/* * Copyright (c) 2018-2021 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/runtime/cpu/operators/CpuConcatenate.h" #include "src/core/cpu/kernels/CpuConcatenateBatchKernel.h" #include "src/core/cpu/kernels/CpuConcatenateDepthKernel.h" #include "src/core/cpu/kernels/CpuConcatenateHeightKernel.h" #include "src/core/cpu/kernels/CpuConcatenateWidthKernel.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "src/core/helpers/AutoConfiguration.h" namespace arm_compute { namespace cpu { CpuConcatenate::CpuConcatenate() : _concat_kernels(), _num_srcs(0), _axis(0) { } void CpuConcatenate::configure(const std::vector &srcs_vector, ITensorInfo *dst, size_t axis) { ARM_COMPUTE_ERROR_ON(dst == nullptr); _axis = axis; _num_srcs = srcs_vector.size(); TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(srcs_vector, axis); // Output auto inizialitation if not yet initialized auto_init_if_empty(*dst, dst_shape, 1, srcs_vector[0]->data_type()); ARM_COMPUTE_ERROR_THROW_ON(CpuConcatenate::validate(srcs_vector, dst, axis)); unsigned int offset = 0; for(unsigned int i = 0; i < _num_srcs; ++i) { switch(axis) { case Window::DimX: { auto kernel = std::make_unique(); kernel->configure(srcs_vector.at(i), offset, dst); _concat_kernels.emplace_back(std::move(kernel)); break; } case Window::DimY: { auto kernel = std::make_unique(); kernel->configure(srcs_vector.at(i), offset, dst); _concat_kernels.emplace_back(std::move(kernel)); break; } case Window::DimZ: { auto kernel = std::make_unique(); kernel->configure(srcs_vector.at(i), offset, dst); _concat_kernels.emplace_back(std::move(kernel)); break; } case 3: { auto kernel = std::make_unique(); kernel->configure(srcs_vector.at(i), offset, dst); _concat_kernels.emplace_back(std::move(kernel)); break; } default: ARM_COMPUTE_ERROR("Axis not supported"); } offset += srcs_vector.at(i)->dimension(axis); } } Status CpuConcatenate::validate(const std::vector &srcs_vector, const ITensorInfo *dst, size_t axis) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(dst); ARM_COMPUTE_RETURN_ERROR_ON(srcs_vector.size() < 2); unsigned int offset = 0; for(const auto &src : srcs_vector) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src); switch(axis) { case Window::DimX: { ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateWidthKernel::validate(src, offset, dst)); break; } case Window::DimY: { ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateHeightKernel::validate(src, offset, dst)); break; } case Window::DimZ: { ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateDepthKernel::validate(src, offset, dst)); break; } case 3: { ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuConcatenateBatchKernel::validate(src, offset, dst)); break; } default: ARM_COMPUTE_ERROR("Axis not supported"); } offset += src->dimension(axis); } if(dst->total_size() != 0) { TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(srcs_vector, axis); ARM_COMPUTE_RETURN_ERROR_ON(dst_shape.total_size() != dst->tensor_shape().total_size()); } return Status{}; } void CpuConcatenate::run(ITensorPack &tensors) { if(tensors.empty()) { ARM_COMPUTE_ERROR("No inputs provided"); } if(static_cast(tensors.size() - 1) != static_cast(_num_srcs)) { ARM_COMPUTE_ERROR("Configured with different number of inputs"); } int i = 0; for(auto &k : _concat_kernels) { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC, tensors.get_const_tensor(ACL_SRC_VEC + i)); pack.add_tensor(TensorType::ACL_DST, tensors.get_tensor(ACL_DST)); NEScheduler::get().schedule_op(k.get(), Window::DimY, k->window(), pack); ++i; } } } // namespace cpu } // namespace arm_compute