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Diffstat (limited to 'src/core/CL/kernels/CLMeanStdDevKernel.cpp')
-rw-r--r-- | src/core/CL/kernels/CLMeanStdDevKernel.cpp | 134 |
1 files changed, 134 insertions, 0 deletions
diff --git a/src/core/CL/kernels/CLMeanStdDevKernel.cpp b/src/core/CL/kernels/CLMeanStdDevKernel.cpp new file mode 100644 index 0000000000..b0b748f466 --- /dev/null +++ b/src/core/CL/kernels/CLMeanStdDevKernel.cpp @@ -0,0 +1,134 @@ +/* + * Copyright (c) 2016, 2017 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 "arm_compute/core/CL/kernels/CLMeanStdDevKernel.h" + +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +#include <cmath> +#include <set> +#include <string> + +using namespace arm_compute; + +CLMeanStdDevKernel::CLMeanStdDevKernel() + : _input(nullptr), _mean(nullptr), _stddev(nullptr), _global_sum(nullptr), _global_sum_squared(nullptr) +{ +} + +void CLMeanStdDevKernel::configure(const ICLImage *input, float *mean, cl::Buffer *global_sum, float *stddev, cl::Buffer *global_sum_squared) +{ + ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); + ARM_COMPUTE_ERROR_ON(nullptr == mean); + ARM_COMPUTE_ERROR_ON(nullptr == global_sum); + ARM_COMPUTE_ERROR_ON(stddev && nullptr == global_sum_squared); + + _input = input; + _mean = mean; + _stddev = stddev; + _global_sum = global_sum; + _global_sum_squared = global_sum_squared; + + // Create kernel + std::set<std::string> build_opts; + + if(_stddev != nullptr) + { + build_opts.insert("-DSTDDEV"); + } + + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("mean_stddev_accumulate", build_opts)); + + // Set fixed arguments + unsigned int idx = num_arguments_per_2D_tensor(); //Skip the input parameters + + _kernel.setArg(idx++, static_cast<cl_uint>(input->info()->dimension(1))); + _kernel.setArg(idx++, *_global_sum); + + if(_stddev != nullptr) + { + _kernel.setArg(idx++, *_global_sum_squared); + } + + // Configure kernel window + constexpr unsigned int num_elems_processed_per_iteration_x = 8; + const unsigned int num_elems_processed_per_iteration_y = input->info()->dimension(1); + + Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); + AccessWindowRectangle input_access(input->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y); + update_window_and_padding(win, input_access); + + ICLKernel::configure(win); +} + +void CLMeanStdDevKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + // Clear sums + static const cl_ulong zero = 0; + queue.enqueueWriteBuffer(*_global_sum, CL_FALSE, 0, sizeof(cl_ulong), &zero); + + if(_stddev != nullptr) + { + queue.enqueueWriteBuffer(*_global_sum_squared, CL_FALSE, 0, sizeof(cl_ulong), &zero); + } + + Window slice = window.first_slice_window_2D(); + + do + { + unsigned int idx = 0; + add_2D_tensor_argument(idx, _input, slice); + // Set slice step equal to height to force gws[1] to 1, + // as each thread calculates the sum across all rows and columns equal to the number of elements processed by each work-item + slice.set_dimension_step(Window::DimY, _input->info()->dimension(1)); + enqueue(queue, *this, slice); + } + while(window.slide_window_slice_2D(slice)); + + // Calculate mean and stddev + cl_ulong global_sum = 0; + cl_ulong global_sum_squared = 0; + const float num_pixels = _input->info()->dimension(0) * _input->info()->dimension(1); + + queue.enqueueReadBuffer(*_global_sum, CL_TRUE, 0, sizeof(cl_ulong), static_cast<void *>(&global_sum)); + const float mean = global_sum / num_pixels; + *_mean = mean; + + if(_stddev != nullptr) + { + queue.enqueueReadBuffer(*_global_sum_squared, CL_TRUE, 0, sizeof(cl_ulong), static_cast<void *>(&global_sum_squared)); + *_stddev = std::sqrt((global_sum_squared / num_pixels) - (mean * mean)); + } +} |