mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-03 13:11:25 +00:00
4234b3a691
* Add tensor partition and generic copy for ck wrapper * Update changelog * Stylistic fixes * Change shape/strides logic to descriptor transforms * Fixes * Fix client example * Fix comments
397 lines
11 KiB
C++
397 lines
11 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
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#pragma once
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#include "ck/ck.hpp"
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#include "ck/utility/number.hpp"
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#include "ck/utility/tuple.hpp"
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#include "ck/utility/tuple_helper.hpp"
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#include "ck/utility/sequence.hpp"
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#include "ck/utility/sequence_helper.hpp"
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#include "ck/utility/is_detected.hpp"
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#include "ck/tensor_description/tensor_descriptor.hpp"
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#include "ck/tensor_description/tensor_descriptor_helper.hpp"
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#include "ck/tensor_description/multi_index_transform_helper.hpp"
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namespace ck {
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namespace wrapper {
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// Disable from doxygen docs generation
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/// @cond
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// forward declaration
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template <typename Shape, typename UnnestedDescriptorType>
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struct Layout;
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template <typename T>
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using is_tuple = decltype(std::declval<T&>().IsTuple());
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namespace {
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// Generate packed (column-major) strides if not passed
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template <typename... Ts>
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__host__ __device__ constexpr static auto
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GenerateColumnMajorPackedStrides(const Tuple<Ts...>& shape)
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{
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const auto unrolled_shape = UnrollNestedTuple(shape);
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return generate_tuple(
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[&](auto i) {
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if constexpr(i.value == 0)
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{
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return Number<1>{};
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}
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else
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{
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return TupleReduce<Number<0>{}.value, i.value>([](auto x, auto y) { return x * y; },
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unrolled_shape);
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}
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},
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Number<decltype(unrolled_shape)::Size()>{});
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}
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template <typename LayoutShape, typename LayoutStrides>
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__host__ __device__ constexpr auto MakeFlattenDescriptor(const LayoutShape& shape,
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const LayoutStrides& strides)
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{
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const auto unrolled_shape = UnrollNestedTuple(shape);
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if constexpr(is_same_v<LayoutStrides, Tuple<>>)
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{
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// if not passed, then generate
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const auto unrolled_strides = GenerateColumnMajorPackedStrides(unrolled_shape);
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static_assert(unrolled_shape.Size() == unrolled_strides.Size(),
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"Size of strides and shape are not consistent.");
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return make_naive_tensor_descriptor(unrolled_shape, unrolled_strides);
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}
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else
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{
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const auto unrolled_strides = UnrollNestedTuple(strides);
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static_assert(unrolled_shape.Size() == unrolled_strides.Size(),
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"Size of strides and shape are not consistent.");
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return make_naive_tensor_descriptor(unrolled_shape, unrolled_strides);
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}
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}
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} // namespace
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/// @endcond
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// make_*
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/**
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* \brief Make layout function.
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*
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* \tparam Shape Shape for layout.
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* \tparam Strides Strides for layout.
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* \return Constructed layout.
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*/
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template <typename Shape, typename Strides>
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__host__ __device__ constexpr auto make_layout(const Shape& shape, const Strides& strides)
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{
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using UnnestedDescriptorType = decltype(MakeFlattenDescriptor(Shape{}, Strides{}));
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return Layout<Shape, UnnestedDescriptorType>(shape, MakeFlattenDescriptor(shape, strides));
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}
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/**
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* \brief Make layout function with packed strides
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* (column-major).
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*
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* \tparam Shape Shape for layout.
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* \return Constructed layout.
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*/
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template <typename Shape>
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__host__ __device__ constexpr auto make_layout(const Shape& shape)
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{
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using UnnestedDescriptorType = decltype(MakeFlattenDescriptor(Shape{}, Tuple<>{}));
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return Layout<Shape, UnnestedDescriptorType>(shape, MakeFlattenDescriptor(shape, Tuple<>{}));
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}
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// Layout helpers
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// get
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// Get dim (could be returned from get with empty Idxs)
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/**
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* \private
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*/
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template <typename T>
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__host__ __device__ T constexpr get(const T& dim)
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{
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return dim;
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}
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/**
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* \brief Get element from tuple (Shape/Strides/Idxs).
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*
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* \tparam idx Index to lookup.
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* \param tuple Tuple to lookup.
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* \return Requsted element.
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*/
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template <index_t idx, typename... Dims>
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__host__ __device__ constexpr auto get(const Tuple<Dims...>& tuple)
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{
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return tuple.At(Number<idx>{});
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}
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/**
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* \brief Get sub layout.
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*
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* \tparam idx Index to lookup.
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* \param layout Layout to create sub layout.
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* \return Requsted sub layout.
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*/
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template <index_t idx, typename Shape, typename FlattenDesc>
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__host__ __device__ constexpr auto get(const Layout<Shape, FlattenDesc>& layout)
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{
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const auto& shape = layout.GetShape();
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const auto new_shape = get<idx>(shape);
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static_assert(is_detected<is_tuple, decltype(new_shape)>::value,
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"Shape of sub layout must be tuple");
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constexpr auto old_shape_dims = decltype(UnrollNestedTuple(shape))::Size();
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constexpr auto new_shape_dims = decltype(UnrollNestedTuple(new_shape))::Size();
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constexpr auto shape_offset = decltype(UnrollNestedTuple(TupleSlice<0, idx>(shape)))::Size();
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const auto unrolled_shape = UnrollNestedTuple(shape);
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const auto transforms = generate_tuple(
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[&](auto i) {
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// Compare Idx with shape
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if constexpr(i < shape_offset || i >= shape_offset + new_shape_dims)
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{
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// Remove dimension
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return make_freeze_transform(Number<0>{});
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}
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else
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{
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return make_pass_through_transform(unrolled_shape.At(i));
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}
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},
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Number<old_shape_dims>{});
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const auto lower_dims =
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generate_tuple([&](auto i) { return Sequence<i.value>{}; }, Number<old_shape_dims>{});
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const auto upper_dims = generate_tuple(
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[&](auto i) {
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if constexpr(i < shape_offset || i >= shape_offset + new_shape_dims)
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return Sequence<>{};
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else
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{
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return Sequence<i.value - shape_offset>{};
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}
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},
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Number<old_shape_dims>{});
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const auto& flatten_desc = layout.GetUnnestedDescriptor();
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auto new_desc = transform_tensor_descriptor(flatten_desc, transforms, lower_dims, upper_dims);
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return Layout<decltype(new_shape), decltype(new_desc)>(new_shape, new_desc);
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}
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/**
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* \brief Hierarchical get.
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*
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* \tparam Idxs Indexes to lookup.
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* \param elem Element to lookup.
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* \return Requsted element.
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*/
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template <index_t Idx, index_t... Idxs, typename T>
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__host__ __device__ constexpr auto get(const T& elem)
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{
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return get<Idxs...>(get<Idx>(elem));
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}
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// size
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// Get dim size (could be returned from get function)
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/**
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* \private
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*/
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template <typename T>
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__host__ __device__ T constexpr size(const T& dim)
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{
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return dim;
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}
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/**
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* \brief Length get (product if tuple).
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*
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* \tparam idx Index to lookup.
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* \param layout Layout to get Shape of.
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* \return Requsted length.
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*/
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template <index_t idx, typename Shape, typename UnnestedDescriptorType>
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__host__ __device__ constexpr auto size(const Layout<Shape, UnnestedDescriptorType>& layout)
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{
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return layout.template GetLength<idx>();
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}
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/**
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* \brief Shape size (product of dims).
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*
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* \param shape Shape to lookup.
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* \return Requsted size.
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*/
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template <typename... ShapeDims>
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__host__ __device__ constexpr auto size(const Tuple<ShapeDims...>& shape)
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{
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const auto unrolled_shape = UnrollNestedTuple(shape);
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return TupleReduce<0, unrolled_shape.Size()>([](auto x, auto y) { return x * y; },
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unrolled_shape);
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}
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/**
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* \brief Layout size (product of dims).
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*
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* \param layout Layout to calculate shape size.
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* \return Requsted size.
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*/
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template <typename Shape, typename UnnestedDescriptorType>
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__host__ __device__ constexpr auto size(const Layout<Shape, UnnestedDescriptorType>& layout)
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{
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return layout.GetLengths();
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}
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/**
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* \brief Length get from tuple (product if tuple).
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*
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* \tparam idx Index to lookup.
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* \param tuple Tuple to lookup.
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* \return Requsted length.
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*/
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template <index_t idx, typename... Ts>
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__host__ __device__ constexpr auto size(const Tuple<Ts...>& tuple)
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{
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return size(tuple.At(Number<idx>{}));
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}
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/**
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* \brief Hierarchical size.
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*
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* \tparam Idx First index to lookup (to avoid empty Idxs).
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* \tparam Idxs Next indexes to lookup.
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* \param elem Element to lookup.
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* \return Requsted element.
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*/
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template <index_t Idx, index_t... Idxs, typename T>
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__host__ __device__ constexpr auto size(const T& elem)
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{
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return size(get<Idx, Idxs...>(elem));
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}
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// rank
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/**
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* \brief Get layout rank (num elements in shape).
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*
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* \param layout Layout to calculate rank.
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* \return Requsted rank.
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*/
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template <typename Shape, typename UnnestedDescriptorType>
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__host__ __device__ constexpr auto
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rank([[maybe_unused]] const Layout<Shape, UnnestedDescriptorType>& layout)
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{
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return Shape::Size();
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}
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/**
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* \brief Get tuple rank (num elements in tuple).
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* Return 1 if scalar passed.
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*
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* \param tuple Tuple to calculate rank.
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* \return Requsted rank.
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*/
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template <typename... Dims>
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__host__ __device__ constexpr auto rank([[maybe_unused]] const Tuple<Dims...>& tuple)
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{
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return Tuple<Dims...>::Size();
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}
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/**
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* \private
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*/
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template <index_t IDim>
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__host__ __device__ constexpr index_t rank(const Number<IDim>&)
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{
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return 1;
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}
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/**
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* \private
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*/
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__host__ __device__ constexpr index_t rank(const index_t&) { return 1; }
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/**
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* \brief Hierarchical rank.
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*
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* \tparam Idxs Indexes to lookup.
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* \param elem Element to lookup.
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* \return Requsted rank.
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*/
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template <index_t... Idxs, typename T>
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__host__ __device__ constexpr auto rank(const T& elem)
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{
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return rank(get<Idxs...>(elem));
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}
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// depth
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/**
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* \brief Get depth of the layout shape (return 0 if scalar).
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*
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* \param layout Layout to calculate depth.
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* \return Requsted depth.
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*/
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template <typename Shape, typename UnnestedDescriptorType>
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__host__ __device__ constexpr auto depth(const Layout<Shape, UnnestedDescriptorType>& layout)
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{
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const auto& shape = layout.GetShape();
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return TupleDepth(shape);
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}
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/**
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* \brief Get depth of the tuple. (return 0 if scalar)
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*
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* \param tuple Tuple to calculate depth.
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* \return Requsted depth.
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*/
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template <typename... Dims>
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__host__ __device__ constexpr auto depth(const Tuple<Dims...>& tuple)
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{
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return TupleDepth(tuple);
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}
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/**
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* \private
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*/
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template <index_t IDim>
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__host__ __device__ constexpr index_t depth(const Number<IDim>&)
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{
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return 0;
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}
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/**
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* \private
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*/
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__host__ __device__ constexpr index_t depth(const index_t&) { return 0; }
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/**
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* \brief Hierarchical depth.
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*
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* \tparam Idxs Indexes to lookup.
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* \param elem Element to lookup.
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* \return Requsted depth.
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*/
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template <index_t... Idxs, typename T>
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__host__ __device__ constexpr auto depth(const T& elem)
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{
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return depth(get<Idxs...>(elem));
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}
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/**
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* \brief Get Layout shape.
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*
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* \param layout Layout to get shape from.
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* \return Requsted shape.
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*/
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template <typename LayoutType>
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__host__ __device__ constexpr const auto& shape(const LayoutType& layout)
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{
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return layout.GetShape();
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}
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} // namespace wrapper
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} // namespace ck
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