Release v4.0.0 (#2294)

media/docs/cpp/cute/03_tensor.md

@@ -269,9 +269,7 @@ Tensor E = A(make_coord(_,1),make_coord(0,_,1));
 Tensor F = A(make_coord(2,_),make_coord(_,3,_));
 ```
 
-<p align="center">
-  <img src="../../../images/cute/slice.png" alt="slice.png" height="300"/>
-</p>
+![slice.png](../../../images/cute/slice.png)
 
 In the image above, a `Tensor` is sliced in various ways and the subtensors generated by those slices are highlighted within the original tensor. Note that tensor `C` and `D` contain the same elements, but have different ranks and shapes due to the use of `_` versus the use of `make_coord(_,_)`. In each case, the rank of the result is equal to the number of `Underscore`s in the slicing coordinate.
 
@@ -327,9 +325,7 @@ Tensor tv = composition(A, tv_layout);                           // (8,4)
 Tensor  v = tv(threadIdx.x, _);                                  // (4)
 ```
 
-<p align="center">
-  <img src="../../../images/cute/tv_layout.png" alt="tv_layout.png" height="300"/>
-</p>
+![tv_layout.png](../../../images/cute/tv_layout.png)
 
 The above image is a visual representation of the above code. An arbitrary 4x8 layout of data is composed with a specific 8x4 TV-layout that represents a partitioning pattern. The result of the composition is on the right where each threads' values are arranged across each row. The bottom layout depicts the inverse TV layout which shows the mapping of 4x8 logical coordinates to the thread id and value id they will be mapped to.