COMPMID-344 Updated doxygen

Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae

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));
+    }
+}