/* * 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/CpuSubKernel.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/sub/neon/list.h" namespace arm_compute { namespace cpu { namespace kernels { namespace { struct SubSelectorData { DataType dt; }; using SubSelectorPtr = std::add_pointer::type; using SubKernelPtr = std::add_pointer::type; struct SubKernel { const char *name; const SubSelectorPtr is_selected; SubKernelPtr ukernel; }; static const SubKernel available_kernels[] = { { "neon_fp32_sub", [](const SubSelectorData & data) { return (data.dt == DataType::F32); }, REGISTER_FP32_NEON(arm_compute::cpu::sub_same_neon) }, #if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) { "neon_fp16_sub", [](const SubSelectorData & data) { return (data.dt == DataType::F16); }, REGISTER_FP16_NEON(arm_compute::cpu::sub_same_neon) }, #endif /* defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) */ { "neon_u8_sub", [](const SubSelectorData & data) { return (data.dt == DataType::U8); }, REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon) }, { "neon_s16_sub", [](const SubSelectorData & data) { return (data.dt == DataType::S16); }, REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon) }, { "neon_s32_sub", [](const SubSelectorData & data) { return (data.dt == DataType::S32); }, REGISTER_INTEGER_NEON(arm_compute::cpu::sub_same_neon) }, { "neon_qu8_sub", [](const SubSelectorData & data) { return (data.dt == DataType::QASYMM8); }, REGISTER_QASYMM8_NEON(arm_compute::cpu::sub_qasymm8_neon) }, { "neon_qs8_sub", [](const SubSelectorData & data) { return (data.dt == DataType::QASYMM8_SIGNED); }, REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::sub_qasymm8_signed_neon) }, { "neon_qs16_sub", [](const SubSelectorData & data) { return (data.dt == DataType::QSYMM16); }, REGISTER_QSYMM16_NEON(arm_compute::cpu::sub_qsymm16_neon) }, }; /** Micro-kernel selector * * @param[in] data Selection data passed to help pick the appropriate micro-kernel * * @return A matching micro-kernel else nullptr */ const SubKernel *get_implementation(DataType dt) { for(const auto &uk : available_kernels) { if(uk.is_selected({ dt })) { return &uk; } } return nullptr; } inline 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::QSYMM16, DataType::S16, DataType::S32, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src0, &src1); const auto *uk = get_implementation(src0.data_type()); ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr); 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(is_data_type_quantized(src0.data_type()) && (policy == ConvertPolicy::WRAP), "Convert policy cannot be WRAP if datatype is quantized"); // 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"); } return Status{}; } } // namespace void CpuSubKernel::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 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()); const auto *uk = get_implementation(src0->data_type()); ARM_COMPUTE_ERROR_ON_NULLPTR(uk); _policy = policy; _run_method = uk->ukernel; _name = std::string("CpuSubKernel").append("/").append(uk->name); // CpuSubKernel doesn't need padding so update_window_and_padding() can be skipped Window win = calculate_max_window(out_shape, Steps()); ICpuKernel::configure(win); } Status CpuSubKernel::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)); return Status{}; } void CpuSubKernel::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(_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 *CpuSubKernel::name() const { return _name.c_str(); } } // namespace kernels } // namespace cpu } // namespace arm_compute