leavelet/cutlass
1
0
Fork 0
Code Issues Pull Requests Actions 26 Packages Projects Releases Wiki Activity

Fix typos in cute docs (#1486)

Browse Source 
* fix typos in 02_layout_algebra.md

* fix typos in 03_tensor.md
This commit is contained in:
Sin
2024-05-02 15:34:36 -04:00
committed by GitHub
parent 5c447dd84f
commit acc3ee18a1
3 changed files with 15 additions and 11 deletions
Download Patch File Download Diff File Expand all files Collapse all files
media/docs/cute/03_tensor.md
+12 -8
View File
@@ -157,8 +157,8 @@ Tensor rmem_4x8_col = make_tensor<float>(Shape<_4,_8>{});
Tensor rmem_4x8_row = make_tensor<float>(Shape<_4,_8>{},
LayoutRight{});
Tensor rmem_4x8_pad = make_tensor<float>(Shape <_4, _8>{},
Stride<_2,_32>{});
Tensor rmem_4x8_like = make_tensor_like(smem_4x8_pad);
Stride<_32,_2>{});
Tensor rmem_4x8_like = make_tensor_like(rmem_4x8_pad);
```
The `make_tensor_like` function makes an owning Tensor of register memory with the same value type and shape as its input `Tensor` argument and attempts to use the same order of strides as well.
@@ -168,7 +168,7 @@ Calling `print` on each of the above tensors produces similar output
```
rmem_4x8_col : ptr[32b](0x7ff1c8fff820) o (_4,_8):(_1,_4)
rmem_4x8_row : ptr[32b](0x7ff1c8fff8a0) o (_4,_8):(_8,_1)
rmem_4x8_pad : ptr[32b](0x7ff1c8fff920) o (_4,_8):(_2,_32)
rmem_4x8_pad : ptr[32b](0x7ff1c8fff920) o (_4,_8):(_32,_2)
rmem_4x8_like : ptr[32b](0x7f4158fffc60) o (_4,_8):(_8,_1)
```
@@ -194,8 +194,9 @@ decltype(auto) operator[](Coord const& coord) {
For example, we can read and write to `Tensor`s using natural coordinates, using the variadic `operator()`, or the container-like `operator[]`.
```c++
Tensor A = make_tensor<float>(Shape <Shape < _4,_5>,_13>{},
Tensor A = make_tensor<float>(Shape <Shape < _4,_5>,Int<13>>{},
Stride<Stride<_12,_1>,_64>{});
float* b_ptr = ...;
Tensor B = make_tensor(b_ptr, make_shape(13, 20));
// Fill A via natural coordinates op[]
@@ -261,8 +262,11 @@ Tensor C = A(_,5);
// (_3,2):(4,1)
Tensor D = A(make_coord(_,_),5);
// (_3,_5):(4,13)
Tensor E = A(make_coord(_,1),make_coord(0,_,1));
// (2,2,_2):(1,_2,100)
Tensor E = A(make_coord(2,_),make_coord(_,3,_));
Tensor F = A(make_coord(2,_),make_coord(_,3,_));
```
<p align="center">
@@ -280,8 +284,8 @@ To implement generic partitioning of a `Tensor`, we apply composition or tiling
Let's take a tiled example and look at how we can slice it in useful ways.
```cpp
Tensor A = make_tensor(ptr, make_shape(24,8)); // (8,24)
auto tiler = Shape<_8,_4>{}; // (_4,_8)
Tensor A = make_tensor(ptr, make_shape(8,24)); // (8,24)
auto tiler = Shape<_4,_8>{}; // (_4,_8)
Tensor tiled_a = zipped_divide(A, tiler); // ((_4,_8),(2,3))
```
@@ -313,7 +317,7 @@ Another common partitioning strategy is called a thread-value partitioning. In t
// to 1D coordinates within a 4x8 tensor
// (T8,V4) -> (M4,N8)
auto tv_layout = Layout<Shape <Shape <_2,_4>,Shape <_2, _2>>,
Stride<Stride<_8,_1>,Stride<_4,_16>>{}; // (8,4)
Stride<Stride<_8,_1>,Stride<_4,_16>>>{}; // (8,4)
// Construct a 4x8 tensor with any layout
Tensor A = make_tensor<float>(Shape<_4,_8>{}, LayoutRight{}); // (4,8)