/* * Copyright (c) 2017-2021, 2023 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/core/NEON/kernels/NENormalizationLayerKernel.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" #include "src/core/common/Registrars.h" #include "src/core/CPP/Validate.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/NormalizationHelpers.h" #include "src/core/helpers/WindowHelpers.h" #include "src/core/NEON/NEFixedPoint.h" #include "src/core/NEON/NEMath.h" #include "src/core/NEON/wrapper/wrapper.h" #include "src/cpu/kernels/norm_layer/generic/neon/impl.h" #include "src/cpu/kernels/norm_layer/generic/neon/list.h" namespace arm_compute { namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *input_squared, const ITensorInfo *output, const NormalizationLayerInfo &norm_info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, input_squared, output); ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, input_squared); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, input_squared); ARM_COMPUTE_RETURN_ERROR_ON_MSG(!(norm_info.norm_size() % 2), "Normalization size should be odd"); // Checks performed when output is configured if (output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); } return Status{}; } } // namespace NENormalizationLayerKernel::NENormalizationLayerKernel() : _func(nullptr), _input(nullptr), _input_squared(nullptr), _output(nullptr), _norm_info(NormType::IN_MAP_1D) { } void NENormalizationLayerKernel::configure(const ITensor *input, const ITensor *input_squared, ITensor *output, NormalizationLayerInfo norm_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, input_squared, output); // Output tensor auto initialization if not yet initialized auto_init_if_empty(*output->info(), *input->info()); // Perform validation step ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), input_squared->info(), output->info(), norm_info)); const unsigned int norm_idx = get_normalization_dimension_index(input->info()->data_layout(), norm_info); _input = input; _input_squared = input_squared; _output = output; _norm_info = norm_info; switch (_input->info()->data_type()) { case DataType::F32: { switch (norm_idx) { case 0: { if (norm_info.type() == NormType::IN_MAP_2D) { _func = REGISTER_FP32_NEON(cpu::neon_normalize_float32_4_0_2D); } else { _func = REGISTER_FP32_NEON(cpu::neon_normalize_float32_4_0); } break; } case 1: if (norm_info.type() == NormType::IN_MAP_2D) { _func = REGISTER_FP32_NEON(cpu::neon_normalize_float32_4_1_2D); } else { _func = REGISTER_FP32_NEON(cpu::neon_normalize_float32_4_1); } break; case 2: _func = REGISTER_FP32_NEON(cpu::neon_normalize_float32_4_2); break; default: break; } break; } #ifdef ARM_COMPUTE_ENABLE_FP16 case DataType::F16: { switch (norm_idx) { case 0: { if (norm_info.type() == NormType::IN_MAP_2D) { _func = REGISTER_FP16_NEON(cpu::neon_normalize_float16_8_0_2D); } else { _func = REGISTER_FP16_NEON(cpu::neon_normalize_float16_8_0); } break; } case 1: if (norm_info.type() == NormType::IN_MAP_2D) { _func = REGISTER_FP16_NEON(cpu::neon_normalize_float16_8_1_2D); } else { _func = REGISTER_FP16_NEON(cpu::neon_normalize_float16_8_1); } break; case 2: _func = REGISTER_FP16_NEON(cpu::neon_normalize_float16_8_2); break; default: break; } break; } #endif /* ARM_COMPUTE_ENABLE_FP16 */ default: ARM_COMPUTE_ERROR("NOT SUPPORTED!"); } // Configure kernel window Window win = calculate_max_window(*input->info(), Steps()); INEKernel::configure(win); } Status NENormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *input_squared, const ITensorInfo *output, const NormalizationLayerInfo norm_info) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, input_squared, output, norm_info)); return Status{}; } void NENormalizationLayerKernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); ARM_COMPUTE_ERROR_ON(_func == nullptr); // Run function (*_func)(window, _input, _input_squared, _output, _norm_info); } } // namespace arm_compute