diff options
Diffstat (limited to 'libs/ARMComputeEx/src/core/CL/kernels/CLArgMinMaxKernel.cpp')
| -rw-r--r-- | libs/ARMComputeEx/src/core/CL/kernels/CLArgMinMaxKernel.cpp | 159 |
1 files changed, 0 insertions, 159 deletions
diff --git a/libs/ARMComputeEx/src/core/CL/kernels/CLArgMinMaxKernel.cpp b/libs/ARMComputeEx/src/core/CL/kernels/CLArgMinMaxKernel.cpp deleted file mode 100644 index c1a2ad0be..000000000 --- a/libs/ARMComputeEx/src/core/CL/kernels/CLArgMinMaxKernel.cpp +++ /dev/null @@ -1,159 +0,0 @@ -/* - * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved - * Copyright (c) 2016-2018 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/core/CL/kernels/CLArgMinMaxKernel.h" - -#include "arm_compute/core/CL/CLHelpers.h" -#include "arm_compute/core/CL/CLKernelLibraryEx.h" -#include "arm_compute/core/CL/ICLTensor.h" - -using namespace arm_compute; - -namespace -{ -const TensorShape inferOutputShape(const TensorShape &input_shape, const uint32_t argminmax_axis) -{ - TensorShape out_shape{input_shape}; - - out_shape.set(argminmax_axis, 1); - - return out_shape; -} -} // namespace - -namespace -{ -constexpr unsigned int num_elems_processed_per_iteration = 16; - -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, - const uint32_t argminmax_axis, ArgOperation op) -{ - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32, DataType::F32, - DataType::U8); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - - ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(input, output); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->tensor_shape().total_size() == 0, - "Inputs are not broadcast compatible"); - - const TensorShape output_shape = inferOutputShape(input->tensor_shape(), argminmax_axis); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output_shape.total_size() != output->tensor_shape().total_size(), - "output shape's size does not match argminmax_axis"); - - const auto num_dimensions = input->tensor_shape().num_dimensions(); - ARM_COMPUTE_RETURN_ERROR_ON_MSG( - argminmax_axis >= 0 && argminmax_axis < num_dimensions, - "argminmax_axis must be greater than or equal to 0 and less than (input's rank)."); - return Status{}; -} - -} // namespace - -CLArgMinMaxKernel::CLArgMinMaxKernel() : _input(nullptr), _output(nullptr), _argminmax_axis() {} - -void CLArgMinMaxKernel::configure(const ICLTensor *input, ICLTensor *output, - const uint32_t argminmax_axis, ArgOperation op) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), argminmax_axis)); - - _input = input; - _output = output; - _argminmax_axis = argminmax_axis; - - std::unique_ptr<ITensorInfo> output_info = output->info()->clone(); - output_info->set_tensor_shape(inferOutputShape(input->info()->tensor_shape(), argminmax_axis)); - - // Construct kernel name for argmax and argmin based on axis - std::string kernel_name = "arg_op"; - int op_code = 0; - if (op == ArgOperation::MAX) - { - op_code = 1; - } - else if (op == ArgOperation::MIN) - { - op_code = 2; - } - else - throw std::runtime_error("Operation not supported, yet"); - - // Set kernel build options - std::set<std::string> build_opts; - build_opts.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(output_info->data_type())); - build_opts.emplace("-DDEPTH_OUT=" + support::cpp11::to_string(output_info->dimension(2))); - build_opts.emplace("-DOP_CODE=" + support::cpp11::to_string(op_code)); - - // Create kernel - _kernel = - static_cast<cl::Kernel>(CLKernelLibraryEx::get().create_kernel(kernel_name, build_opts)); - - // Configure kernel window - Window win = calculate_max_window(*output_info, Steps()); - - Coordinates coord; - coord.set_num_dimensions(output_info->num_dimensions()); - output->info()->set_valid_region(ValidRegion(coord, output_info->tensor_shape())); - - ICLKernel::configure_internal(win); -} - -Status CLArgMinMaxKernel::validate(const ITensorInfo *input, const ITensorInfo *output, - const uint32_t argminmax_axis, ArgOperation op) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, argminmax_axis, op)); - - return Status{}; -} - -void CLArgMinMaxKernel::run(const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - const TensorShape &shape_in = _input->info()->tensor_shape(); - - unsigned int idx = 2 * num_arguments_per_4D_tensor(); // Skip the input and output parameters - - _kernel.setArg<cl_int>(idx++, _argminmax_axis); - _kernel.setArg<cl_int>(idx++, shape_in[_argminmax_axis]); - - Window slice_out = window.first_slice_window_4D().collapse(ICLKernel::window(), 2, 4); - - // Setup input slice - Window slice_in(slice_out); - slice_in.set(Window::DimX, Window::Dimension(0, 0, 0)); - slice_in.set(Window::DimY, Window::Dimension(0, 0, 0)); - slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); - slice_in.set(3, Window::Dimension(0, 0, 0)); - - // Copy output's shape in order to use for recovering at end of this method - const TensorShape shape_out = _output->info()->tensor_shape(); - _output->info()->set_tensor_shape(inferOutputShape(shape_in, _argminmax_axis)); - - do - { - unsigned int idx = 0; - add_4D_tensor_argument(idx, _input, slice_in); - add_4D_tensor_argument(idx, _output, slice_out); - enqueue(queue, *this, slice_out); - } while (window.slide_window_slice_4D(slice_in) && window.slide_window_slice_4D(slice_out)); - - // Recover output's shape of output tensor - _output->info()->set_tensor_shape(shape_out); -} |