| /* |
| * Copyright (c) 2021 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 ARM_COMPUTE_ACL_HPP_ |
| #define ARM_COMPUTE_ACL_HPP_ |
| |
| #include "arm_compute/Acl.h" |
| |
| #include <cstdlib> |
| #include <memory> |
| #include <string> |
| #include <vector> |
| |
| #if defined(ARM_COMPUTE_EXCEPTIONS_ENABLED) |
| #include <exception> |
| #endif /* defined(ARM_COMPUTE_EXCEPTIONS_ENABLED) */ |
| |
| // Helper Macros |
| #define ARM_COMPUTE_IGNORE_UNUSED(x) (void)(x) |
| |
| namespace acl |
| { |
| // Forward declarations |
| class Context; |
| class Queue; |
| class Tensor; |
| class TensorPack; |
| |
| /**< Status code enum */ |
| enum class StatusCode |
| { |
| Success = AclSuccess, |
| RuntimeError = AclRuntimeError, |
| OutOfMemory = AclOutOfMemory, |
| Unimplemented = AclUnimplemented, |
| UnsupportedTarget = AclUnsupportedTarget, |
| InvalidArgument = AclInvalidArgument, |
| InvalidTarget = AclInvalidTarget, |
| UnsupportedConfig = AclUnsupportedConfig, |
| InvalidObjectState = AclInvalidObjectState, |
| }; |
| |
| /**< Utility namespace containing helpers functions */ |
| namespace detail |
| { |
| /** Construct to handle destruction of objects |
| * |
| * @tparam T Object base type |
| */ |
| template <typename T> |
| struct ObjectDeleter |
| { |
| }; |
| |
| #define OBJECT_DELETER(obj, func) \ |
| template <> \ |
| struct ObjectDeleter<obj> \ |
| \ |
| { \ |
| static inline AclStatus Destroy(obj v) \ |
| { \ |
| return func(v); \ |
| } \ |
| }; |
| |
| OBJECT_DELETER(AclContext, AclDestroyContext) |
| OBJECT_DELETER(AclQueue, AclDestroyQueue) |
| OBJECT_DELETER(AclTensor, AclDestroyTensor) |
| OBJECT_DELETER(AclTensorPack, AclDestroyTensorPack) |
| OBJECT_DELETER(AclOperator, AclDestroyOperator) |
| |
| #undef OBJECT_DELETER |
| |
| /** Convert a strongly typed enum to an old plain c enum |
| * |
| * @tparam E Plain old C enum |
| * @tparam SE Strongly typed resulting enum |
| * |
| * @param[in] v Value to convert |
| * |
| * @return A corresponding plain old C enumeration |
| */ |
| template <typename E, typename SE> |
| constexpr E as_cenum(SE v) noexcept |
| { |
| return static_cast<E>(static_cast<typename std::underlying_type<SE>::type>(v)); |
| } |
| |
| /** Convert plain old enumeration to a strongly typed enum |
| * |
| * @tparam SE Strongly typed resulting enum |
| * @tparam E Plain old C enum |
| * |
| * @param[in] val Value to convert |
| * |
| * @return A corresponding strongly typed enumeration |
| */ |
| template <typename SE, typename E> |
| constexpr SE as_enum(E val) noexcept |
| { |
| return static_cast<SE>(val); |
| } |
| |
| /** Object base class for library objects |
| * |
| * Class is defining basic common interface for all the library objects |
| * |
| * @tparam T Object type to be templated on |
| */ |
| template <typename T> |
| class ObjectBase |
| { |
| public: |
| /** Destructor */ |
| ~ObjectBase() = default; |
| /** Copy constructor */ |
| ObjectBase(const ObjectBase<T> &) = default; |
| /** Move Constructor */ |
| ObjectBase(ObjectBase<T> &&) = default; |
| /** Copy assignment operator */ |
| ObjectBase<T> &operator=(const ObjectBase<T> &) = default; |
| /** Move assignment operator */ |
| ObjectBase<T> &operator=(ObjectBase<T> &&) = default; |
| /** Reset object value |
| * |
| * @param [in] val Value to set |
| */ |
| void reset(T *val) |
| { |
| _object.reset(val, detail::ObjectDeleter<T *>::Destroy); |
| } |
| /** Access uderlying object |
| * |
| * @return Underlying object |
| */ |
| const T *get() const |
| { |
| return _object.get(); |
| } |
| /** Access uderlying object |
| * |
| * @return Underlying object |
| */ |
| T *get() |
| { |
| return _object.get(); |
| } |
| |
| protected: |
| /** Constructor */ |
| ObjectBase() = default; |
| |
| protected: |
| std::shared_ptr<T> _object{nullptr}; /**< Library object */ |
| }; |
| |
| /** Equality operator for library object |
| * |
| * @tparam T Parameter to template on |
| * |
| * @param[in] lhs Left hand-side argument |
| * @param[in] rhs Right hand-side argument |
| * |
| * @return True if objects are equal, else false |
| */ |
| template <typename T> |
| bool operator==(const ObjectBase<T> &lhs, const ObjectBase<T> &rhs) |
| { |
| return lhs.get() == rhs.get(); |
| } |
| |
| /** Inequality operator for library object |
| * |
| * @tparam T Parameter to template on |
| * |
| * @param[in] lhs Left hand-side argument |
| * @param[in] rhs Right hand-side argument |
| * |
| * @return True if objects are equal, else false |
| */ |
| template <typename T> |
| bool operator!=(const ObjectBase<T> &lhs, const ObjectBase<T> &rhs) |
| { |
| return !(lhs == rhs); |
| } |
| } // namespace detail |
| |
| #if defined(ARM_COMPUTE_EXCEPTIONS_ENABLED) |
| /** Status class |
| * |
| * Class is an extension of std::exception and contains the underlying |
| * status construct and an error explanatory message to be reported. |
| * |
| * @note Class is visible only when exceptions are enabled during compilation |
| */ |
| class Status : public std::exception |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] status Status returned |
| * @param[in] msg Error message to be bound with the exception |
| */ |
| Status(StatusCode status, const std::string &msg) : _status(status), _msg(msg) |
| { |
| } |
| /** Returns an explanatory exception message |
| * |
| * @return Status message |
| */ |
| const char *what() const noexcept override |
| { |
| return _msg.c_str(); |
| } |
| /** Underlying status accessor |
| * |
| * @return Status code |
| */ |
| StatusCode status() const |
| { |
| return _status; |
| } |
| /** Explicit status converter |
| * |
| * @return Status code |
| */ |
| explicit operator StatusCode() const |
| { |
| return _status; |
| } |
| |
| private: |
| StatusCode _status; /**< Status code */ |
| std::string _msg; /**< Status message */ |
| }; |
| |
| /** Reports an error status and throws an exception object in case of failure |
| * |
| * @note This implementation is used when exceptions are enabled during compilation |
| * |
| * @param[in] status Status to report |
| * @param[in] msg Explanatory error messaged |
| * |
| * @return Status code |
| */ |
| static inline void report_status(StatusCode status, const std::string &msg) |
| { |
| if (status != StatusCode::Success) |
| { |
| throw Status(status, msg); |
| } |
| } |
| #else /* defined(ARM_COMPUTE_EXCEPTIONS_ENABLED) */ |
| /** Reports a status code |
| * |
| * @note This implementation is used when exceptions are disabled during compilation |
| * @note Message is surpressed and not reported in this case |
| * |
| * @param[in] status Status to report |
| * @param[in] msg Explanatory error messaged |
| * |
| * @return Status code |
| */ |
| static inline void report_status(StatusCode status, const std::string &msg) |
| { |
| ARM_COMPUTE_IGNORE_UNUSED(status); |
| ARM_COMPUTE_IGNORE_UNUSED(msg); |
| } |
| #endif /* defined(ARM_COMPUTE_EXCEPTIONS_ENABLED) */ |
| |
| /**< Target enum */ |
| enum class Target |
| { |
| Cpu = AclCpu, /**< Cpu target that leverages SIMD */ |
| GpuOcl = AclGpuOcl /**< Gpu target that leverages OpenCL */ |
| }; |
| |
| /**< Available execution modes */ |
| enum class ExecutionMode |
| { |
| FastRerun = |
| AclPreferFastRerun, /**< Prefer minimum latency in consecutive runs, might introduce higher startup times */ |
| FastStart = AclPreferFastStart, /**< Prefer minimizing startup time */ |
| }; |
| |
| /** Context class |
| * |
| * Context acts as a central aggregate service for further objects created from it. |
| * It provides, internally, common facilities in order to avoid the use of global |
| * statically initialized objects that can lead to important side-effect under |
| * specific execution contexts. |
| * |
| * For example context contains allocators for object creation, for further backing memory allocation, |
| * any serialization interfaces and other modules that affect the construction of objects, |
| * like program caches for OpenCL. |
| */ |
| class Context : public detail::ObjectBase<AclContext_> |
| { |
| public: |
| /**< Context options */ |
| struct Options |
| { |
| static constexpr int32_t num_threads_auto = -1; /**< Allow runtime to specify number of threads */ |
| |
| /** Default Constructor |
| * |
| * @note By default no precision loss is enabled for operators |
| * @note By default the preferred execution mode is to favor multiple consecutive reruns of an operator |
| */ |
| Options() |
| : Options(ExecutionMode::FastRerun /* mode */, |
| AclCpuCapabilitiesAuto /* caps */, |
| false /* enable_fast_math */, |
| nullptr /* kernel_config */, |
| num_threads_auto /* max_compute_units */, |
| nullptr /* allocator */) |
| { |
| } |
| /** Constructor |
| * |
| * @param[in] mode Execution mode to be used |
| * @param[in] caps Capabilities to be used |
| * @param[in] enable_fast_math Allow precision loss in favor of performance |
| * @param[in] kernel_config Kernel configuration file containing construction tuning meta-data |
| * @param[in] max_compute_units Max compute units that are expected to used |
| * @param[in] allocator Allocator to be used for internal memory allocation |
| */ |
| Options(ExecutionMode mode, |
| AclTargetCapabilities caps, |
| bool enable_fast_math, |
| const char *kernel_config, |
| int32_t max_compute_units, |
| AclAllocator *allocator) |
| { |
| copts.mode = detail::as_cenum<AclExecutionMode>(mode); |
| copts.capabilities = caps; |
| copts.enable_fast_math = enable_fast_math; |
| copts.kernel_config_file = kernel_config; |
| copts.max_compute_units = max_compute_units; |
| copts.allocator = allocator; |
| } |
| |
| AclContextOptions copts{}; |
| }; |
| |
| public: |
| /** Constructor |
| * |
| * @note Serves as a simpler delegate constructor |
| * @note As context options, default conservative options will be used |
| * |
| * @param[in] target Target to create context for |
| * @param[out] status Status information if requested |
| */ |
| explicit Context(Target target, StatusCode *status = nullptr) : Context(target, Options(), status) |
| { |
| } |
| /** Constructor |
| * |
| * @param[in] target Target to create context for |
| * @param[in] options Context construction options |
| * @param[out] status Status information if requested |
| */ |
| Context(Target target, const Options &options, StatusCode *status = nullptr) |
| { |
| AclContext ctx; |
| const auto st = |
| detail::as_enum<StatusCode>(AclCreateContext(&ctx, detail::as_cenum<AclTarget>(target), &options.copts)); |
| reset(ctx); |
| report_status(st, "[Compute Library] Failed to create context"); |
| if (status) |
| { |
| *status = st; |
| } |
| } |
| }; |
| |
| /**< Available tuning modes */ |
| enum class TuningMode |
| { |
| Rapid = AclRapid, |
| Normal = AclNormal, |
| Exhaustive = AclExhaustive |
| }; |
| |
| /** Queue class |
| * |
| * Queue is responsible for the execution related aspects, with main responsibilities those of |
| * scheduling and tuning operators. |
| * |
| * Multiple queues can be created from the same context, and the same operator can be scheduled on each concurrently. |
| * |
| * @note An operator might depend on the maximum possible compute units that are provided in the context, |
| * thus in cases where the number of the scheduling units of the queue are greater might lead to errors. |
| */ |
| class Queue : public detail::ObjectBase<AclQueue_> |
| { |
| public: |
| /**< Queue options */ |
| struct Options |
| { |
| /** Default Constructor |
| * |
| * As default options, no tuning will be performed, and the number of scheduling units will |
| * depends on internal device discovery functionality |
| */ |
| Options() : opts{AclTuningModeNone, 0} {}; |
| /** Constructor |
| * |
| * @param[in] mode Tuning mode to be used |
| * @param[in] compute_units Number of scheduling units to be used |
| */ |
| Options(TuningMode mode, int32_t compute_units) : opts{detail::as_cenum<AclTuningMode>(mode), compute_units} |
| { |
| } |
| |
| AclQueueOptions opts; |
| }; |
| |
| public: |
| /** Constructor |
| * |
| * @note Serves as a simpler delegate constructor |
| * @note As queue options, default conservative options will be used |
| * |
| * @param[in] ctx Context to create queue for |
| * @param[out] status Status information if requested |
| */ |
| explicit Queue(Context &ctx, StatusCode *status = nullptr) : Queue(ctx, Options(), status) |
| { |
| } |
| /** Constructor |
| * |
| * @note As queue options, default conservative options will be used |
| * |
| * @param[in] ctx Context from where the queue will be created from |
| * @param[in] options Queue options to be used |
| * @param[out] status Status information if requested |
| */ |
| explicit Queue(Context &ctx, const Options &options = Options(), StatusCode *status = nullptr) |
| { |
| AclQueue queue; |
| const auto st = detail::as_enum<StatusCode>(AclCreateQueue(&queue, ctx.get(), &options.opts)); |
| reset(queue); |
| report_status(st, "[Compute Library] Failed to create queue!"); |
| if (status) |
| { |
| *status = st; |
| } |
| } |
| /** Block until all the tasks of the queue have been marked as finished |
| * |
| * @return Status code |
| */ |
| StatusCode finish() |
| { |
| return detail::as_enum<StatusCode>(AclQueueFinish(_object.get())); |
| } |
| }; |
| |
| /**< Data type enumeration */ |
| enum class DataType |
| { |
| Unknown = AclDataTypeUnknown, |
| UInt8 = AclUInt8, |
| Int8 = AclInt8, |
| UInt16 = AclUInt16, |
| Int16 = AclInt16, |
| UInt32 = AclUint32, |
| Int32 = AclInt32, |
| Float16 = AclFloat16, |
| BFloat16 = AclBFloat16, |
| Float32 = AclFloat32, |
| }; |
| |
| /** Tensor Descriptor class |
| * |
| * Structure that contains all the required meta-data to represent a tensor |
| */ |
| class TensorDescriptor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] shape Shape of the tensor |
| * @param[in] data_type Data type of the tensor |
| */ |
| TensorDescriptor(const std::vector<int32_t> &shape, DataType data_type) : _shape(shape), _data_type(data_type) |
| { |
| _cdesc.ndims = _shape.size(); |
| _cdesc.shape = _shape.data(); |
| _cdesc.data_type = detail::as_cenum<AclDataType>(_data_type); |
| _cdesc.strides = nullptr; |
| _cdesc.boffset = 0; |
| } |
| /** Constructor |
| * |
| * @param[in] desc C-type descriptor |
| */ |
| explicit TensorDescriptor(const AclTensorDescriptor &desc) |
| { |
| _cdesc = desc; |
| _data_type = detail::as_enum<DataType>(desc.data_type); |
| _shape.reserve(desc.ndims); |
| for (int32_t d = 0; d < desc.ndims; ++d) |
| { |
| _shape.emplace_back(desc.shape[d]); |
| } |
| } |
| /** Get underlying C tensor descriptor |
| * |
| * @return Underlying structure |
| */ |
| const AclTensorDescriptor *get() const |
| { |
| return &_cdesc; |
| } |
| /** Operator to compare two TensorDescriptor |
| * |
| * @param[in] other The instance to compare against |
| * |
| * @return True if two instances have the same shape and data type |
| */ |
| bool operator==(const TensorDescriptor &other) |
| { |
| bool is_same = true; |
| |
| is_same &= _data_type == other._data_type; |
| is_same &= _shape.size() == other._shape.size(); |
| |
| if (is_same) |
| { |
| for (uint32_t d = 0; d < _shape.size(); ++d) |
| { |
| is_same &= _shape[d] == other._shape[d]; |
| } |
| } |
| |
| return is_same; |
| } |
| |
| private: |
| std::vector<int32_t> _shape{}; |
| DataType _data_type{}; |
| AclTensorDescriptor _cdesc{}; |
| }; |
| |
| /** Import memory types */ |
| enum class ImportType |
| { |
| Host = AclImportMemoryType::AclHostPtr |
| }; |
| |
| /** Tensor class |
| * |
| * Tensor is an mathematical construct that can represent an N-Dimensional space. |
| * |
| * @note Maximum dimensionality support is 6 internally at the moment |
| */ |
| class Tensor : public detail::ObjectBase<AclTensor_> |
| { |
| public: |
| /** Constructor |
| * |
| * @note Tensor memory is allocated |
| * |
| * @param[in] ctx Context from where the tensor will be created from |
| * @param[in] desc Tensor descriptor to be used |
| * @param[out] status Status information if requested |
| */ |
| Tensor(Context &ctx, const TensorDescriptor &desc, StatusCode *status = nullptr) : Tensor(ctx, desc, true, status) |
| { |
| } |
| /** Constructor |
| * |
| * @param[in] ctx Context from where the tensor will be created from |
| * @param[in] desc Tensor descriptor to be used |
| * @param[in] allocate Flag to indicate if the tensor needs to be allocated |
| * @param[out] status Status information if requested |
| */ |
| Tensor(Context &ctx, const TensorDescriptor &desc, bool allocate, StatusCode *status) |
| { |
| AclTensor tensor; |
| const auto st = detail::as_enum<StatusCode>(AclCreateTensor(&tensor, ctx.get(), desc.get(), allocate)); |
| reset(tensor); |
| report_status(st, "[Compute Library] Failed to create tensor!"); |
| if (status) |
| { |
| *status = st; |
| } |
| } |
| /** Maps the backing memory of a given tensor that can be used by the host to access any contents |
| * |
| * @return A valid non-zero pointer in case of success else nullptr |
| */ |
| void *map() |
| { |
| void *handle = nullptr; |
| const auto st = detail::as_enum<StatusCode>(AclMapTensor(_object.get(), &handle)); |
| report_status(st, "[Compute Library] Failed to map the tensor and extract the tensor's backing memory!"); |
| return handle; |
| } |
| /** Unmaps tensor's memory |
| * |
| * @param[in] handle Handle to unmap |
| * |
| * @return Status code |
| */ |
| StatusCode unmap(void *handle) |
| { |
| const auto st = detail::as_enum<StatusCode>(AclUnmapTensor(_object.get(), handle)); |
| report_status(st, "[Compute Library] Failed to unmap the tensor!"); |
| return st; |
| } |
| /** Import external memory to a given tensor object |
| * |
| * @param[in] handle External memory handle |
| * @param[in] type Type of memory to be imported |
| * |
| * @return Status code |
| */ |
| StatusCode import(void *handle, ImportType type) |
| { |
| const auto st = detail::as_enum<StatusCode>( |
| AclTensorImport(_object.get(), handle, detail::as_cenum<AclImportMemoryType>(type))); |
| report_status(st, "[Compute Library] Failed to import external memory to tensor!"); |
| return st; |
| } |
| /** Get the size of the tensor in byte |
| * |
| * @note The size isn't based on allocated memory, but based on information in its descriptor (dimensions, data type, etc.). |
| * |
| * @return The size of the tensor in byte |
| */ |
| uint64_t get_size() |
| { |
| uint64_t size{0}; |
| const auto st = detail::as_enum<StatusCode>(AclGetTensorSize(_object.get(), &size)); |
| report_status(st, "[Compute Library] Failed to get the size of the tensor"); |
| return size; |
| } |
| /** Get the descriptor of this tensor |
| * |
| * @return The descriptor describing the characteristics of this tensor |
| */ |
| TensorDescriptor get_descriptor() |
| { |
| AclTensorDescriptor desc; |
| const auto st = detail::as_enum<StatusCode>(AclGetTensorDescriptor(_object.get(), &desc)); |
| report_status(st, "[Compute Library] Failed to get the descriptor of the tensor"); |
| return TensorDescriptor(desc); |
| } |
| }; |
| |
| /** Tensor pack class |
| * |
| * Pack is a utility construct that is used to create a collection of tensors that can then |
| * be passed into operator as inputs. |
| */ |
| class TensorPack : public detail::ObjectBase<AclTensorPack_> |
| { |
| public: |
| /** Pack pair construct */ |
| struct PackPair |
| { |
| /** Constructor |
| * |
| * @param[in] tensor_ Tensor to pack |
| * @param[in] slot_id_ Slot identification of the tensor in respect with the operator |
| */ |
| PackPair(Tensor *tensor_, int32_t slot_id_) : tensor(tensor_), slot_id(slot_id_) |
| { |
| } |
| |
| Tensor *tensor{nullptr}; /**< Tensor object */ |
| int32_t slot_id{AclSlotUnknown}; /**< Slot id in respect with the operator */ |
| }; |
| |
| public: |
| /** Constructor |
| * |
| * @param[in] ctx Context from where the tensor pack will be created from |
| * @param[out] status Status information if requested |
| */ |
| explicit TensorPack(Context &ctx, StatusCode *status = nullptr) |
| { |
| AclTensorPack pack; |
| const auto st = detail::as_enum<StatusCode>(AclCreateTensorPack(&pack, ctx.get())); |
| reset(pack); |
| report_status(st, "[Compute Library] Failure during tensor pack creation"); |
| if (status) |
| { |
| *status = st; |
| } |
| } |
| /** Add tensor to tensor pack |
| * |
| * @param[in] slot_id Slot id of the tensor in respect with the operator |
| * @param[in] tensor Tensor to be added in the pack |
| * |
| * @return Status code |
| */ |
| StatusCode add(Tensor &tensor, int32_t slot_id) |
| { |
| return detail::as_enum<StatusCode>(AclPackTensor(_object.get(), tensor.get(), slot_id)); |
| } |
| /** Add a list of tensors to a tensor pack |
| * |
| * @param[in] packed Pair packs to be added |
| * |
| * @return Status code |
| */ |
| StatusCode add(std::initializer_list<PackPair> packed) |
| { |
| const size_t size = packed.size(); |
| std::vector<int32_t> slots(size); |
| std::vector<AclTensor> tensors(size); |
| int i = 0; |
| for (auto &p : packed) |
| { |
| slots[i] = p.slot_id; |
| tensors[i] = AclTensor(p.tensor); |
| ++i; |
| } |
| return detail::as_enum<StatusCode>(AclPackTensors(_object.get(), tensors.data(), slots.data(), size)); |
| } |
| }; |
| |
| /** Operator class |
| * |
| * Operators are the basic algorithmic blocks responsible for performing distinct operations |
| */ |
| class Operator : public detail::ObjectBase<AclOperator_> |
| { |
| public: |
| /** Run an operator on a given input list |
| * |
| * @param[in,out] queue Queue to scheduler the operator on |
| * @param pack Tensor list to be used as input |
| * |
| * @return Status Code |
| */ |
| StatusCode run(Queue &queue, TensorPack &pack) |
| { |
| return detail::as_cenum<StatusCode>(AclRunOperator(_object.get(), queue.get(), pack.get())); |
| } |
| |
| protected: |
| /** Constructor */ |
| Operator() = default; |
| }; |
| |
| /// Operators |
| using ActivationDesc = AclActivationDescriptor; |
| class Activation : public Operator |
| { |
| public: |
| Activation(Context &ctx, |
| const TensorDescriptor &src, |
| const TensorDescriptor &dst, |
| const ActivationDesc &desc, |
| StatusCode *status = nullptr) |
| { |
| AclOperator op; |
| const auto st = detail::as_enum<StatusCode>(AclActivation(&op, ctx.get(), src.get(), dst.get(), desc)); |
| reset(op); |
| report_status(st, "[Compute Library] Failure during Activation operator creation"); |
| if (status) |
| { |
| *status = st; |
| } |
| } |
| }; |
| } // namespace acl |
| #undef ARM_COMPUTE_IGNORE_UNUSED |
| #endif /* ARM_COMPUTE_ACL_HPP_ */ |