COMPMID-344 Updated doxygen

Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae

1 files changed, 92 insertions, 0 deletions

diff --git a/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp
new file mode 100644
index 0000000000..289873c23f
--- /dev/null
+++ b/src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp
@@ -0,0 +1,92 @@
+/*
+ * Copyright (c) 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/CLGEMMMatrixAccumulateBiasesKernel.h"
+
+#include "arm_compute/core/AccessWindowStatic.h"
+#include "arm_compute/core/CL/CLHelpers.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/Types.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+
+using namespace arm_compute;
+
+CLGEMMMatrixAccumulateBiasesKernel::CLGEMMMatrixAccumulateBiasesKernel()
+    : _accum(nullptr), _biases(nullptr)
+{
+}
+
+void CLGEMMMatrixAccumulateBiasesKernel::configure(ICLTensor *accum, const ICLTensor *biases)
+{
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::F16, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::F16, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(biases, accum);
+    ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() != 1);
+
+    _biases = biases;
+    _accum  = accum;
+
+    // Create kernel
+    std::string data_type_name = lower_string(string_from_data_type(accum->info()->data_type()));
+    _kernel                    = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_accumulate_biases_" + data_type_name));
+
+    // Configure kernel window
+    const unsigned int num_elems_processed_per_iteration = max_cl_vector_width / data_size_from_type(accum->info()->data_type());
+
+    Window win = calculate_max_window(*_accum->info(), Steps(num_elems_processed_per_iteration));
+
+    AccessWindowStatic     biases_access(biases->info(), 0, 0, biases->info()->dimension(0), biases->info()->dimension(1));
+    AccessWindowHorizontal accum_access(_accum->info(), 0, num_elems_processed_per_iteration);
+
+    update_window_and_padding(win, biases_access, accum_access);
+
+    ICLKernel::configure(win);
+}
+
+void CLGEMMMatrixAccumulateBiasesKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window);
+
+    Window accum_slice = window.first_slice_window_2D();
+
+    Window biases_slice(accum_slice);
+    biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1));
+
+    // Run kernel
+    do
+    {
+        // Set arguments
+        unsigned int idx = 0;
+        add_2D_tensor_argument(idx, _accum, accum_slice);
+        add_1D_tensor_argument(idx, _biases, biases_slice);
+
+        enqueue(queue, *this, accum_slice);
+    }
+    while(window.slide_window_slice_2D(accum_slice));
+}