From 3f26ef4f9a2d447adb324dd69aec7c49cf7905fc Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Tue, 23 Feb 2021 10:01:33 +0000 Subject: Add tensor related data structures for the new API Adds the following: - TensorDescriptor: which is responsible for holding the information needed to represent a tensor (e.g. shape, dimensions, etc) - Tensor: an aggreate object of a descriptor and a backing memory - TensorPack: A map of tensor that can be passed to operators as inputs/outputs Signed-off-by: Georgios Pinitas Change-Id: I02734ac6ad85700d91d6e73217b4637adbf5d177 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5260 Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins --- arm_compute/Acl.hpp | 252 +++++++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 238 insertions(+), 14 deletions(-) (limited to 'arm_compute/Acl.hpp') diff --git a/arm_compute/Acl.hpp b/arm_compute/Acl.hpp index b74e65430c..a009894438 100644 --- a/arm_compute/Acl.hpp +++ b/arm_compute/Acl.hpp @@ -29,6 +29,7 @@ #include #include #include +#include #if defined(ARM_COMPUTE_EXCEPTIONS_ENABLED) #include @@ -41,6 +42,8 @@ namespace acl { // Forward declarations class Context; +class Tensor; +class TensorPack; /**< Status code enum */ enum class StatusCode @@ -80,6 +83,8 @@ struct ObjectDeleter }; OBJECT_DELETER(AclContext, AclDestroyContext) +OBJECT_DELETER(AclTensor, AclDestroyTensor) +OBJECT_DELETER(AclTensorPack, AclDestroyTensorPack) #undef OBJECT_DELETER @@ -256,13 +261,12 @@ private: * * @return Status code */ -static inline StatusCode report_status(StatusCode status, const std::string &msg) +static inline void report_status(StatusCode status, const std::string &msg) { if(status != StatusCode::Success) { throw Status(status, msg); } - return status; } #else /* defined(ARM_COMPUTE_EXCEPTIONS_ENABLED) */ /** Reports a status code @@ -275,10 +279,10 @@ static inline StatusCode report_status(StatusCode status, const std::string &msg * * @return Status code */ -static inline StatusCode report_status(StatusCode status, const std::string &msg) +static inline void report_status(StatusCode status, const std::string &msg) { + ARM_COMPUTE_IGNORE_UNUSED(status); ARM_COMPUTE_IGNORE_UNUSED(msg); - return status; } #endif /* defined(ARM_COMPUTE_EXCEPTIONS_ENABLED) */ @@ -313,12 +317,22 @@ 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() = default; + 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 @@ -335,14 +349,15 @@ public: int32_t max_compute_units, AclAllocator *allocator) { - opts.mode = detail::as_cenum(mode); - opts.capabilities = caps; - opts.enable_fast_math = enable_fast_math; - opts.kernel_config_file = kernel_config; - opts.max_compute_units = max_compute_units; - opts.allocator = allocator; + copts.mode = detail::as_cenum(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 opts{ acl_default_ctx_options }; + + AclContextOptions copts{}; }; public: @@ -367,14 +382,223 @@ public: Context(Target target, const Options &options, StatusCode *status = nullptr) { AclContext ctx; - const auto st = detail::as_enum(AclCreateContext(&ctx, detail::as_cenum(target), &options.opts)); + const auto st = detail::as_enum(AclCreateContext(&ctx, detail::as_cenum(target), &options.copts)); reset(ctx); - report_status(st, "Failure during context creation"); + report_status(st, "[Arm Compute Library] Failed to create context"); + if(status) + { + *status = st; + } + } +}; + +/**< 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 &shape, DataType data_type) + : _shape(shape), _data_type(data_type) + { + _cdesc.ndims = _shape.size(); + _cdesc.shape = _shape.data(); + _cdesc.data_type = detail::as_cenum(_data_type); + _cdesc.strides = nullptr; + _cdesc.boffset = 0; + } + /** Get underlying C tensor descriptor + * + * @return Underlying structure + */ + const AclTensorDescriptor *get() const + { + return &_cdesc; + } + +private: + std::vector _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 +{ +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(AclCreateTensor(&tensor, ctx.get(), desc.get(), allocate)); + reset(tensor); + report_status(st, "[Arm 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(AclMapTensor(_object.get(), &handle)); + report_status(st, "[Arm 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(AclUnmapTensor(_object.get(), handle)); + report_status(st, "[Arm 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(AclTensorImport(_object.get(), handle, detail::as_cenum(type))); + report_status(st, "[Arm Compute Library] Failed to import external memory to tensor!"); + return st; + } +}; + +/** 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 +{ +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(AclCreateTensorPack(&pack, ctx.get())); + reset(pack); + report_status(st, "[Arm 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(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 packed) + { + const size_t size = packed.size(); + std::vector slots(size); + std::vector tensors(size); + int i = 0; + for(auto &p : packed) + { + slots[i] = p.slot_id; + tensors[i] = AclTensor(p.tensor); + ++i; + } + return detail::as_enum(AclPackTensors(_object.get(), tensors.data(), slots.data(), size)); + } }; } // namespace acl #undef ARM_COMPUTE_IGNORE_UNUSED -- cgit v1.2.1