Add device op 'DevicePermute'

This device op is clone of 'DeviceElementwise'

include/ck/tensor_operation/gpu/device/device_permute.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <iostream>
+#include <sstream>
+
+#include "ck/utility/math.hpp"
+#include "ck/utility/sequence.hpp"
+#include "ck/tensor_operation/gpu/device/device_elementwise_base.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_elementwise_1d.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+
+#include "ck/host_utility/kernel_launch.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+template <typename InDataTypeTuple,
+          typename OutDataTypeTuple,
+          typename ElementwiseOperation,
+          index_t NumDim,
+          index_t MPerThread,
+          typename InScalarPerVectorSeq,
+          typename OutScalarPerVectorSeq>
+struct DevicePermute
+    : public DeviceElementwiseBase<InDataTypeTuple, OutDataTypeTuple, ElementwiseOperation, NumDim>
+{
+    static constexpr int NumInput  = InDataTypeTuple::Size();
+    static constexpr int NumOutput = OutDataTypeTuple::Size();
+
+    static_assert(NumInput == InScalarPerVectorSeq::Size() &&
+                      NumOutput == OutScalarPerVectorSeq::Size(),
+                  "Tuple size is inconsistent with the number of in/out!");
+
+    static auto GenerateInDataTypePointerTuple()
+    {
+        return generate_tuple(
+            [&](auto I) {
+                using DataType = remove_cvref_t<decltype(InDataTypeTuple{}[I])>;
+
+                return static_cast<const DataType*>(nullptr);
+            },
+            Number<NumInput>{});
+    };
+
+    static auto GenerateOutDataTypePointerTuple()
+    {
+        return generate_tuple(
+            [&](auto I) {
+                using DataType = remove_cvref_t<decltype(OutDataTypeTuple{}[I])>;
+
+                return static_cast<DataType*>(nullptr);
+            },
+            Number<NumOutput>{});
+    };
+
+    using InDataTypePointerTuple  = decltype(GenerateInDataTypePointerTuple());
+    using OutDataTypePointerTuple = decltype(GenerateOutDataTypePointerTuple());
+
+    template <typename Desc_M>
+    static auto PadDescriptor_M_1d(Desc_M desc_m, index_t gridSize, index_t blockSize)
+    {
+        constexpr auto I0 = Number<0>{};
+
+        const auto m            = desc_m.GetLength(I0);
+        const index_t loop_step = gridSize * blockSize * MPerThread;
+        const auto pad          = math::integer_least_multiple(m, loop_step) - m;
+        const auto desc_m_pad =
+            transform_tensor_descriptor(desc_m,
+                                        make_tuple(make_right_pad_transform(m, pad)),
+                                        make_tuple(Sequence<0>{}),
+                                        make_tuple(Sequence<0>{}));
+        return desc_m_pad;
+    }
+
+    static auto MakeDescriptor_M(const std::array<index_t, NumDim>& lengths,
+                                 const std::array<index_t, NumDim>& stride,
+                                 index_t gridSize,
+                                 index_t blockSize)
+    {
+        auto tupleOfShape  = generate_tuple([&](auto I) { return lengths[I]; }, Number<NumDim>{});
+        auto tupleOfStride = generate_tuple([&](auto I) { return stride[I]; }, Number<NumDim>{});
+
+        // nd desc - [s0, s1, s2, ...]
+        const auto desc = make_naive_tensor_descriptor(tupleOfShape, tupleOfStride);
+
+        // merge nd to 1d desc - [s0 * s1 * ...]
+        if constexpr(NumDim > 1)
+        {
+            const auto desc_m = transform_tensor_descriptor(
+                desc,
+                make_tuple(make_merge_transform(tupleOfShape)),
+                make_tuple(generate_sequence_v2([&](auto I) { return I; }, Number<NumDim>{})),
+                make_tuple(Sequence<0>{}));
+
+            return PadDescriptor_M_1d(desc_m, gridSize, blockSize);
+        }
+        else
+            return PadDescriptor_M_1d(desc, gridSize, blockSize);
+    }
+
+    template <index_t TupleSize>
+    static auto GenerateInOutGrid1dDescTuple(Number<TupleSize>)
+    {
+        return generate_tuple(
+            [&](auto) {
+                if constexpr(NumDim > 1)
+                {
+                    return MakeDescriptor_M({1, 1}, {1, 1}, 1, 1);
+                }
+                else
+                {
+                    return MakeDescriptor_M({1}, {1}, 1, 1);
+                };
+            },
+            Number<TupleSize>{});
+    };
+
+    using InGrid1dDescTuple  = decltype(GenerateInOutGrid1dDescTuple(Number<NumInput>{}));
+    using OutGrid1dDescTuple = decltype(GenerateInOutGrid1dDescTuple(Number<NumOutput>{}));
+
+    using GridwiseElementwise = GridwiseElementwise_1D<InGrid1dDescTuple,
+                                                       OutGrid1dDescTuple,
+                                                       InDataTypePointerTuple,
+                                                       OutDataTypePointerTuple,
+                                                       ElementwiseOperation,
+                                                       MPerThread,
+                                                       InScalarPerVectorSeq,
+                                                       OutScalarPerVectorSeq>;
+
+    struct Argument : public BaseArgument
+    {
+        Argument(const std::array<index_t, NumDim> lengths,
+                 const std::array<std::array<index_t, NumDim>, NumInput> inStridesArray,
+                 const std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray,
+                 const std::array<const void*, NumInput> in_dev_buffers,
+                 const std::array<void*, NumOutput> out_dev_buffers,
+                 ElementwiseOperation elementwise_op)
+
+            : lengths_(lengths),
+              inStridesArray_(inStridesArray),
+              outStridesArray_(outStridesArray),
+              elementwise_op_(elementwise_op),
+              blockSize_(256),
+              gridSize_(120) // FIXME - Calculate the grid size by number of CU in the future
+        {
+            in_dev_buffers_ = generate_tuple(
+                [&](auto I) {
+                    using DataType = remove_cvref_t<decltype(InDataTypeTuple{}[I])>;
+                    return static_cast<const DataType*>(in_dev_buffers[I.value]);
+                },
+                Number<NumInput>{});
+
+            out_dev_buffers_ = generate_tuple(
+                [&](auto I) {
+                    using DataType = remove_cvref_t<decltype(OutDataTypeTuple{}[I])>;
+                    return static_cast<DataType*>(out_dev_buffers[I.value]);
+                },
+                Number<NumOutput>{});
+
+            in_grid_1d_desc_tuple_ = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_M(
+                        lengths, inStridesArray[I.value], gridSize_, blockSize_);
+                },
+                Number<NumInput>{});
+
+            out_grid_1d_desc_tuple_ = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_M(
+                        lengths, outStridesArray[I.value], gridSize_, blockSize_);
+                },
+                Number<NumOutput>{});
+        }
+
+        InDataTypePointerTuple in_dev_buffers_;
+        OutDataTypePointerTuple out_dev_buffers_;
+        InGrid1dDescTuple in_grid_1d_desc_tuple_;
+        OutGrid1dDescTuple out_grid_1d_desc_tuple_;
+
+        std::array<index_t, NumDim> lengths_;
+        std::array<std::array<index_t, NumDim>, NumInput> inStridesArray_;
+        std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray_;
+
+        ElementwiseOperation elementwise_op_;
+        index_t blockSize_;
+        index_t gridSize_;
+    };
+
+    struct Invoker : public BaseInvoker
+    {
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
+        {
+            const auto kernel = kernel_elementwise_1d<GridwiseElementwise,
+                                                      InGrid1dDescTuple,
+                                                      OutGrid1dDescTuple,
+                                                      InDataTypePointerTuple,
+                                                      OutDataTypePointerTuple,
+                                                      ElementwiseOperation>;
+
+            float elapsed_time = launch_and_time_kernel(stream_config,
+                                                        kernel,
+                                                        dim3(arg.gridSize_),
+                                                        dim3(arg.blockSize_),
+                                                        0,
+                                                        arg.in_grid_1d_desc_tuple_,
+                                                        arg.out_grid_1d_desc_tuple_,
+                                                        arg.in_dev_buffers_,
+                                                        arg.out_dev_buffers_,
+                                                        arg.elementwise_op_);
+            return elapsed_time;
+        }
+
+        // polymorphic
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    static bool IsSupportedArgument(const Argument& arg)
+    {
+        if(arg.lengths_.back() % MPerThread != 0)
+            return false;
+
+        auto IsScalarPerVectorValid = [&](const std::array<index_t, NumDim>& lengths,
+                                          const std::array<index_t, NumDim>& strides,
+                                          index_t scalarPerVector) {
+            if(strides.back() == 1 && lengths.back() % scalarPerVector == 0)
+                return true;
+
+            if(strides.back() != 1 && scalarPerVector == 1)
+                return true;
+
+            return false;
+        };
+
+        bool valid = true;
+        static_for<0, NumInput, 1>{}([&](auto I) {
+            if(!IsScalarPerVectorValid(
+                   arg.lengths_, arg.inStridesArray_[I.value], InScalarPerVectorSeq::At(I)))
+                valid = false;
+        });
+
+        static_for<0, NumOutput, 1>{}([&](auto I) {
+            if(!IsScalarPerVectorValid(
+                   arg.lengths_, arg.outStridesArray_[I.value], OutScalarPerVectorSeq::At(I)))
+                valid = false;
+        });
+
+        return valid;
+    };
+
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
+    }
+
+    static auto
+    MakeArgument(const std::array<index_t, NumDim> lengths,
+                 const std::array<std::array<index_t, NumDim>, NumInput> inStridesArray,
+                 const std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray,
+                 const std::array<const void*, NumInput> in_dev_buffers,
+                 const std::array<void*, NumOutput> out_dev_buffers,
+                 ElementwiseOperation elementwise_op)
+    {
+        return Argument{lengths,
+                        inStridesArray,
+                        outStridesArray,
+                        in_dev_buffers,
+                        out_dev_buffers,
+                        elementwise_op};
+    }
+
+    std::unique_ptr<BaseArgument>
+    MakeArgumentPointer(const std::array<index_t, NumDim> lengths,
+                        const std::array<std::array<index_t, NumDim>, NumInput> inStridesArray,
+                        const std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray,
+                        const std::array<const void*, NumInput> in_dev_buffers,
+                        const std::array<void*, NumOutput> out_dev_buffers,
+                        ElementwiseOperation elementwise_op) override
+    {
+        return std::make_unique<Argument>(lengths,
+                                          inStridesArray,
+                                          outStridesArray,
+                                          in_dev_buffers,
+                                          out_dev_buffers,
+                                          elementwise_op);
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>();
+    };
+}; // namespace device
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck