/* * 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. */ #include "src/cpu/kernels/CpuAddKernel.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Validate.h" #include "src/core/CPP/Validate.h" #include "src/core/common/Registrars.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" #include "src/cpu/kernels/add/list.h" #include namespace arm_compute { namespace cpu { namespace kernels { namespace { struct AddSelectorData { DataType dt; const CPUInfo &ci; }; using AddSelectorPtr = std::add_pointer::type; using AddKernelPtr = std::add_pointer::type; struct AddKernel { const char *name; const AddSelectorPtr is_selected; AddKernelPtr ukernel; }; static const AddKernel available_kernels[] = { #if defined(ARM_COMPUTE_ENABLE_SVE2) { "sve2_qu8_add", [](const AddSelectorData & data) { return (data.dt == DataType::QASYMM8) && data.ci.has_sve2(); }, REGISTER_QASYMM8_SVE2(arm_compute::cpu::add_qasymm8_sve2) }, { "sve2_qs8_add", [](const AddSelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED) && data.ci.has_sve2(); }, REGISTER_QASYMM8_SIGNED_SVE2(arm_compute::cpu::add_qasymm8_signed_sve2) }, { "sve2_qs16_add", [](const AddSelectorData & data) { return (data.dt == DataType::QSYMM16) && data.ci.has_sve2(); }, REGISTER_QSYMM16_SVE2(arm_compute::cpu::add_qsymm16_sve2) }, #endif /* !defined(ARM_COMPUTE_ENABLE_SVE2) */ #if defined(ARM_COMPUTE_ENABLE_SVE) { "sve_fp32_add", [](const AddSelectorData & data) { return (data.dt == DataType::F32) && data.ci.has_sve(); }, REGISTER_FP32_SVE(arm_compute::cpu::add_fp32_sve) }, { "sve_fp16_add", [](const AddSelectorData & data) { return (data.dt == DataType::F16) && data.ci.has_sve(); }, REGISTER_FP16_SVE(arm_compute::cpu::add_fp16_sve) }, { "sve_u8_add", [](const AddSelectorData & data) { return (data.dt == DataType::U8) && data.ci.has_sve(); }, REGISTER_INTEGER_SVE(arm_compute::cpu::add_u8_sve) }, { "sve_s16_add", [](const AddSelectorData & data) { return (data.dt == DataType::S16) && data.ci.has_sve(); }, REGISTER_INTEGER_SVE(arm_compute::cpu::add_s16_sve) }, { "sve_s32_add", [](const AddSelectorData & data) { return (data.dt == DataType::S32) && data.ci.has_sve(); }, REGISTER_INTEGER_SVE(arm_compute::cpu::add_s32_sve) }, #endif /* defined(ARM_COMPUTE_ENABLE_SVE) */ #if defined(ARM_COMPUTE_ENABLE_NEON) { "neon_fp32_add", [](const AddSelectorData & data) { return (data.dt == DataType::F32); }, REGISTER_FP32_NEON(arm_compute::cpu::add_fp32_neon) }, #if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) { "neon_fp16_add", [](const AddSelectorData & data) { return (data.dt == DataType::F16) && data.ci.has_fp16(); }, REGISTER_FP16_NEON(arm_compute::cpu::add_fp16_neon) }, #endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) */ { "neon_u8_add", [](const AddSelectorData & data) { return (data.dt == DataType::U8); }, REGISTER_INTEGER_NEON(arm_compute::cpu::add_u8_neon) }, { "neon_s16_add", [](const AddSelectorData & data) { return (data.dt == DataType::S16); }, REGISTER_INTEGER_NEON(arm_compute::cpu::add_s16_neon) }, { "neon_s32_add", [](const AddSelectorData & data) { return (data.dt == DataType::S32); }, REGISTER_INTEGER_NEON(arm_compute::cpu::add_s32_neon) }, #endif /* defined(ARM_COMPUTE_ENABLE_NEON) */ #if defined(ARM_COMPUTE_ENABLE_NEON) || defined(ARM_COMPUTE_ENABLE_SVE) { "neon_qu8_add", [](const AddSelectorData & data) { return (data.dt == DataType::QASYMM8); }, REGISTER_QASYMM8_NEON(arm_compute::cpu::add_qasymm8_neon) }, { "neon_qs8_add", [](const AddSelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); }, REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::add_qasymm8_signed_neon) }, { "neon_qs16_add", [](const AddSelectorData & data) { return (data.dt == DataType::QSYMM16); }, REGISTER_QSYMM16_NEON(arm_compute::cpu::add_qsymm16_neon) }, #endif /* defined(ARM_COMPUTE_ENABLE_NEON) || defined(ARM_COMPUTE_ENABLE_SVE) */ }; /** Micro-kernel selector * * @param[in] data Selection data passed to help pick the appropriate micro-kernel * * @return A matching micro-kernel else nullptr */ const AddKernel *get_implementation(const CPUInfo &cpuinfo, DataType dt) { for(const auto &uk : available_kernels) { if(uk.is_selected({ dt, cpuinfo })) { return &uk; } } return nullptr; } Status validate_arguments(const ITensorInfo &src0, const ITensorInfo &src1, const ITensorInfo &dst, ConvertPolicy policy) { ARM_COMPUTE_UNUSED(policy); ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&src0); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src0, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::S32, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src0, &src1); const TensorShape out_shape = TensorShape::broadcast_shape(src0.tensor_shape(), src1.tensor_shape()); ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); ARM_COMPUTE_RETURN_ERROR_ON_MSG((src0.tensor_shape().x() != src1.tensor_shape().x()) && ((src0.data_type() != src1.data_type()) || (src0.data_type() != dst.data_type()) || (src1.data_type() != dst.data_type())), "Broadcasting across width is supported on configurations where all tensors have the same data type"); // Validate in case of configured dst if(dst.total_size() > 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src0, &dst); ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst.tensor_shape(), 0), "Wrong shape for dst"); } const auto *uk = get_implementation(CPUInfo::get(), src0.data_type()); ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr); return Status{}; } std::pair validate_and_configure_window(const ITensorInfo &src0, const ITensorInfo &src1, ITensorInfo &dst) { const TensorShape &out_shape = TensorShape::broadcast_shape(src0.tensor_shape(), src1.tensor_shape()); // Auto initialize dst if not initialized set_shape_if_empty(dst, out_shape); set_data_type_if_unknown(dst, src0.data_type()); Window win = calculate_max_window(out_shape, Steps()); // CpuAddKernel doesn't need padding so update_window_and_padding() can be skipped return std::make_pair(Status{}, win); } } // namespace void CpuAddKernel::configure(const ITensorInfo *src0, const ITensorInfo *src1, ITensorInfo *dst, ConvertPolicy policy) { ARM_COMPUTE_ERROR_ON_NULLPTR(src0, src1, dst); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*src0, *src1, *dst, policy)); const auto uk = get_implementation(CPUInfo::get(), src0->data_type()); ARM_COMPUTE_ERROR_ON_NULLPTR(uk); _policy = policy; _run_method = uk->ukernel; _name = std::string("CpuAddKernel").append("/").append(uk->name); // Configure kernel window auto win_config = validate_and_configure_window(*src0, *src1, *dst); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICpuKernel::configure(win_config.second); } Status CpuAddKernel::validate(const ITensorInfo *src0, const ITensorInfo *src1, const ITensorInfo *dst, ConvertPolicy policy) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src0, src1, dst); ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*src0, *src1, *dst, policy)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(*src0->clone(), *src1->clone(), *dst->clone()).first); return Status{}; } void CpuAddKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window); ARM_COMPUTE_ERROR_ON(tensors.empty()); ARM_COMPUTE_ERROR_ON(_run_method == nullptr); const ITensor *src0 = tensors.get_const_tensor(TensorType::ACL_SRC_0); const ITensor *src1 = tensors.get_const_tensor(TensorType::ACL_SRC_1); ITensor *dst = tensors.get_tensor(TensorType::ACL_DST); _run_method(src0, src1, dst, _policy, window); } const char *CpuAddKernel::name() const { return _name.c_str(); } size_t CpuAddKernel::get_mws(const CPUInfo &platform, size_t thread_count) const { ARM_COMPUTE_UNUSED(thread_count); // Tuning results that gave optimized results in performance investigation if(platform.get_cpu_model() == CPUModel::A73) { return 10240; } else if (platform.get_cpu_model() == CPUModel::A76) { return 9216; } else { return ICPPKernel::default_mws; } } } // namespace kernels } // namespace cpu } // namespace arm_compute