Introduce wrapper library

client_example/25_tensor_transforms/CMakeLists.txt

+add_executable(client_tensor_transform tensor_transform.cpp)
+add_executable(client_tensor_transform_using_wrapper tensor_transform_using_wrapper.cpp)

example/64_tensor_transforms/tensor_transform_using_wrapper.cpp → client_example/25_tensor_transforms/tensor_transform_using_wrapper.cpp

@@ -9,7 +9,7 @@
 #include "ck/utility/tuple.hpp"
 #include "ck/utility/sequence.hpp"
 
-#include "tensor_transform_wrapper.hpp"
+#include "ck/wrapper/layout.hpp"
 
 using DataType = int;
 
@@ -17,7 +17,7 @@ template <typename Layout>
 void Print1d(const Layout& layout)
 {
     std::cout << "Print1d" << std::endl;
-    for(ck::index_t w = 0; w < ck::tensor_transform_wrapper::size(layout); w++)
+    for(ck::index_t w = 0; w < ck::wrapper::size(layout); w++)
     {
         std::cout << layout(ck::make_tuple(w)) << " ";
     }
@@ -28,9 +28,9 @@ template <typename Layout>
 void Print2d(const Layout& layout)
 {
     std::cout << "Print2d" << std::endl;
-    for(ck::index_t h = 0; h < ck::tensor_transform_wrapper::size<0>(layout); h++)
+    for(ck::index_t h = 0; h < ck::wrapper::size<0>(layout); h++)
     {
-        for(ck::index_t w = 0; w < ck::tensor_transform_wrapper::size<1>(layout); w++)
+        for(ck::index_t w = 0; w < ck::wrapper::size<1>(layout); w++)
         {
             std::cout << layout(ck::make_tuple(h, w)) << " ";
         }
@@ -43,15 +43,11 @@ template <typename Layout>
 void Print3dCustom(const Layout& layout)
 {
     std::cout << "Print3dCustom" << std::endl;
-    for(ck::index_t d = 0;
-        d < ck::tensor_transform_wrapper::size<0>(ck::tensor_transform_wrapper::get<0>(layout));
-        d++)
+    for(ck::index_t d = 0; d < ck::wrapper::size<0>(ck::wrapper::get<0>(layout)); d++)
     {
-        for(ck::index_t h = 0;
-            h < ck::tensor_transform_wrapper::size<1>(ck::tensor_transform_wrapper::get<0>(layout));
-            h++)
+        for(ck::index_t h = 0; h < ck::wrapper::size<1>(ck::wrapper::get<0>(layout)); h++)
         {
-            for(ck::index_t w = 0; w < ck::tensor_transform_wrapper::size<1>(layout); w++)
+            for(ck::index_t w = 0; w < ck::wrapper::size<1>(layout); w++)
             {
                 std::cout << layout(ck::make_tuple(ck::make_tuple(d, h), w)) << " ";
             }
@@ -68,7 +64,7 @@ int main()
     // Basic descriptor 0, 1, 2, ... 30, 31 (compile-time descriptor)
     // (dims:4,8 strides:1,4)
     const auto shape_4x8       = ck::make_tuple(ck::Number<4>{}, ck::Number<8>{});
-    const auto layout_4x8_s1x4 = ck::tensor_transform_wrapper::make_layout(shape_4x8);
+    const auto layout_4x8_s1x4 = ck::wrapper::make_layout(shape_4x8);
     std::cout << "dims:4,8 strides:1,4" << std::endl;
     Print2d(layout_4x8_s1x4);
     using Cord1x1Type                = ck::Tuple<ck::Number<1>, ck::Number<1>>;
@@ -77,10 +73,9 @@ int main()
 
     // Basic descriptor 0, 1, 8, 9, 16, 17, ... 30, 31 (runtime descriptor)
     // dims:4,(2,4) strides:2,(1,8)
-    const auto shape_4x2x4    = ck::make_tuple(4, ck::make_tuple(2, 4));
-    const auto strides_s2x1x8 = ck::make_tuple(2, ck::make_tuple(1, 8));
-    const auto layout_4x2x4_s2x1x8 =
-        ck::tensor_transform_wrapper::make_layout(shape_4x2x4, strides_s2x1x8);
+    const auto shape_4x2x4         = ck::make_tuple(4, ck::make_tuple(2, 4));
+    const auto strides_s2x1x8      = ck::make_tuple(2, ck::make_tuple(1, 8));
+    const auto layout_4x2x4_s2x1x8 = ck::wrapper::make_layout(shape_4x2x4, strides_s2x1x8);
 
     std::cout << "dims:4,(2,4) strides:2,(1,8)" << std::endl;
     Print2d(layout_4x2x4_s2x1x8);
@@ -92,7 +87,7 @@ int main()
     const auto strides_s1x4x2x8 = ck::make_tuple(ck::make_tuple(ck::Number<1>{}, ck::Number<4>{}),
                                                  ck::make_tuple(ck::Number<2>{}, ck::Number<8>{}));
     static const auto layout_2x2x2x4_s1x4x2x8 =
-        ck::tensor_transform_wrapper::make_layout(shape_2x2x2x4, strides_s1x4x2x8);
+        ck::wrapper::make_layout(shape_2x2x2x4, strides_s1x4x2x8);
 
     std::cout << "dims:(2,2),(2,4) strides:(1,4),(2,8)" << std::endl;
     Print2d(layout_2x2x2x4_s1x4x2x8);
@@ -108,7 +103,7 @@ int main()
         ck::make_tuple(ck::make_tuple(ck::Number<1>{}, ck::Number<4>{}), ck::Number<2>{}),
         ck::Number<8>{});
     static const auto layout_2x2x2x4_s1x4x2x8_nested =
-        ck::tensor_transform_wrapper::make_layout(shape_2x2x2x4_nested, strides_s1x4x2x8_nested);
+        ck::wrapper::make_layout(shape_2x2x2x4_nested, strides_s1x4x2x8_nested);
 
     std::cout << "dims:((2,2),2),4 strides:((1,4),2),8" << std::endl;
     Print1d(layout_2x2x2x4_s1x4x2x8_nested);

docs/doxygen/Doxyfile

@@ -778,7 +778,9 @@ WARN_LOGFILE           =
 INPUT                  = ../../include/ck/tensor_operation/gpu/grid \
                          ../../include/ck/tensor_operation/gpu/block \
                          ../../include/ck/tensor_operation/gpu/thread \
-                         ../../library/include/ck/library/utility
+                         ../../library/include/ck/library/utility \
+                         ../../include/ck/wrapper
+
 
 # This tag can be used to specify the character encoding of the source files
 # that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses

docs/index.rst

@@ -34,6 +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"
 * "Client API" layer
 
 .. image:: data/ck_layer.png
@@ -50,6 +51,7 @@ The following is a list of CK documents in the suggested reading order:
 
    tutorial_hello_world
    dockerhub
+   wrapper
    Supported_Primitives_Guide
    API_Reference_Guide
    Contributors_Guide

docs/wrapper.rst

+===============
+Wrapper
+===============
+
+-------------------------------------
+Description
+-------------------------------------
+Note: Wrapper is currently under development. At the moment, 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 
+(avoiding complex descriptor transformations). 
+
+Example:
+
+.. code-block:: c
+
+    const auto shape_4x2x4         = ck::make_tuple(4, ck::make_tuple(2, 4));
+    const auto strides_s2x1x8      = ck::make_tuple(2, ck::make_tuple(1, 8));
+    const auto layout = ck::wrapper::make_layout(shape_4x2x4, strides_s2x1x8);
+
+    std::cout << "dims:4,(2,4) strides:2,(1,8)" << std::endl;
+    for(ck::index_t h = 0; h < ck::wrapper::size<0>(layout); h++)
+    {
+        for(ck::index_t w = 0; w < ck::wrapper::size<1>(layout); w++)
+        {
+            std::cout << layout(ck::make_tuple(h, w)) << " ";
+        }
+        std::cout << std::endl;
+    }
+
+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 
+    6 7 14 15 22 23 30 31 
+
+-------------------------------------
+Layout
+-------------------------------------
+
+.. doxygenstruct:: ck::wrapper::Layout
+
+-------------------------------------
+Layout helpers
+-------------------------------------
+
+.. doxygenfile:: layout_utils.hpp

example/64_tensor_transforms/CMakeLists.txt

-add_example_executable(example_tensor_transform tensor_transform.cpp)
-add_example_executable(example_tensor_transform_using_wrapper tensor_transform_using_wrapper.cpp)

include/ck/utility/tuple_helper.hpp

@@ -166,4 +166,16 @@ __host__ __device__ constexpr auto IsNestedTuple(const Tuple<Ts...>&)
     return (is_detected<is_tuple, Ts>::value || ...);
 }
 
+template <index_t depth = 0, typename T>
+__host__ __device__ constexpr auto TupleDepth(const T&)
+{
+    return depth;
+}
+
+template <index_t depth = 0, typename... Ts>
+__host__ __device__ constexpr auto TupleDepth(const Tuple<Ts...>&)
+{
+    return math::max(TupleDepth<depth + 1>(Ts{})...);
+}
+
 } // namespace ck

example/64_tensor_transforms/tensor_transform_wrapper.hpp → include/ck/wrapper/layout.hpp

@@ -3,27 +3,13 @@
 
 #pragma once
 
-#include "ck/ck.hpp"
-
-#include "ck/utility/number.hpp"
-#include "ck/utility/tuple.hpp"
-#include "ck/utility/tuple_helper.hpp"
-#include "ck/utility/sequence.hpp"
-#include "ck/utility/sequence_helper.hpp"
-#include "ck/utility/is_detected.hpp"
-
-#include "ck/tensor_description/tensor_descriptor.hpp"
-#include "ck/tensor_description/tensor_descriptor_helper.hpp"
-#include "ck/tensor_description/multi_index_transform_helper.hpp"
+#include "ck/wrapper/layout_utils.hpp"
 
 namespace ck {
-namespace tensor_transform_wrapper {
+namespace wrapper {
 
 /**
- * \brief Layout wrapper
- *
- * \details
- * Layout wrapper that performs the tensor descriptor logic.
+ * \brief Layout wrapper that performs the tensor descriptor logic.
  *
  * \tparam Shape Tuple of Number<> (for compile-time layout) or index_t
  *         (dynamic layout). It is possible to pass nested shapes
@@ -32,21 +18,19 @@ namespace tensor_transform_wrapper {
  *         (dynamic layout). Stride tuple should be nested if shape tuple is
  *         nested.
  */
-template <typename Shape, typename Strides = Tuple<>>
+template <typename Shape, typename Strides>
 struct Layout
 {
     private:
     static constexpr auto I0 = Number<0>{};
     static constexpr auto I1 = Number<1>{};
 
-    template <typename T>
-    using is_tuple = decltype(std::declval<T&>().IsTuple());
-
     // Generate packed (column-major) strides if not passed
     template <typename... Ts>
     __host__ __device__ constexpr static auto
-    GenerateColumnMajorPackedStrides(const Tuple<Ts...>& tuple)
+    GenerateColumnMajorPackedStrides(const Tuple<Ts...>& shape)
     {
+        const auto unrolled_shape = UnrollNestedTuple(shape);
         return generate_tuple(
             [&](auto i) {
                 if constexpr(i.value == 0)
@@ -56,10 +40,10 @@ struct Layout
                 else
                 {
                     return TupleReduce<I0.value, i.value>([](auto x, auto y) { return x * y; },
-                                                          tuple);
+                                                          unrolled_shape);
                 }
             },
-            Number<Tuple<Ts...>::Size()>{});
+            Number<decltype(unrolled_shape)::Size()>{});
     }
 
     // Generate LowerDims in Compile-time for MergeTrasform using passed Type
@@ -112,8 +96,8 @@ struct Layout
     // Example shape:   (2, (2, 2)), 2, (2, 2)
     // Unrolled shape:  2,  (2, 2),  2, (2, 2)
     template <typename... ShapeDims, typename... IdxDims>
-    __host__ __device__ constexpr static auto UnrollShapeViaIdx(const Tuple<ShapeDims...>& shape,
-                                                                const Tuple<IdxDims...>& idx)
+    __host__ __device__ constexpr static auto AlignShapeToIdx(const Tuple<ShapeDims...>& shape,
+                                                              const Tuple<IdxDims...>& idx)
     {
         if constexpr(!IsNestedTuple(Tuple<IdxDims...>{}))
         {
@@ -140,8 +124,8 @@ struct Layout
                 Number<Tuple<IdxDims...>::Size()>{});
 
             // Unroll and process next step
-            return UnrollShapeViaIdx(UnrollNestedTuple<0, 1>(unrolled_shape_via_idx),
-                                     UnrollNestedTuple<0, 1>(idx));
+            return AlignShapeToIdx(UnrollNestedTuple<0, 1>(unrolled_shape_via_idx),
+                                   UnrollNestedTuple<0, 1>(idx));
         }
     }
 
@@ -150,14 +134,11 @@ struct Layout
                                                           DescriptorToMerge& desc)
     {
         // Reverse each element in tuple
-        using ReversedUnrolledShape = decltype(TupleReverse(UnrollNestedTuple(shape)));
-        const auto merge_elems      = ReversedUnrolledShape{};
-
+        const auto merge_elems = TupleReverse(UnrollNestedTuple(shape));
         // Generate reverted indexes (column major traverse)
-        using MergeElemsSequence =
-            typename arithmetic_sequence_gen<0, ReversedUnrolledShape::Size(), 1>::type;
-        const auto lower_dims = make_tuple(MergeElemsSequence::Reverse());
-        const auto upper_dims = make_tuple(Sequence<0>{});
+        using MergeElemsSequence = typename arithmetic_sequence_gen<0, merge_elems.Size(), 1>::type;
+        const auto lower_dims    = make_tuple(MergeElemsSequence::Reverse());
+        const auto upper_dims    = make_tuple(Sequence<0>{});
         // Merge to 1d
         return transform_tensor_descriptor(
             desc, make_tuple(make_merge_transform(merge_elems)), lower_dims, upper_dims);
@@ -169,8 +150,8 @@ struct Layout
     // Example shape:    2, (2, 2), 2, (2, 2)
     // Merged shape:     2,      4, 2,      4
     template <typename... ShapeDims, typename... IdxDims, typename DescriptorToMerge>
-    __host__ __device__ constexpr static auto
-    MakeMerges(const Tuple<ShapeDims...>& shape, const Tuple<IdxDims...>&, DescriptorToMerge& desc)
+    __host__ __device__ constexpr static auto CreateMergedDescriptor(
+        const Tuple<ShapeDims...>& shape, const Tuple<IdxDims...>&, DescriptorToMerge& desc)
     {
         const auto transforms = generate_tuple(
             [&](auto i) {
@@ -224,9 +205,10 @@ 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 = UnrollShapeViaIdx(shape, idx);
+            const auto unrolled_shape_via_idx = AlignShapeToIdx(shape, idx);
             // Transform correct form of shape
-            return MakeMerges(unrolled_shape_via_idx, UnrollNestedTuple(idx), descriptor_);
+            return CreateMergedDescriptor(
+                unrolled_shape_via_idx, UnrollNestedTuple(idx), descriptor_);
         }
     }
 
@@ -234,26 +216,21 @@ struct Layout
     __host__ __device__ static auto MakeNaiveDescriptor(const LayoutShape& shape,
                                                         const LayoutStrides& strides)
     {
-        const auto unrolled_shape = UnrollNestedTuple(shape);
-
-        if constexpr(ck::is_same_v<LayoutStrides, Tuple<>>)
-        {
-            // If shape is packed
-            const auto column_major_packed_strides =
-                GenerateColumnMajorPackedStrides(unrolled_shape);
-            return make_naive_tensor_descriptor(unrolled_shape, column_major_packed_strides);
-        }
-        else
-        {
-            const auto unrolled_strides = UnrollNestedTuple(strides);
-            static_assert(unrolled_shape.Size() == unrolled_strides.Size(),
-                          "Size of strides and shape are not consistent.");
-            return make_naive_tensor_descriptor(unrolled_shape, unrolled_strides);
-        }
+        const auto unrolled_shape   = UnrollNestedTuple(shape);
+        const auto unrolled_strides = UnrollNestedTuple(strides);
+        static_assert(unrolled_shape.Size() == unrolled_strides.Size(),
+                      "Size of strides and shape are not consistent.");
+        return make_naive_tensor_descriptor(unrolled_shape, unrolled_strides);
     }
 
     public:
-    using NaiveDescriptorType = remove_cvref_t<decltype(MakeNaiveDescriptor(Shape{}, Strides{}))>;
+    // If stride not passed, deduce from GenerateColumnMajorPackedStrides
+    using DeducedStrides =
+        std::conditional_t<is_same_v<Strides, Tuple<>>,
+                           remove_cvref_t<decltype(GenerateColumnMajorPackedStrides(Shape{}))>,
+                           Strides>;
+    using NaiveDescriptorType =
+        remove_cvref_t<decltype(MakeNaiveDescriptor(Shape{}, DeducedStrides{}))>;
 
     /**
      * \brief Layout constructor.
@@ -268,9 +245,9 @@ struct Layout
         // Construct if runtime mode
         if constexpr(!NaiveDescriptorType::IsKnownAtCompileTime())
         {
-            // Keep only shape, strides are not need for transforms
             shape_      = shape;
-            descriptor_ = MakeNaiveDescriptor(shape, strides);
+            strides_    = strides;
+            descriptor_ = MakeNaiveDescriptor(shape_, strides_);
         }
     }
 
@@ -279,7 +256,8 @@ struct Layout
         if constexpr(!NaiveDescriptorType::IsKnownAtCompileTime())
         {
             shape_      = shape;
-            descriptor_ = MakeNaiveDescriptor(shape, Strides{});
+            strides_    = GenerateColumnMajorPackedStrides(shape_);
+            descriptor_ = MakeNaiveDescriptor(shape_, strides_);
         }
     }
 
@@ -338,7 +316,7 @@ struct Layout
      *
      * \return Calculated size.
      */
-    __host__ __device__ constexpr index_t GetLength() const
+    __host__ __device__ constexpr index_t GetLengths() const
     {
         const auto unrolled_shape = UnrollNestedTuple(shape_);
         return TupleReduce<I0.value, unrolled_shape.Size()>([](auto x, auto y) { return x * y; },
@@ -346,80 +324,24 @@ struct Layout
     }
 
     /**
-     * \brief Dimension getter.
+     * \brief Shape getter.
      *
-     * \tparam IDim Dimension idx.
-     * \return Calculated size.
+     * \return Shape.
      */
-    template <index_t IDim>
-    __host__ __device__ constexpr auto Get() const
-    {
-        const auto elem = shape_.At(Number<IDim>{});
-        return elem;
-    }
+    __host__ __device__ constexpr Shape GetShape() const { return shape_; }
+
+    /**
+     * \brief Strides getter.
+     *
+     * \return Strides.
+     */
+    __host__ __device__ constexpr DeducedStrides GetStrides() const { return strides_; }
 
     private:
     NaiveDescriptorType descriptor_;
     Shape shape_;
+    DeducedStrides strides_;
 };
 
-// Layout helpers
-// Length getter (product if tuple)
-template <index_t idx, typename Shape, typename Strides>
-__host__ __device__ constexpr index_t size(const Layout<Shape, Strides>& layout)
-{
-    return layout.template GetLength<idx>();
-}
-
-// Get shape size (product of dims if tuple)
-template <typename... ShapeDims>
-__host__ __device__ constexpr index_t size(const Tuple<ShapeDims...>& shape)
-{
-    using UnrolledShape = decltype(UnrollNestedTuple(shape));
-    return TupleReduce<0, UnrolledShape::Size()>([](auto x, auto y) { return x * y; },
-                                                 UnrolledShape{});
-}
-
-// Get dim size (could be returned from get function)
-template <typename T>
-__host__ __device__ T constexpr size(const T& dim)
-{
-    return dim;
-}
-
-// Get layout size (product of shapes)
-template <typename Shape, typename Strides>
-__host__ __device__ constexpr index_t size(const Layout<Shape, Strides>& layout)
-{
-    return layout.GetLength();
-}
-
-// Get shape element size
-template <index_t idx, typename... ShapeDims>
-__host__ __device__ constexpr index_t size(const Tuple<ShapeDims...>& shape)
-{
-    return size(shape.At(Number<idx>{}));
-}
-
-// Dim getter (tuple if tuple)
-template <index_t idx, typename Shape, typename Strides>
-__host__ __device__ constexpr auto get(const Layout<Shape, Strides>& layout)
-{
-    return layout.template Get<idx>();
-}
-
-template <typename Shape, typename Strides>
-__host__ __device__ constexpr Layout<Shape, Strides> make_layout(const Shape& shape,
-                                                                 const Strides& strides)
-{
-    return Layout<Shape, Strides>(shape, strides);
-}
-
-template <typename Shape>
-__host__ __device__ constexpr Layout<Shape> make_layout(const Shape& shape)
-{
-    return Layout<Shape>(shape);
-}
-
-} // namespace tensor_transform_wrapper
+} // namespace wrapper
 } // namespace ck

include/ck/wrapper/layout_utils.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include "ck/ck.hpp"
+
+#include "ck/utility/number.hpp"
+#include "ck/utility/tuple.hpp"
+#include "ck/utility/tuple_helper.hpp"
+#include "ck/utility/sequence.hpp"
+#include "ck/utility/sequence_helper.hpp"
+#include "ck/utility/is_detected.hpp"
+
+#include "ck/tensor_description/tensor_descriptor.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+#include "ck/tensor_description/multi_index_transform_helper.hpp"
+
+namespace ck {
+namespace wrapper {
+
+// Disable from doxygen docs generation
+/// @cond
+// forward declaration
+template <typename Shape, typename Strides = Tuple<>>
+struct Layout;
+
+template <typename T>
+using is_tuple = decltype(std::declval<T&>().IsTuple());
+/// @endcond
+
+// make_*
+/**
+ * \brief Make layout function.
+ *
+ * \tparam Shape Shape for layout.
+ * \tparam Strides Strides for layout.
+ * \return Constructed layout.
+ */
+template <typename Shape, typename Strides>
+__host__ __device__ constexpr Layout<Shape, Strides> make_layout(const Shape& shape,
+                                                                 const Strides& strides)
+{
+    return Layout<Shape, Strides>(shape, strides);
+}
+
+/**
+ * \brief Make layout function with packed strides
+ *        (column-major).
+ *
+ * \tparam Shape Shape for layout.
+ * \return Constructed layout.
+ */
+template <typename Shape>
+__host__ __device__ constexpr Layout<Shape> make_layout(const Shape& shape)
+{
+    return Layout<Shape>(shape);
+}
+
+// Layout helpers
+// get
+/**
+ * \brief Get element from tuple (Shape/Strides/Idxs).
+ *
+ * \tparam idx Index to lookup.
+ * \param tuple Tuple to lookup.
+ * \return Requsted element.
+ */
+template <index_t idx, typename... Dims>
+__host__ __device__ constexpr auto get(const Tuple<Dims...>& tuple)
+{
+    return tuple.At(Number<idx>{});
+}
+
+/**
+ * \brief Get sub layout.
+ *
+ * \tparam idx Index to lookup.
+ * \param layout Layout to create sub layout.
+ * \return Requsted sub layout.
+ */
+template <index_t idx, typename Shape, typename Strides>
+__host__ __device__ constexpr auto get(const Layout<Shape, Strides>& layout)
+{
+    const auto new_shape = get<idx>(layout.GetShape());
+    static_assert(is_detected<is_tuple, decltype(new_shape)>::value,
+                  "Shape of sub layout must be tuple");
+    if constexpr(is_same_v<Strides, Tuple<>>)
+    {
+        // If stride not passed, create without strides
+        return make_layout(new_shape);
+    }
+    else
+    {
+        const auto new_strides = get<idx>(layout.GetStrides());
+        static_assert(is_detected<is_tuple, decltype(new_strides)>::value,
+                      "Strides of sub layout must be tuple");
+        return make_layout(new_shape, new_strides);
+    }
+}
+
+/**
+ * \brief Hierarchical get.
+ *
+ * \tparam Idxs Indexes to lookup.
+ * \param elem Element to lookup.
+ * \return Requsted element.
+ */
+template <index_t Idx, index_t... Idxs, typename T>
+__host__ __device__ constexpr auto get(const T& elem)
+{
+    return get<Idxs...>(get<Idx>(elem));
+}
+
+// size
+/**
+ * \brief Length get (product if tuple).
+ *
+ * \tparam idx Index to lookup.
+ * \param layout Layout to get Shape.
+ * \return Requsted length.
+ */
+template <index_t idx, typename Shape, typename Strides>
+__host__ __device__ constexpr index_t size(const Layout<Shape, Strides>& layout)
+{
+    return layout.template GetLength<idx>();
+}
+
+/**
+ * \brief Shape size (product of dims).
+ *
+ * \param shape Shape to lookup.
+ * \return Requsted size.
+ */
+template <typename... ShapeDims>
+__host__ __device__ constexpr index_t size(const Tuple<ShapeDims...>& shape)
+{
+    const auto unrolled_shape = UnrollNestedTuple(shape);
+    return TupleReduce<0, unrolled_shape.Size()>([](auto x, auto y) { return x * y; },
+                                                 unrolled_shape);
+}
+
+// Get dim size (could be returned from get function)
+/**
+ * \private
+ */
+template <typename T>
+__host__ __device__ T constexpr size(const T& dim)
+{
+    return dim;
+}
+
+/**
+ * \brief Layout size (product of dims).
+ *
+ * \param layout Layout to calculate shape size.
+ * \return Requsted size.
+ */
+template <typename Shape, typename Strides>
+__host__ __device__ constexpr index_t size(const Layout<Shape, Strides>& layout)
+{
+    return layout.GetLengths();
+}
+
+/**
+ * \brief Length get from tuple (product if tuple).
+ *
+ * \tparam idx Index to lookup.
+ * \param tuple Tuple to lookup.
+ * \return Requsted length.
+ */
+template <index_t idx, typename... Ts>
+__host__ __device__ constexpr index_t size(const Tuple<Ts...>& tuple)
+{
+    return size(tuple.At(Number<idx>{}));
+}
+
+/**
+ * \brief Hierarchical size.
+ *
+ * \tparam Idxs Indexes to lookup.
+ * \param elem Element to lookup.
+ * \return Requsted element.
+ */
+template <index_t... Idxs, typename T>
+__host__ __device__ constexpr auto size(const T& elem)
+{
+    return size(get<Idxs...>(elem));
+}
+
+// rank
+/**
+ * \brief Get layout rank (num elements in shape).
+ *
+ * \param layout Layout to calculate rank.
+ * \return Requsted rank.
+ */
+template <typename Shape, typename Strides>
+__host__ __device__ constexpr auto rank([[maybe_unused]] const Layout<Shape, Strides>& layout)
+{
+    return Shape::Size();
+}
+
+/**
+ * \brief Get tuple rank (num elements in tuple).
+ *        Return 1 if scalar passed.
+ *
+ * \param tuple Tuple to calculate rank.
+ * \return Requsted rank.
+ */
+template <typename... Dims>
+__host__ __device__ constexpr auto rank([[maybe_unused]] const Tuple<Dims...>& tuple)
+{
+    return Tuple<Dims...>::Size();
+}
+
+/**
+ * \private
+ */
+template <index_t IDim>
+__host__ __device__ constexpr index_t rank(const Number<IDim>&)
+{
+    return 1;
+}
+
+/**
+ * \private
+ */
+__host__ __device__ constexpr index_t rank(const index_t&) { return 1; }
+
+/**
+ * \brief Hierarchical rank.
+ *
+ * \tparam Idxs Indexes to lookup.
+ * \param elem Element to lookup.
+ * \return Requsted rank.
+ */
+template <index_t... Idxs, typename T>
+__host__ __device__ constexpr auto rank(const T& elem)
+{
+    return rank(get<Idxs...>(elem));
+}
+
+// depth
+/**
+ * \brief Get depth of the layout shape (return 0 if scalar).
+ *
+ * \param layout Layout to calculate depth.
+ * \return Requsted depth.
+ */
+template <typename Shape, typename Strides>
+__host__ __device__ constexpr auto depth(const Layout<Shape, Strides>& layout)
+{
+    return TupleDepth(layout.GetShape());
+}
+
+/**
+ * \brief Get depth of the tuple. (return 0 if scalar)
+ *
+ * \param tuple Tuple to calculate depth.
+ * \return Requsted depth.
+ */
+template <typename... Dims>
+__host__ __device__ constexpr auto depth(const Tuple<Dims...>& tuple)
+{
+    return TupleDepth(tuple);
+}
+
+/**
+ * \private
+ */
+template <index_t IDim>
+__host__ __device__ constexpr index_t depth(const Number<IDim>&)
+{
+    return 0;
+}
+
+/**
+ * \private
+ */
+__host__ __device__ constexpr index_t depth(const index_t&) { return 0; }
+
+/**
+ * \brief Hierarchical depth.
+ *
+ * \tparam Idxs Indexes to lookup.
+ * \param elem Element to lookup.
+ * \return Requsted depth.
+ */
+template <index_t... Idxs, typename T>
+__host__ __device__ constexpr auto depth(const T& elem)
+{
+    return depth(get<Idxs...>(elem));
+}
+
+/**
+ * \brief Get Layout strides.
+ *
+ * \param layout Layout to get strides.
+ * \return Requsted strides.
+ */
+template <typename Shape, typename Strides>
+__host__ __device__ constexpr auto stride(const Layout<Shape, Strides>& layout)
+{
+    return layout.GetStrides();
+}
+
+/**
+ * \brief Get Layout shape.
+ *
+ * \param layout Layout to get shape.
+ * \return Requsted shape.
+ */
+template <typename Shape, typename Strides>
+__host__ __device__ constexpr auto shape(const Layout<Shape, Strides>& layout)
+{
+    return layout.GetShape();
+}
+
+} // namespace wrapper
+} // namespace ck

test/CMakeLists.txt

@@ -149,6 +149,7 @@ add_subdirectory(batched_gemm_multi_d)
 add_subdirectory(grouped_convnd_bwd_data)
 add_subdirectory(conv_tensor_rearrange)
 add_subdirectory(transpose)
+add_subdirectory(wrapper)
 if(GPU_TARGETS MATCHES "gfx11")
     add_subdirectory(wmma_op)
 endif()

test/wrapper/CMakeLists.txt

+add_gtest_executable(test_layout test_layout.cpp)
+target_link_libraries(test_layout PRIVATE utility)