/* * Copyright (c) 2020-2022 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/NEMaxUnpoolingLayerKernel.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" #include "arm_compute/core/utils/misc/ShapeCalculator.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/maxunpool/list.h" #include "support/ToolchainSupport.h" namespace arm_compute { using namespace misc::shape_calculator; namespace { struct MaxUnpoolingSelectorData { DataType dt; }; using MaxUnpoolingSelctorPtr = std::add_pointer::type; using MaxUnpoolingUKernelPtr = std::add_pointer::type; struct MaxUnpoolingKernel { const char *name; const MaxUnpoolingSelctorPtr is_selected; MaxUnpoolingUKernelPtr ukernel; }; static const MaxUnpoolingKernel available_kernels[] = { { "fp32_neon_maxunpooling", [](const MaxUnpoolingSelectorData & data) { return data.dt == DataType::F32; }, REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_maxunpooling) }, #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC { "fp16_neon_maxunpooling", [](const MaxUnpoolingSelectorData & data) { return data.dt == DataType::F16; }, REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_maxunpooling) }, #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC #if defined(ARM_COMPUTE_ENABLE_NEON) { "qs8_neon_maxunpooling", [](const MaxUnpoolingSelectorData & data) { return data.dt == DataType::QASYMM8; }, REGISTER_QASYMM8_NEON(arm_compute::cpu::neon_qs8_maxunpooling) }, { "qu8_neon_maxunpooling", [](const MaxUnpoolingSelectorData & data) { return data.dt == DataType::QASYMM8_SIGNED; }, REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::neon_qu8_maxunpooling) }, #endif //defined(ARM_COMPUTE_ENABLE_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 MaxUnpoolingKernel *get_implementation(const MaxUnpoolingSelectorData &data) { for(const auto &uk : available_kernels) { if(uk.is_selected(data)) { return &uk; } } return nullptr; } Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PoolingLayerInfo &pool_info, const ITensorInfo *indices) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output, indices); ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::U32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, indices); int pool_stride_x = 0; int pool_stride_y = 0; PoolingType pool_type = pool_info.pool_type; const PadStrideInfo pad_stride_info = pool_info.pad_stride_info; std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride(); const int pool_size_x = pool_info.pool_size.width; const int pool_size_y = pool_info.pool_size.height; const Size2D pool_size(pool_size_x, pool_size_y); ARM_COMPUTE_RETURN_ERROR_ON_MSG(pool_type != PoolingType::MAX, "Pooling indices only supported for MAX pooling method"); ARM_COMPUTE_RETURN_ERROR_ON_MSG((pool_size != Size2D(2, 2)), "Pooling indices only supported for pool size 2x2"); if(output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); } return Status{}; } } // namespace NEMaxUnpoolingLayerKernel::NEMaxUnpoolingLayerKernel() : _input(nullptr), _output(nullptr), _indices(nullptr) { } void NEMaxUnpoolingLayerKernel::configure(const ITensor *input, const ITensor *indices, ITensor *output, const PoolingLayerInfo &pool_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), pool_info, indices->info())); _input = input; _output = output; _indices = indices; const TensorShape output_shape = compute_unpool_shape(*input->info(), pool_info); auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); auto window = calculate_max_window(*input->info(), Steps()); INEKernel::configure(window); } Status NEMaxUnpoolingLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *indices, const ITensorInfo *output, const PoolingLayerInfo &pool_info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, indices, output); ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, pool_info, indices)); return Status{}; } void NEMaxUnpoolingLayerKernel::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); const auto *uk = get_implementation(MaxUnpoolingSelectorData{ _input->info()->data_type() }); ARM_COMPUTE_ERROR_ON(uk == nullptr || uk->ukernel == nullptr); uk->ukernel(_input, _output, _indices, window); } } // namespace arm_compute