| /* |
| * 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/gpu/cl/operators/ClConcatenate.h" |
| |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| |
| #include "src/gpu/cl/kernels/ClBatchConcatenateKernel.h" |
| #include "src/gpu/cl/kernels/ClDepthConcatenateKernel.h" |
| #include "src/gpu/cl/kernels/ClHeightConcatenateKernel.h" |
| #include "src/gpu/cl/kernels/ClWidthConcatenate2TensorsKernel.h" |
| #include "src/gpu/cl/kernels/ClWidthConcatenate4TensorsKernel.h" |
| #include "src/gpu/cl/kernels/ClWidthConcatenateKernel.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Types.h" |
| |
| #include "src/common/utils/Log.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| |
| namespace arm_compute |
| { |
| namespace opencl |
| { |
| void ClConcatenate::configure(const CLCompileContext &compile_context, const std::vector<ITensorInfo *> &src_vector, ITensorInfo *dst, size_t axis) |
| { |
| ARM_COMPUTE_ERROR_ON(dst == nullptr); |
| ARM_COMPUTE_LOG_PARAMS(src_vector, dst, axis); |
| _axis = axis; |
| _num_inputs = src_vector.size(); |
| |
| TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(src_vector, _axis); |
| std::vector<const ITensorInfo *> const_src_vector(src_vector.size()); |
| std::transform(src_vector.begin(), src_vector.end(), const_src_vector.begin(), [](ITensorInfo * t) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(t); |
| return t; |
| }); |
| |
| // dst auto inizialitation if not yet initialized |
| auto_init_if_empty(*dst, dst_shape, 1, src_vector[0]->data_type()); |
| ARM_COMPUTE_ERROR_THROW_ON(ClConcatenate::validate(const_src_vector, dst, axis)); |
| |
| unsigned int offset = 0; |
| switch(_axis) |
| { |
| case Window::DimX: |
| { |
| switch(_num_inputs) |
| { |
| case 2: |
| { |
| // Configure WidthConcatenate2Tensors kernel |
| auto kernel = std::make_unique<kernels::ClWidthConcatenate2TensorsKernel>(); |
| kernel->configure(compile_context, src_vector.at(0), src_vector.at(1), dst); |
| _concat_kernels.emplace_back(std::move(kernel)); |
| break; |
| } |
| case 4: |
| { |
| // Configure WidthConcatenate4Tensors kernel |
| auto kernel = std::make_unique<kernels::ClWidthConcatenate4TensorsKernel>(); |
| kernel->configure(compile_context, src_vector.at(0), src_vector.at(1), src_vector.at(2), src_vector.at(3), dst); |
| _concat_kernels.emplace_back(std::move(kernel)); |
| break; |
| } |
| default: |
| { |
| // Configure generic case WidthConcatenate kernels |
| for(unsigned int i = 0; i < _num_inputs; ++i) |
| { |
| auto kernel = std::make_unique<kernels::ClWidthConcatenateKernel>(); |
| kernel->configure(compile_context, src_vector.at(i), offset, dst); |
| offset += src_vector.at(i)->dimension(_axis); |
| _concat_kernels.emplace_back(std::move(kernel)); |
| } |
| break; |
| } |
| } |
| break; |
| } |
| case Window::DimY: |
| { |
| for(unsigned int i = 0; i < _num_inputs; ++i) |
| { |
| auto kernel = std::make_unique<kernels::ClHeightConcatenateKernel>(); |
| kernel->configure(compile_context, src_vector.at(i), offset, dst); |
| offset += src_vector.at(i)->dimension(_axis); |
| _concat_kernels.emplace_back(std::move(kernel)); |
| } |
| break; |
| } |
| case Window::DimZ: |
| { |
| for(unsigned int i = 0; i < _num_inputs; ++i) |
| { |
| auto kernel = std::make_unique<kernels::ClDepthConcatenateKernel>(); |
| kernel->configure(compile_context, src_vector.at(i), offset, dst); |
| offset += src_vector.at(i)->dimension(_axis); |
| _concat_kernels.emplace_back(std::move(kernel)); |
| } |
| break; |
| } |
| case 3: |
| { |
| for(unsigned int i = 0; i < _num_inputs; ++i) |
| { |
| auto kernel = std::make_unique<kernels::ClBatchConcatenateKernel>(); |
| kernel->configure(compile_context, src_vector.at(i), offset, dst); |
| offset += src_vector.at(i)->dimension(_axis); |
| _concat_kernels.emplace_back(std::move(kernel)); |
| } |
| break; |
| } |
| default: |
| ARM_COMPUTE_ERROR("Axis not supported"); |
| } |
| } |
| |
| Status ClConcatenate::validate(const std::vector<const ITensorInfo *> &src_vector, const ITensorInfo *dst, size_t axis) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON(dst == nullptr); |
| const unsigned int num_inputs = src_vector.size(); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(dst); |
| ARM_COMPUTE_RETURN_ERROR_ON(num_inputs < 2); |
| |
| unsigned int offset = 0; |
| switch(axis) |
| { |
| case Window::DimX: |
| { |
| switch(num_inputs) |
| { |
| case 2: |
| // Validate WidthConcatenate2Tensors kernels if there are 2 inputs |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src_vector[0], src_vector[1]); |
| ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClWidthConcatenate2TensorsKernel::validate(src_vector[0], src_vector[1], dst)); |
| break; |
| case 4: |
| // Validate WidthConcatenate4Tensors kernels if there are 4 inputs |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src_vector[0], src_vector[1], src_vector[2], src_vector[3]); |
| ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClWidthConcatenate4TensorsKernel::validate(src_vector[0], src_vector[1], src_vector[2], src_vector[3], dst)); |
| break; |
| default: |
| // Validate generic case of WidthConcatenate kernel |
| for(const auto &src : src_vector) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src); |
| ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClWidthConcatenateKernel::validate(src, offset, dst)); |
| offset += src->dimension(axis); |
| } |
| break; |
| } |
| break; |
| } |
| case Window::DimY: |
| { |
| for(const auto &src : src_vector) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClHeightConcatenateKernel::validate(src, offset, dst)); |
| offset += src->dimension(axis); |
| } |
| break; |
| } |
| case Window::DimZ: |
| { |
| for(const auto &src : src_vector) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClDepthConcatenateKernel::validate(src, offset, dst)); |
| offset += src->dimension(axis); |
| } |
| break; |
| } |
| case 3: |
| { |
| for(const auto &src : src_vector) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClBatchConcatenateKernel::validate(src, offset, dst)); |
| offset += src->dimension(axis); |
| } |
| break; |
| } |
| default: |
| ARM_COMPUTE_ERROR("Axis not supported"); |
| } |
| |
| if(dst->total_size() != 0) |
| { |
| TensorShape dst_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(src_vector, axis); |
| ARM_COMPUTE_RETURN_ERROR_ON(dst_shape.total_size() != dst->tensor_shape().total_size()); |
| } |
| |
| return Status{}; |
| } |
| |
| void ClConcatenate::run(ITensorPack &tensors) |
| { |
| if(tensors.empty()) |
| { |
| ARM_COMPUTE_ERROR("No inputs provided"); |
| } |
| |
| if(static_cast<int>(tensors.size()) - 1 != static_cast<int>(_num_inputs)) |
| { |
| ARM_COMPUTE_ERROR("Configured with different number of inputs"); |
| } |
| |
| if(_axis == Window::DimX && (_num_inputs == 2 || _num_inputs == 4)) |
| { |
| ARM_COMPUTE_ERROR_ON(_concat_kernels.empty()); |
| CLScheduler::get().enqueue_op(*_concat_kernels.at(0), tensors, true); |
| } |
| else |
| { |
| 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)); |
| CLScheduler::get().enqueue_op(*k, pack, true); |
| ++i; |
| } |
| } |
| } |
| } // namespace opencl |
| } // namespace arm_compute |