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+/*
+ * Copyright (c) 2022 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef SRC_DYNAMIC_FUSION_SKETCH_GPU_GPUWORKLOADSOURCECODE
+#define SRC_DYNAMIC_FUSION_SKETCH_GPU_GPUWORKLOADSOURCECODE
+
+#include "arm_compute/core/experimental/Types.h"
+#include "arm_compute/dynamic_fusion/sketch/MemoryDescriptor.h"
+#include "src/dynamic_fusion/sketch/gpu/GpuKernelSourceCode.h"
+
+namespace arm_compute
+{
+namespace experimental
+{
+namespace dynamic_fusion
+{
+/** Uniquely identifies a @ref GpuUnitWorkload within a @ref GpuWorkloadSourceCode */
+using UnitWorkloadId = int32_t;
+
+/** Describes all the info related to a kernel in order to:
+ * - be used by runtime to configure gpu kernel argument
+ * - be used by memory managers to allocate required memory
+ */
+class GpuWorkloadArgument
+{
+public:
+ /** Default constructor */
+ GpuWorkloadArgument() = default;
+ /** Constructor
+ *
+ * @param[in] tensor_info @ref ITensorInfo of the workload argument
+ * @param[in] mem_desc @ref MemoryDescriptor of the workload argument
+ * @param[in] kernel_arg_info @ref GpuKernelArgumentInfo of the workload argument
+ */
+ GpuWorkloadArgument(const ITensorInfo &tensor_info,
+ const MemoryDescriptor &mem_desc,
+ const GpuKernelArgumentInfo &kernel_arg_info)
+ : _tensor_info{ tensor_info },
+ _mem_desc{ mem_desc },
+ _kernel_arg_info{ kernel_arg_info }
+ {
+ }
+ /** Get tensor id within workload */
+ ITensorInfo::Id id() const
+ {
+ return _tensor_info.id();
+ }
+ /** Get @ref ITensorInfo of the argument */
+ ITensorInfo *tensor_info()
+ {
+ return &_tensor_info;
+ }
+ /** Get @ref ITensorInfo of the argument */
+ const ITensorInfo *tensor_info() const
+ {
+ return &_tensor_info;
+ }
+ /** Get @ref MemoryDescriptor of the argument */
+ MemoryDescriptor *memory_descriptor()
+ {
+ return &_mem_desc;
+ }
+ /** Get @ref MemoryDescriptor of the argument */
+ const MemoryDescriptor *memory_descriptor() const
+ {
+ return &_mem_desc;
+ }
+ /** Get @ref GpuKernelArgumentInfo of the argument */
+ GpuKernelArgumentInfo *kernel_argument_info()
+ {
+ return &_kernel_arg_info;
+ }
+ /** Get @ref GpuKernelArgumentInfo of the argument */
+ const GpuKernelArgumentInfo *kernel_argument_info() const
+ {
+ return &_kernel_arg_info;
+ }
+ /** Check if the workload argument has valid id
+ *
+ * @return true If has valid id
+ * @return false Otherwise
+ */
+ bool has_valid_id() const
+ {
+ return _tensor_info.has_valid_id();
+ }
+
+private:
+ TensorInfo _tensor_info{};
+ MemoryDescriptor _mem_desc{};
+ GpuKernelArgumentInfo _kernel_arg_info{};
+};
+
+/** Describes when a unit workload is run.
+ */
+struct UnitWorkloadStage
+{
+ enum class Stage
+ {
+ Prepare, /**< Only run once at the beginning. */
+ Run, /**< Run every time after the first time. */
+ };
+ Stage stage{ Stage::Run };
+};
+
+inline bool operator==(const UnitWorkloadStage &stage0, const UnitWorkloadStage &stage1)
+{
+ return stage0.stage == stage1.stage;
+}
+
+/** The atomic unit in a Gpu workload. It contains exactly one kernel to run.
+ */
+class GpuUnitWorkload
+{
+public:
+ /** Default constructor */
+ GpuUnitWorkload() = default;
+ /** Constructor
+ *
+ * @param[in] id Id that uniquely identifies this unit workload in a workload
+ * @param[in] kernel_code @ref GpuKernelSourceCode contained within
+ * @param[in] stage Stage of the unit workload
+ */
+ GpuUnitWorkload(UnitWorkloadId id, const GpuKernelSourceCode &kernel_code, const UnitWorkloadStage &stage)
+ : _id{ id }, _kernel_code{ kernel_code }, _stage{ stage }
+ {
+ }
+ /** Get the id of the unit workload */
+ UnitWorkloadId id() const
+ {
+ return _id;
+ }
+ /** Get reference to the underlying @ref GpuKernelSourceCode */
+ const GpuKernelSourceCode &code() const
+ {
+ return _kernel_code;
+ }
+ /** Get the stage of the unit workload */
+ UnitWorkloadStage stage() const
+ {
+ return _stage;
+ }
+
+private:
+ UnitWorkloadId _id{};
+ GpuKernelSourceCode _kernel_code{};
+ UnitWorkloadStage _stage{};
+};
+
+/** Hold the generated kernel source code and other information required to compile and run the workload.
+ */
+class GpuWorkloadSourceCode
+{
+public:
+ /** Default constructor */
+ GpuWorkloadSourceCode() = default;
+ /** Add a unit workload to the workload code
+ *
+ * @param[in] kernel_code @ref GpuKernelSourceCode to be contained within the unit workload
+ * @param[in] stage Stage of the unit workload
+ * @param[in] mem_map @ref MemoryDescriptor map for all tensors within the unit workload
+ *
+ * @return UnitWorkloadId Allocated unit workload id
+ */
+ UnitWorkloadId add_unit_workload(const GpuKernelSourceCode &kernel_code, const UnitWorkloadStage &stage, const MemoryDescriptorMap &mem_map)
+ {
+ // Use the size of the kernel codes as Id
+ const auto uwk_id = static_cast<UnitWorkloadId>(_unit_workloads.size());
+ const auto unit_work = GpuUnitWorkload(uwk_id, kernel_code, stage);
+ _unit_workloads.push_back(unit_work);
+ // Assemble kernel argument with memory descriptor to form workload argument
+ for(const auto &id_arg : kernel_code.arguments())
+ {
+ const auto arg_id = id_arg.first;
+ const auto arg = id_arg.second;
+ _workload_arguments[arg_id] = GpuWorkloadArgument{ *arg.tensor_info(), mem_map.at(arg_id), *arg.kernel_argument_info() };
+ if(_tensor_uwork_map.find(arg_id) == _tensor_uwork_map.end())
+ {
+ _tensor_uwork_map[arg_id] = std::set<UnitWorkloadId>();
+ }
+ _tensor_uwork_map[arg_id].insert(uwk_id);
+ }
+ return uwk_id;
+ }
+ /** Get a unit workload from its id */
+ const GpuUnitWorkload &query_unit_workload(UnitWorkloadId id) const
+ {
+ ARM_COMPUTE_ERROR_ON(id < 0);
+ return _unit_workloads.at(id);
+ }
+ /** Get all unit workloads sorted in topological order */
+ std::vector<UnitWorkloadId> unit_workloads() const
+ {
+ std::vector<UnitWorkloadId> ids{};
+
+ for(const auto &uwk : _unit_workloads)
+ {
+ ids.push_back(uwk.id());
+ }
+ return ids;
+ }
+ /** Get a @ref GpuWorkloadArgument from its associated tensor id */
+ const GpuWorkloadArgument *query_tensor(ITensorInfo::Id t_id) const
+ {
+ return &_workload_arguments.at(t_id);
+ }
+ /** Get all tensors in the entire workload */
+ std::vector<ITensorInfo::Id> tensors() const
+ {
+ std::vector<ITensorInfo::Id> ids{};
+ for(const auto &id_tensor : _workload_arguments)
+ {
+ ids.push_back(id_tensor.first);
+ }
+ return ids;
+ }
+ /** Get all unit workloads connected to the tensor with @p t_id */
+ std::vector<UnitWorkloadId> get_unit_workloads_from_tensor(ITensorInfo::Id t_id) const
+ {
+ const auto unit_work_set = _tensor_uwork_map.at(t_id);
+ return std::vector<UnitWorkloadId>(unit_work_set.begin(), unit_work_set.end());
+ }
+
+private:
+ std::vector<GpuUnitWorkload> _unit_workloads{};
+ std::map<ITensorInfo::Id, GpuWorkloadArgument> _workload_arguments{};
+ std::map<ITensorInfo::Id, std::set<UnitWorkloadId>> _tensor_uwork_map{};
+};
+} // namespace dynamic_fusion
+} // namespace experimental
+} // namespace arm_compute
+#endif /* SRC_DYNAMIC_FUSION_SKETCH_GPU_GPUWORKLOADSOURCECODE */