Critical bug: colMajor is WRONG for 3D+ tensors
Not detected before convolutions because matmul, CuBLAS etc are only used in 2D space ...

```Nim
import ../src/arraymancer



let a = newTensor[int](1, 1, 4, 4)

echo a.shape
echo a.strides

echo ""
echo "rowMajor check"
var rowM: MetadataArray
shape_to_strides(a.shape, rowMajor, rowM)
echo rowM
echo repr rowM

echo ""
echo "colMajor check"
var colM: MetadataArray
shape_to_strides(a.shape, colMajor, colM)
echo colM
echo repr colM
```

```
[1, 1, 4, 4]
[16, 16, 4, 1]

rowMajor check
[16, 16, 4, 1]
[data = [16, 16, 4, 1, 0, 0, 0, 0],
len = 4]


colMajor check
[1, 1, 1, 4]
[data = [1, 1, 1, 4, 0, 0, 0, 0],
len = 4]
```

Regression introduced by the change in shape_to_strides in #94 :/