Fix comments

CHANGELOG.md

@@ -19,6 +19,7 @@ None
 - Support for NHWGC (2D and 3D) grouped convolution backward weight (#769 #804)
 - Support for bf16/f32/f16 and NHWGC (2D and 3D) grouped convolution backward data (#757 #799)
 - Support for Batched Gemm DL (#732)
+- Introduce wrapper sublibrary (limited functionality) (#1071)
 
 ### Changes
  - Changed the grouped convolution API to maintain consistency with other convolution kernels (#817)

client_example/25_tensor_transforms/CMakeLists.txt

 add_executable(client_tensor_transform tensor_transform.cpp)
+target_link_libraries(client_tensor_transform PRIVATE composable_kernel::device_other_operations)
 add_executable(client_tensor_transform_using_wrapper tensor_transform_using_wrapper.cpp)
+target_link_libraries(client_tensor_transform_using_wrapper PRIVATE composable_kernel::device_other_operations)

docs/index.rst

@@ -34,7 +34,7 @@ Current CK library are structured into 4 layers:
 * "Templated Tile Operators" layer
 * "Templated Kernel and Invoker" layer
 * "Instantiated Kernel and Invoker" layer
-* "Wrapper for tensor tranforms operations"
+* "Wrapper for tensor transform operations"
 * "Client API" layer
 
 .. image:: data/ck_layer.png

docs/wrapper.rst

@@ -5,8 +5,11 @@ Wrapper
 -------------------------------------
 Description
 -------------------------------------
-Note: Wrapper is currently under development. At the moment, its functionality 
-is limited.
+
+.. note::
+
+    The wrapper is under development and its functionality is limited.
+
 
 CK provides a lightweight wrapper for more complex operations implemented in 
 the library. It allows indexing of nested layouts using a simple interface 
@@ -33,7 +36,6 @@ Example:
 Output::
 
     dims:4,(2,4) strides:2,(1,8)
-    Print2d
     0 1 8 9 16 17 24 25 
     2 3 10 11 18 19 26 27 
     4 5 12 13 20 21 28 29 

include/ck/wrapper/layout.hpp

@@ -109,7 +109,7 @@ struct Layout
             // Iterate over shape tuple elements:
             // 1. If corresponding idx element is tuple then return (will be unrolled)
             // 2. If no, pack in tuple. It will be restored during unroll.
-            auto unrolled_shape_via_idx = generate_tuple(
+            auto aligned_shape = generate_tuple(
                 [&](auto i) {
                     if constexpr(is_detected<is_tuple,
                                              tuple_element_t<i, Tuple<IdxDims...>>>::value)
@@ -124,7 +124,7 @@ struct Layout
                 Number<Tuple<IdxDims...>::Size()>{});
 
             // Unroll and process next step
-            return AlignShapeToIdx(UnrollNestedTuple<0, 1>(unrolled_shape_via_idx),
+            return AlignShapeToIdx(UnrollNestedTuple<0, 1>(aligned_shape),
                                    UnrollNestedTuple<0, 1>(idx));
         }
     }
@@ -144,7 +144,7 @@ struct Layout
             desc, make_tuple(make_merge_transform(merge_elems)), lower_dims, upper_dims);
     }
 
-    // Merge nested shape dims
+    // Merge nested shape dims. Merge nested shape dims when idx is also nested.
     // Input desc shape: 2,  2,  2, 2,  2,  2
     // Example idx:      1,      1, 1,      1
     // Example shape:    2, (2, 2), 2, (2, 2)
@@ -205,10 +205,9 @@ struct Layout
             static_assert(Tuple<ShapeDims...>::Size() == Tuple<IdxDims...>::Size(),
                           "Idx rank and Shape rank must be the same (except 1d).");
             // Unroll while IdxDims is nested
-            const auto unrolled_shape_via_idx = AlignShapeToIdx(shape, idx);
+            const auto aligned_shape = AlignShapeToIdx(shape, idx);
             // Transform correct form of shape
-            return CreateMergedDescriptor(
-                unrolled_shape_via_idx, UnrollNestedTuple(idx), descriptor_);
+            return CreateMergedDescriptor(aligned_shape, UnrollNestedTuple(idx), descriptor_);
         }
     }
 
@@ -224,7 +223,7 @@ struct Layout
     }
 
     public:
-    // If stride not passed, deduce from GenerateColumnMajorPackedStrides
+    // If the stride is not passed, you can infer it from `GenerateColumnMajorPackedStrides`.
     using DeducedStrides =
         std::conditional_t<is_same_v<Strides, Tuple<>>,
                            remove_cvref_t<decltype(GenerateColumnMajorPackedStrides(Shape{}))>,

test/wrapper/test_layout.cpp

@@ -356,7 +356,7 @@ TEST(TestLayoutHelpers, SizeAndGet)
     EXPECT_EQ(ck::wrapper::size<1>(layout_runtime), d1 * d0);
     EXPECT_EQ(ck::wrapper::size<1>(layout_compiletime), d1 * d0);
 
-    // Acces via new layout (using get on layout)
+    // Access through new layout (using get with layout object)
     EXPECT_EQ(ck::wrapper::size<0>(ck::wrapper::get<0>(layout_runtime)), d4 * d3);
     EXPECT_EQ(ck::wrapper::size<0>(ck::wrapper::get<0>(layout_compiletime)), d4 * d3);
     EXPECT_EQ(ck::wrapper::size<1>(ck::wrapper::get<0>(layout_runtime)), d2);