message: Clarify the shape of convolution arguments.
  Replace n-d with size n, as n-d often means rank n, while the arguments here are arrays of size n.
diff: @@ -440,11 +440,13 @@ area and a computation is performed for each possible position of the window.
  | `lhs` | `ComputationDataHandle` | rank n+2 array of inputs |
  | `rhs` | `ComputationDataHandle` | rank n+2 array of kernel |
  : : : weights :
  -| `window_strides` | `ArraySlice<int64>` | n-d array of kernel strides |
  -| `padding` | `ArraySlice<pair<int64, | n-d array of (low, high) |
  +| `window_strides` | `ArraySlice<int64>` | size n array of kernel strides|
  +| `padding` | `ArraySlice<pair<int64, | size n array of (low, high) |
  : : int64>>` : padding :
  -| `lhs_dilation` | `ArraySlice<int64>` | n-d lhs dilation factor array |
  -| `rhs_dilation` | `ArraySlice<int64>` | n-d rhs dilation factor array |
  +| `lhs_dilation` | `ArraySlice<int64>` | size n lhs dilation factor |
  +: : : array |
  +| `rhs_dilation` | `ArraySlice<int64>` | size n rhs dilation factor
  +: : : array |
  Let n be the number of spatial dimensions. The `lhs` argument is a rank n+2
  array describing the base area. This is called the input, even though of course
  