc = tensor.index_by(["a", "b", "c"]);
        assert_eq!(abc.shape(), [("a", 3), ("b", 3), ("c", 3)]);
        // Our first index is for a, our second index is for b, and our third index is for c
        assert_eq!(abc.get([0, 0, 0]), [0, 0, 0]);
        assert_eq!(abc.get([0, 0, 1]), [0, 0, 1]);
        assert_eq!(abc.get([0, 0, 2]), [0, 0, 2]);
        assert_eq!(abc.get([0, 1, 0]), [0, 1, 0]);
        assert_eq!(abc.get([0, 1, 1]), [0, 1, 1]);
        assert_eq!(abc.get([0, 1, 2]), [0, 1, 2]);
        assert_eq!(abc.get([0, 2, 0]), [0, 2, 0]);
        assert_eq!(abc.get([0, 2, 1]), [0, 2, 1]);
        assert_eq!(abc.get([0, 2, 2]), [0, 2, 2]);
        assert_eq!(abc.get([1, 0, 0]), [1, 0, 0]);
        assert_eq!(abc.get([1, 0, 1]), [1, 0, 1]);
        assert_eq!(abc.get([1, 0, 2]), [1, 0, 2]);
        assert_eq!(abc.get([1, 1, 0]), [1, 1, 0]);
        assert_eq!(abc.get([1, 1, 1]), [1, 1, 1]);
        assert_eq!(abc.get([1, 1, 2]), [1, 1, 2]);
        assert_eq!(abc.get([1, 2, 0]), [1, 2, 0]);
        assert_eq!(abc.get([1, 2, 1]), [1, 2, 1]);
        assert_eq!(abc.get([1, 2, 2]), [1, 2, 2]);
        assert_eq!(abc.get([2, 0, 0]), [2, 0, 0]);
        assert_eq!(abc.get([2, 0, 1]), [2, 0, 1]);
        assert_eq!(abc.get([2, 0, 2]), [2, 0, 2]);
        assert_eq!(abc.get([2, 1, 0]), [2, 1, 0]);
        assert_eq!(abc.get([2, 1, 1]), [2, 1, 1]);
        assert_eq!(abc.get([2, 1, 2]), [2, 1, 2]);
        assert_eq!(abc.get([2, 2, 0]), [2, 2, 0]);
        assert_eq!(abc.get([2, 2, 1]), [2, 2, 1]);
        assert_eq!(abc.get([2, 2, 2]), [2, 2, 2]);

        let cba = tensor.index_by(["c", "b", "a"]);
        assert_eq!(cba.shape(), [("c", 3), ("b", 3), ("a", 3)]);
        // Our first index is for c, our second index is for b, and our third index is for a
        assert_eq!(cba.get([0, 0, 0]), [0, 0, 0]);
        assert_eq!(cba.get([0, 0, 1]), [1, 0, 0]);
        assert_eq!(cba.get([0, 0, 2]), [2, 0, 0]);
        assert_eq!(cba.get([0, 1, 0]), [0, 1, 0]);
        assert_eq!(cba.get([0, 1, 1]), [1, 1, 0]);
        assert_eq!(cba.get([0, 1, 2]), [2, 1, 0]);
        assert_eq!(cba.get([0, 2, 0]), [0, 2, 0]);
        assert_eq!(cba.get([0, 2, 1]), [1, 2, 0]);
        assert_eq!(cba.get([0, 2, 2]), [2, 2, 0]);
        assert_eq!(cba.get([1, 0, 0]), [0, 0, 1]);
        assert_eq!(cba.get([1, 0, 1]), [1, 0, 1]);
        assert_eq!(cba.get([1, 0, 2]), [2, 0, 1]);
        assert_eq!(cba.get([1, 1, 0]), [0, 1, 1]);
        assert_eq!(cba.get([1, 1, 1]), [1, 1, 1]);
        assert_eq!(cba.get([1, 1, 2]), [2, 1, 1]);
        assert_eq!(cba.get([1, 2, 0]), [0, 2, 1]);
        assert_eq!(cba.get([1, 2, 1]), [1, 2, 1]);
        assert_eq!(cba.get([1, 2, 2]), [2, 2, 1]);
        assert_eq!(cba.get([2, 0, 0]), [0, 0, 2]);
        assert_eq!(cba.get([2, 0, 1]), [1, 0, 2]);
        assert_eq!(cba.get([2, 0, 2]), [2, 0, 2]);
        assert_eq!(cba.get([2, 1, 0]), [0, 1, 2]);
        assert_eq!(cba.get([2, 1, 1]), [1, 1, 2]);
        assert_eq!(cba.get([2, 1, 2]), [2, 1, 2]);
        assert_eq!(cba.get([2, 2, 0]), [0, 2, 2]);
        assert_eq!(cba.get([2, 2, 1]), [1, 2, 2]);
        assert_eq!(cba.get([2, 2, 2]), [2, 2, 2]);

        let cab = tensor.index_by(["c", "a", "b"]);
        assert_eq!(cab.shape(), [("c", 3), ("a", 3), ("b", 3)]);
        // Our first index is for c, our second index is for a, and our third index is for b
        assert_eq!(cab.get([0, 0, 0]), [0, 0, 0]);
        assert_eq!(cab.get([0, 0, 1]), [0, 1, 0]);
        assert_eq!(cab.get([0, 0, 2]), [0, 2, 0]);
        assert_eq!(cab.get([0, 1, 0]), [1, 0, 0]);
        assert_eq!(cab.get([0, 1, 1]), [1, 1, 0]);
        assert_eq!(cab.get([0, 1, 2]), [1, 2, 0]);
        assert_eq!(cab.get([0, 2, 0]), [2, 0, 0]);
        assert_eq!(cab.get([0, 2, 1]), [2, 1, 0]);
        assert_eq!(cab.get([0, 2, 2]), [2, 2, 0]);
        assert_eq!(cab.get([1, 0, 0]), [0, 0, 1]);
        assert_eq!(cab.get([1, 0, 1]), [0, 1, 1]);
        assert_eq!(cab.get([1, 0, 2]), [0, 2, 1]);
        assert_eq!(cab.get([1, 1, 0]), [1, 0, 1]);
        assert_eq!(cab.get([1, 1, 1]), [1, 1, 1]);
        assert_eq!(cab.get([1, 1, 2]), [1, 2, 1]);
        assert_eq!(cab.get([1, 2, 0]), [2, 0, 1]);
        assert_eq!(cab.get([1, 2, 1]), [2, 1, 1]);
        assert_eq!(cab.get([1, 2, 2]), [2, 2, 1]);
        assert_eq!(cab.get([2, 0, 0]), [0, 0, 2]);
        assert_eq!(cab.get([2, 0, 1]), [0, 1, 2]);
        assert_eq!(cab.get([2, 0, 2]), [0, 2, 2]);
        assert_eq!(cab.get([2, 1, 0]), [1, 0, 2]);
        assert_eq!(cab.get([2, 1, 1]), [1, 1, 2]);
        assert_eq!(cab.get([2, 1, 2]), [1, 2, 2]);
        assert_eq!(cab.get([2, 2, 0]), [2, 0, 2]);
        assert_eq!(cab.get([2, 2, 1]), [2, 1, 2]);
        assert_eq!(cab.get([2, 2, 2]), [2, 2, 2]);

        let bca = tensor.index_by(["b", "c", "a"]);
        assert_eq!(bca.shape(), [("b", 3), ("c", 3), ("a", 3)]);
        // Our first index is for b, our second index is for c, and our third index is for a
        assert_eq!(bca.get([0, 0, 0]), [0, 0, 0]);
        assert_eq!(bca.get([0, 0, 1]), [1, 0, 0]);
        assert_eq!(bca.get([0, 0, 2]), [2, 0, 0]);
        assert_eq!(bca.get([0, 1, 0]), [0, 0, 1]);
        assert_eq!(bca.get([0, 1, 1]), [1, 0, 1]);
        assert_eq!(bca.get([0, 1, 2]), [2, 0, 1]);
        assert_eq!(bca.get([0, 2, 0]), [0, 0, 2]);
        assert_eq!(bca.get([0, 2, 1]), [1, 0, 2]);
        assert_eq!(bca.get([0, 2, 2]), [2, 0, 2]);
        assert_eq!(bca.get([1, 0, 0]), [0, 1, 0]);
        assert_eq!(bca.get([1, 0, 1]), [1, 1, 0]);
        assert_eq!(bca.get([1, 0, 2]), [2, 1, 0]);
        assert_eq!(bca.get([1, 1, 0]), [0, 1, 1]);
        assert_eq!(bca.get([1, 1, 1]), [1, 1, 1]);
        assert_eq!(bca.get([1, 1, 2]), [2, 1, 1]);
        assert_eq!(bca.get([1, 2, 0]), [0, 1, 2]);
        assert_eq!(bca.get([1, 2, 1]), [1, 1, 2]);
        assert_eq!(bca.get([1, 2, 2]), [2, 1, 2]);
        assert_eq!(bca.get([2, 0, 0]), [0, 2, 0]);
        assert_eq!(bca.get([2, 0, 1]), [1, 2, 0]);
        assert_eq!(bca.get([2, 0, 2]), [2, 2, 0]);
        assert_eq!(bca.get([2, 1, 0]), [0, 2, 1]);
        assert_eq!(bca.get([2, 1, 1]), [1, 2, 1]);
        assert_eq!(bca.get([2, 1, 2]), [2, 2, 1]);
        assert_eq!(bca.get([2, 2, 0]), [0, 2, 2]);
        assert_eq!(bca.get([2, 2, 1]), [1, 2, 2]);
        assert_eq!(bca.get([2, 2, 2]), [2, 2, 2]);

        use easy_ml::tensors::views::{DataLayout, TensorRef};
        assert_eq!(abc.data_layout(), DataLayout::Linear(["a", "b", "c"]));
        assert_eq!(cba.data_layout(), DataLayout::Linear(["a", "b", "c"]));
        assert_eq!(cab.data_layout(), DataLayout::Linear(["a", "b", "c"]));
        assert_eq!(bca.data_layout(), DataLayout::Linear(["a", "b", "c"]));
    }

    #[test]
    #[should_panic]
    fn repeated_name() {
        Tensor::from([("x", 2), ("x", 2)], vec![1, 2, 3, 4]);
    }

    #[test]
    #[should_panic]
    fn wrong_size() {
        Tensor::from([("x", 2), ("y", 3)], vec![1, 2, 3, 4]);
    }

    #[test]
    #[should_panic]
    fn bad_indexing() {
        let tensor = Tensor::from([("x", 2), ("y", 2)], vec![1, 2, 3, 4]);
        tensor.index_by(["x", "x"]);
    }

    #[test]
    #[rustfmt::skip]
    fn transpose_more_dimensions() {
        let tensor = Tensor::from(
            [("batch", 2), ("y", 10), ("x", 10), ("color", 1)], vec![
            0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
            0, 0, 0, 0, 1, 1, 0, 0, 0, 0,
            0, 0, 0, 1, 0, 0, 1, 0, 0, 0,
            0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
            0, 1, 1, 1, 1, 1, 1, 1, 1, 0,
            0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
            0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
            0, 0, 0, 0, 1, 0, 0, 0, 1, 0,
            0, 0, 0, 0, 0, 1, 1, 1, 0, 0,
            0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

            0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
            0, 0, 0, 0, 1, 1, 0, 0, 0, 0,
            0, 0, 0, 1, 0, 0, 1, 0, 0, 0,
            0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
            0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
            0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
            0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
            0, 0, 0, 1, 0, 0, 1, 0, 0, 0,
            0, 0, 0, 0, 1, 1, 0, 0, 0, 0,
            0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
        ]);
        let transposed = tensor.transpose(["batch", "x", "y", "color"]);
        assert_eq!(
            transposed,
            Tensor::from([("batch", 2), ("y", 10), ("x", 10), ("color", 1)], vec![
                0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
                0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
                0, 0, 0, 1, 1, 1, 0, 0, 0, 0,
                0, 0, 1, 0, 1, 0, 1, 0, 0, 0,
                0, 1, 0, 0, 1, 0, 0, 1, 0, 0,
                0, 1, 0, 0, 1, 0, 0, 0, 1, 0,
                0, 0, 1, 0, 1, 0, 0, 0, 1, 0,
                0, 0, 0, 1, 1, 0, 0, 0, 1, 0,
                0, 0, 0, 0, 1, 0, 0, 1, 0, 0,
                0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

                0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
                0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
                0, 0, 0, 1, 1, 1, 1, 0, 0, 0,
                0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
                0, 1, 0, 0, 0, 0, 0, 0, 1, 0,
                0, 1, 0, 0, 0, 0, 0, 0, 1, 0,
                0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
                0, 0, 0, 1, 1, 1, 1, 0, 0, 0,
                0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
                0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
            ])
        );
    }

    #[test]
    fn check_iterators() {
        #[rustfmt::skip]
        let tensor = Tensor::from([("row", 3), ("column", 2)], vec![
            1, 2,
            3, 4,
            5, 6
        ]);
        let mut row_column_iterator = tensor.iter_reference();
        assert_eq!(row_column_iterator.next(), Some(&1));
        assert_eq!(row_column_iterator.next(), Some(&2));
        assert_eq!(row_column_iterator.next(), Some(&3));
        assert_eq!(row_column_iterator.next(), Some(&4));
        assert_eq!(row_column_iterator.next(), Some(&5));
        assert_eq!(row_column_iterator.next(), Some(&6));
        assert_eq!(row_column_iterator.next(), None);
    }

    #[test]
    fn check_iterators_with_index() {
        #[rustfmt::skip]
        let tensor = Tensor::from([("row", 3), ("column", 2)], vec![
            1, 2,
            3, 4,
            5, 6
        ]);
        let row_column = tensor.index();
        let mut iterator = row_column.iter_reference().with_index();
        assert_eq!(iterator.next(), Some(([0, 0], &1)));
        assert_eq!(iterator.next(), Some(([0, 1], &2)));
        assert_eq!(iterator.next(), Some(([1, 0], &3)));
        assert_eq!(iterator.next(), Some(([1, 1], &4)));
        assert_eq!(iterator.next(), Some(([2, 0], &5)));
        assert_eq!(iterator.next(), Some(([2, 1], &6)));
        assert_eq!(iterator.next(), None);
    }

    #[test]
    fn check_transposition() {
        let mut tensor = Tensor::from([("row", 4), ("column", 1)], vec![1, 2, 3, 4]);
        tensor.transpose_mut(["column", "row"]);
        assert_eq!(
            tensor,
            Tensor::from([("row", 1), ("column", 4)], vec![1, 2, 3, 4])
        );
        let mut tensor = Tensor::from([("row", 1), ("column", 4)], vec![1, 2, 3, 4]);
        tensor.transpose_mut(["column", "row"]);
        assert_eq!(
            tensor,
            Tensor::from([("row", 4), ("column", 1)], vec![1, 2, 3, 4])
        );
        #[rustfmt::skip]
        let mut tensor = Tensor::from([("row", 3), ("column", 3)], vec![
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
        ]);
        tensor.transpose_mut(["column", "row"]);
        #[rustfmt::skip]
        assert_eq!(
            tensor,
            Tensor::from(
                [("row", 3), ("column", 3)],
                vec![
                    1, 4, 7,
                    2, 5, 8,
                    3, 6, 9
                ]
            )
        );
        #[rustfmt::skip]
        let mut tensor = Tensor::from([("r", 2), ("c", 3)], vec![
            1, 2, 3,
            4, 5, 6
        ]);
        tensor.transpose_mut(["c", "r"]);
        #[rustfmt::skip]
        assert_eq!(
            tensor,
            Tensor::from([("r", 3), ("c", 2)], vec![
                1, 4,
                2, 5,
                3, 6
            ])
        );
        #[rustfmt::skip]
        let mut tensor = Tensor::from([("a", 3), ("b", 2)], vec![
            1, 2,
            3, 4,
            5, 6
        ]);
        tensor.transpose_mut(["b", "a"]);
        #[rustfmt::skip]
        assert_eq!(
            tensor,
            Tensor::from([("a", 2), ("b", 3)], vec![
                1, 3, 5,
                2, 4, 6
            ])
        );
        #[rustfmt::skip]
        let tensor = Tensor::from([("row", 3), ("column", 3)], vec![
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
        ]);
        #[rustfmt::skip]
        assert_eq!(
            tensor.transpose(["column", "row"]),
            Tensor::from(
                [("row", 3), ("column", 3)],
                vec![
                    1, 4, 7,
                    2, 5, 8,
                    3, 6, 9
                ]
            )
        );
    }

    #[test]
    fn check_reorder() {
        let mut tensor = Tensor::from([("row", 4), ("column", 1)], vec![1, 2, 3, 4]);
        tensor.reorder_mut(["column", "row"]);
        assert_eq!(
            tensor,
            Tensor::from([("column", 1), ("row", 4)], vec![1, 2, 3, 4])
        );
        let mut tensor = Tensor::from([("row", 1), ("column", 4)], vec![1, 2, 3, 4]);
        tensor.reorder_mut(["column", "row"]);
        assert_eq!(
            tensor,
            Tensor::from([("column", 4), ("row", 1)], vec![1, 2, 3, 4])
        );
        #[rustfmt::skip]
        let mut tensor = Tensor::from([("row", 3), ("column", 3)], vec![
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
        ]);
        tensor.reorder_mut(["column", "row"]);
        assert_eq!(
            tensor,
            Tensor::from(
                [("column", 3), ("row", 3)],
                vec![1, 4, 7, 2, 5, 8, 3, 6, 9,]
            )
        );
        #[rustfmt::skip]
        let mut tensor = Tensor::from([("r", 2), ("c", 3)], vec![
            1, 2, 3,
            4, 5, 6
        ]);
        tensor.reorder_mut(["c", "r"]);
        assert_eq!(
            tensor,
            Tensor::from([("c", 3), ("r", 2)], vec![1, 4, 2, 5, 3, 6,])
        );
        #[rustfmt::skip]
        let mut tensor = Tensor::from([("a", 3), ("b", 2)], vec![
            1, 2,
            3, 4,
            5, 6
        ]);
        tensor.reorder_mut(["b", "a"]);
        assert_eq!(
            tensor,
            Tensor::from([("b", 2), ("a", 3)], vec![1, 3, 5, 2, 4, 6,])
        );
        #[rustfmt::skip]
        let tensor = Tensor::from([("row", 3), ("column", 3)], vec![
            1, 2, 3,
            4, 5, 6,
            7, 8, 9
        ]);
        assert_eq!(
            tensor.reorder(["column", "row"]),
            Tensor::from(
                [("column", 3), ("row", 3)],
                vec![1, 4, 7, 2, 5, 8, 3, 6, 9,]
            )
        );
    }

    #[test]
    fn test_reshaping() {
        let tensor = Tensor::from([("everything", 20)], (0..20).collect());
        let mut five_by_four = tensor.reshape_owned([("fives", 5), ("fours", 4)]);
        #[rustfmt::skip]
        assert_eq!(
            Tensor::from([("fives", 5), ("fours", 4)], vec![
                0, 1, 2, 3,
                4, 5, 6, 7,
                8, 9, 10, 11,
                12, 13, 14, 15,
                16, 17, 18, 19
            ]),
            five_by_four
        );
        five_by_four.reshape_mut([("twos", 2), ("tens", 10)]);
        #[rustfmt::skip]
        assert_eq!(
            Tensor::from([("twos", 2), ("tens", 10)], vec![
                0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
                10, 11, 12, 13, 14, 15, 16, 17, 18, 19
            ]),
            five_by_four
        );
        let flattened = five_by_four.reshape_owned([("data", 20)]);
        assert_eq!(flattened, Tensor::from([("data", 20)], (0..20).collect()));
    }

    #[test]
    #[should_panic]
    fn invalid_reshape() {
        let mut square = Tensor::from([("r", 2), ("c", 2)], (0..4).collect());
        square.reshape_mut([("not", 3), ("square", 1)]);
    }

    #[test]
    fn check_data_layout_tensor() {
        use easy_ml::tensors::views::{DataLayout, TensorRef};
        let tensor = Tensor::from([("b", 3), ("r", 3), ("c", 3)], (0..27).collect());
        assert_eq!(tensor.data_layout(), DataLayout::Linear(["b", "r", "c"]));
        let tensor = Tensor::from([("r", 2), ("c", 2)], (0..4).collect());
        assert_eq!(tensor.data_layout(), DataLayout::Linear(["r", "c"]));
        let tensor = Tensor::from([("a", 3)], (0..3).collect());
        assert_eq!(tensor.data_layout(), DataLayout::Linear(["a"]));
    }

    #[test]
    fn check_data_layout_non_linear_tensor_views() {
        use easy_ml::tensors::views::{DataLayout, TensorRef};
        let tensor = Tensor::from([("b", 3), ("r", 3), ("c", 3)], (0..27).collect());
        assert_eq!(tensor.data_layout(), DataLayout::Linear(["b", "r", "c"]));
        assert_eq!(
            tensor
                .range([("b", 0..2)])
                .unwrap()
                .source_ref()
                .data_layout(),
            DataLayout::NonLinear
        );
        assert_eq!(
            tensor
                .mask([("c", 0..2)])
                .unwrap()
                .source_ref()
                .data_layout(),
            DataLayout::NonLinear
        );
        assert_eq!(
            tensor.select([("b", 1)]).source_ref().data_layout(),
            DataLayout::NonLinear
        );
        assert_eq!(
            tensor.expand([(2, "x")]).source_ref().data_layout(),
            DataLayout::NonLinear
        );
    }

    #[test]
    fn check_data_layout_tensor_access() {
        use easy_ml::tensors::indexing::TensorAccess;
        use easy_ml::tensors::views::{DataLayout, TensorRef, TensorRename, TensorView};
        let tensor = Tensor::from([("b", 3), ("r", 3), ("c", 3)], (0..27).collect());
        assert_eq!(tensor.data_layout(), DataLayout::Linear(["b", "r", "c"]));
        assert_eq!(
            tensor.index_by(["b", "r", "c"]).data_layout(),
            DataLayout::Linear(["b", "r", "c"])
        );
        assert_eq!(
            tensor.index_by(["c", "r", "b"]).data_layout(),
            DataLayout::Linear(["b", "r", "c"])
        );
        assert_eq!(
            tensor.index_by(["r", "c", "b"]).data_layout(),
            DataLayout::Linear(["b", "r", "c"])
        );
        assert_eq!(
            tensor.index_by(["r", "b", "c"]).data_layout(),
            DataLayout::Linear(["b", "r", "c"])
        );
        assert_eq!(
            tensor.index_by(["c", "b", "r"]).data_layout(),
            DataLayout::Linear(["b", "r", "c"])
        );

        // Each time we transpose we expect the data layout we get back to be correct, which
        // we can verify by using it as the index order. If the data layout is correct then
        // returning to big endian order means we iterate through the tensor as the 0..27 it was
        // defined with.
        let transposed = tensor.transpose_view(["b", "r", "c"]);
        assert_eq!(
            transposed.source_ref().data_layout(),
            DataLayout::Linear(["b", "r", "c"])
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            transposed
                .index_by(["b", "r", "c"])
                .iter()
                .collect::<Vec<_>>()
        );
        // We can avoid manually passing the linear data layout if we use from_memory_order
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            TensorAccess::from_memory_order(transposed.source_ref())
                .unwrap()
                .iter()
                .collect::<Vec<_>>()
        );
        // Alternative way to 'transpose', should match TensorTranspose exactly
        let also_transposed = TensorView::from(TensorRename::from(
            tensor.index_by(["b", "r", "c"]),
            ["b", "r", "c"],
        ));
        assert_eq!(transposed, also_transposed);
        assert_eq!(
            also_transposed.source_ref().data_layout(),
            DataLayout::Linear(["b", "r", "c"])
        );

        let transposed = tensor.transpose_view(["c", "r", "b"]);
        assert_eq!(
            transposed.source_ref().data_layout(),
            DataLayout::Linear(["c", "r", "b"])
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            transposed
                .index_by(["c", "r", "b"])
                .iter()
                .collect::<Vec<_>>()
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            TensorAccess::from_memory_order(transposed.source_ref())
                .unwrap()
                .iter()
                .collect::<Vec<_>>()
        );
        let also_transposed = TensorView::from(TensorRename::from(
            tensor.index_by(["c", "r", "b"]),
            ["b", "r", "c"],
        ));
        assert_eq!(transposed, also_transposed);
        assert_eq!(
            also_transposed.source_ref().data_layout(),
            DataLayout::Linear(["c", "r", "b"])
        );

        let transposed = tensor.transpose_view(["r", "c", "b"]);
        assert_eq!(
            transposed.source_ref().data_layout(),
            DataLayout::Linear(["c", "b", "r"])
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            transposed
                .index_by(["c", "b", "r"])
                .iter()
                .collect::<Vec<_>>()
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            TensorAccess::from_memory_order(transposed.source_ref())
                .unwrap()
                .iter()
                .collect::<Vec<_>>()
        );
        let also_transposed = TensorView::from(TensorRename::from(
            tensor.index_by(["r", "c", "b"]),
            ["b", "r", "c"],
        ));
        assert_eq!(transposed, also_transposed);
        assert_eq!(
            also_transposed.source_ref().data_layout(),
            DataLayout::Linear(["c", "b", "r"])
        );

        let transposed = tensor.transpose_view(["r", "b", "c"]);
        assert_eq!(
            transposed.source_ref().data_layout(),
            DataLayout::Linear(["r", "b", "c"])
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            transposed
                .index_by(["r", "b", "c"])
                .iter()
                .collect::<Vec<_>>()
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            TensorAccess::from_memory_order(transposed.source_ref())
                .unwrap()
                .iter()
                .collect::<Vec<_>>()
        );
        let also_transposed = TensorView::from(TensorRename::from(
            tensor.index_by(["r", "b", "c"]),
            ["b", "r", "c"],
        ));
        assert_eq!(transposed, also_transposed);
        assert_eq!(
            also_transposed.source_ref().data_layout(),
            DataLayout::Linear(["r", "b", "c"])
        );

        let transposed = tensor.transpose_view(["c", "b", "r"]);
        assert_eq!(
            transposed.source_ref().data_layout(),
            DataLayout::Linear(["r", "c", "b"])
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            transposed
                .index_by(["r", "c", "b"])
                .iter()
                .collect::<Vec<_>>()
        );
        assert_eq!(
            (0..27).collect::<Vec<_>>(),
            TensorAccess::from_memory_order(transposed.source_ref())
                .unwrap()
                .iter()
                .collect::<Vec<_>>()
        );
        let also_transposed = TensorView::from(TensorRename::from(
            tensor.index_by(["c", "b", "r"]),
            ["b", "r", "c"],
        ));
        assert_eq!(transposed, also_transposed);
        assert_eq!(
            also_transposed.source_ref().data_layout(),
            DataLayout::Linear(["r", "c", "b"])
        );
    }

    #[test]
    fn check_data_layout_linear_tensor_views() {
        use easy_ml::tensors::views::{DataLayout, TensorRef};
        let tensor = Tensor::from([("b", 3), ("r", 3), ("c", 3)], (0..27).collect());
        assert_eq!(tensor.data_layout(), DataLayout::Linear(["b", "r", "c"]));
        assert_eq!(
            tensor
                .rename_view(["a", "q", "b"])
                .source_ref()
                .data_layout(),
            DataLayout::Linear(["a", "q", "b"])
        );
    }

    #[test]
    fn display_and_indexing_for_reordering() {
        use easy_ml::tensors::views::TensorView;
        let tensor = Tensor::from([("a", 2), ("b", 3), ("c", 4)], (0..(2 * 3 * 4)).collect());
        assert_eq!(
            tensor.iter().collect::<Vec<_>>(),
            (0..(2 * 3 * 4)).collect::<Vec<_>>()
        );
        assert_eq!(
            r#"D = 3
("a", 2), ("b", 3), ("c", 4)
[
  0, 1, 2, 3
  4, 5, 6, 7
  8, 9, 10, 11

  12, 13, 14, 15
  16, 17, 18, 19
  20, 21, 22, 23
]"#,
            tensor.to_string(),
        );
        let reordered = tensor.index_by(["b", "c", "a"]);
        // reordering the 3D tensor should yield a tensor that still displays with the leftmost
        // dimension as the largest group, the second dimension as rows and the final dimension as
        // columns
        assert_eq!(
            reordered.iter().collect::<Vec<_>>(),
            vec![
                0, 12, 1, 13, 2, 14, 3, 15, 4, 16, 5, 17, 6, 18, 7, 19, 8, 20, 9, 21, 10, 22, 11,
                23
            ]
        );
        assert_eq!(
            r#"D = 3
("b", 3), ("c", 4), ("a", 2)
[
  0, 12
  1, 13
  2, 14
  3, 15

  4, 16
  5, 17
  6, 18
  7, 19

  8, 20
  9, 21
  10, 22
  11, 23
]
Data Layout = Linear(["a", "b", "c"])"#,
            reordered.to_string(),
        );

        // To transpose our way back, make biggest dimension a, since as from above that's a
        // stride of 12. Make next dimension b. since that's a stride of 4, then make smallest
        // dimension c since that's a stride of 1 (this aligns with data layout too).
        let transposed = TensorView::from(reordered).transpose(["a", "b", "c"]);
        assert_eq!(
            transposed.iter().collect::<Vec<_>>(),
            (0..(2 * 3 * 4)).collect::<Vec<_>>()
        );
        assert_eq!(
            r#"D = 3
("b", 2), ("c", 3), ("a", 4)
[
  0, 1, 2, 3
  4, 5, 6, 7
  8, 9, 10, 11

  12, 13, 14, 15
  16, 17, 18, 19
  20, 21, 22, 23
]"#,
            transposed.to_string(),
        );
    }

    #[test]
    fn test_identity_constructor() {
        let identity = Tensor::diagonal([("a", 3), ("b", 3)], 1.0);
        #[rustfmt::skip]
        assert_eq!(
            identity,
            Tensor::from([("a", 3), ("b", 3)], vec![
                1.0, 0.0, 0.0,
                0.0, 1.0, 0.0,
                0.0, 0.0, 1.0
            ])
        );
    }

    #[test]
    fn test_owned_iterator_of_mut_source() {
        use easy_ml::tensors::indexing::TensorOwnedIterator;
        let mut tensor = Tensor::from_fn([("x", 2), ("y", 2)], |[x, y]| x + y);
        let mut_tensor = &mut tensor;
        let owned_iter = TensorOwnedIterator::from(mut_tensor);
        let drained = owned_iter.collect::<Vec<_>>();
        assert_eq!(drained, vec![0, 1, 1, 2]);
        // original tensor is now drained of its values so should be set to 0 as that's the
        // default value substituted.
        assert_eq!(tensor, Tensor::empty([("x", 2), ("y", 2)], 0));
    }
}