diff options
Diffstat (limited to 'libs/ARMComputeEx/src/runtime/CL/functions/CLArgMinMax.cpp')
-rw-r--r-- | libs/ARMComputeEx/src/runtime/CL/functions/CLArgMinMax.cpp | 120 |
1 files changed, 0 insertions, 120 deletions
diff --git a/libs/ARMComputeEx/src/runtime/CL/functions/CLArgMinMax.cpp b/libs/ARMComputeEx/src/runtime/CL/functions/CLArgMinMax.cpp deleted file mode 100644 index dff743e89..000000000 --- a/libs/ARMComputeEx/src/runtime/CL/functions/CLArgMinMax.cpp +++ /dev/null @@ -1,120 +0,0 @@ -/* - * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved - * Copyright (c) 2017 ARM Limited. - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ -#include "arm_compute/runtime/CL/functions/CLArgMinMax.h" - -#include "arm_compute/core/CL/kernels/CLArgMinMaxKernel.h" -#include "arm_compute/runtime/CL/CLScheduler.h" - -namespace arm_compute -{ - -CLArgMinMax::CLArgMinMax() - : _input(nullptr), _output(nullptr), _argminmax_axis(), _interm_tensors(), _argminmax_kernels(), - _num_of_kernels() -{ -} - -void CLArgMinMax::configure(ICLTensor *input, ICLTensor *output, std::vector<uint32_t> axis, - ArgOperation op) -{ - ARM_COMPUTE_ERROR_THROW_ON(validate(input->info(), output->info(), axis, op)); - _input = input; - _output = output; - _argminmax_axis = axis; - _arg_op = op; - // NOTE The argminmax_axis must have no duplication. - _num_of_kernels = axis.size(); - const size_t num_of_interm_tensors = _num_of_kernels - 1; - - _interm_tensors = arm_compute::support::cpp14::make_unique<CLTensor[]>(num_of_interm_tensors); - _argminmax_kernels = - arm_compute::support::cpp14::make_unique<CLArgMinMaxKernel[]>(_num_of_kernels); - - TensorShape shape{input->info()->tensor_shape()}; - for (size_t i = 0; i < num_of_interm_tensors; i++) - { - shape.set(_argminmax_axis[i], 1); - _interm_tensors[i].allocator()->init( - TensorInfo(shape, input->info()->num_channels(), input->info()->data_type())); - _interm_tensors[i].allocator()->allocate(); - } - - // Set a vector that is ordered ICLTensors sequentially. - std::vector<ICLTensor *> tensors; - tensors.emplace_back(input); - for (size_t i = 0; i < num_of_interm_tensors; i++) - { - tensors.emplace_back(_interm_tensors.get() + i); - } - tensors.emplace_back(output); - - // Apply ArgMinMax on all kernels - for (size_t i = 0; i < _num_of_kernels; i++) - { - _argminmax_kernels[i].configure(tensors[i], tensors[i + 1], _argminmax_axis[i], op); - } -} - -Status CLArgMinMax::validate(const ITensorInfo *input, const std::vector<uint32_t> &argminmax_axis, - const ITensorInfo *output, ArgOperation op) -{ - const size_t num_of_kernels = argminmax_axis.size(); - const size_t num_of_interm_tensors = num_of_kernels - 1; - - // Create temporary tensor infos - auto interm_tensors = - arm_compute::support::cpp14::make_unique<TensorInfo[]>(num_of_interm_tensors); - - // Create intermediate tensor info - TensorShape shape{input->tensor_shape()}; - - for (size_t i = 0; i < num_of_interm_tensors; i++) - { - shape.set(argminmax_axis[i], 1); - interm_tensors[i].set_data_type(input->data_type()); - interm_tensors[i].set_tensor_shape(shape); - interm_tensors[i].set_num_channels(input->num_channels()); - } - - // Set a vector that is ordered ITensorInfo sequentially. - std::vector<const ITensorInfo *> tensors; - tensors.emplace_back(input); - for (size_t i = 0; i < num_of_interm_tensors; i++) - { - tensors.emplace_back(interm_tensors.get() + i); - } - tensors.emplace_back(output); - - // Validate argminmax only on all kernels - for (size_t i = 0; i < num_of_kernels; i++) - { - ARM_COMPUTE_RETURN_ON_ERROR( - CLArgMinMaxKernel::validate(tensors[i], tensors[i + 1], argminmax_axis[i], op)); - } - - return Status{}; -} - -void CLArgMinMax::run() -{ - for (size_t i = 0; i < _num_of_kernels; ++i) - { - CLScheduler::get().enqueue(_argminmax_kernels[i]); - } -} - -} // namespace arm_compute |