COMPMID-344 Updated doxygen
Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae
diff --git a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
new file mode 100644
index 0000000..ecee1ab
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+++ b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
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+/*
+ * 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/CLGEMMTranspose1xWKernel.h"
+
+#include "arm_compute/core/AccessWindowTranspose.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/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include <cmath>
+
+using namespace arm_compute;
+
+void CLGEMMTranspose1xWKernel::configure(const ICLTensor *input, ICLTensor *output)
+{
+ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::F16, DataType::F32);
+ ARM_COMPUTE_ERROR_ON(output == nullptr);
+
+ TensorShape output_shape{ input->info()->tensor_shape() };
+ const size_t transpose_w = 16 / input->info()->element_size();
+ output_shape.set(0, input->info()->dimension(1) * transpose_w);
+ output_shape.set(1, static_cast<size_t>(std::ceil((input->info()->dimension(0) / static_cast<float>(transpose_w)))));
+
+ // Output tensor auto inizialitation if not yet initialized
+ auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position());
+
+ ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape);
+
+ _input = input;
+ _output = output;
+ const unsigned int num_elems_processed_per_iteration = max_cl_vector_width / data_size_from_type(input->info()->data_type());
+
+ /*
+ * Following an example of how the transposition1xW works when the input data type is F32
+ *
+ * |a00 a01 a02 a03|
+ * |a10 a11 a12 a13|
+ * |a20 a21 a22 a23| = | a00 a01 a02 a03 || a10 a11 a12 a13 || a20 a21 a22 a23 || a30 a31 a32 a33 |
+ * |a30 a31 a32 a33|
+ *
+ * If the input data type is F32, the output matrix will have the following shape: [ height * 4, width / 4 ]
+ * If the input data type is F16, the output matrix will have the following shape: [ height * 8, width / 8 ]
+ */
+ // Create kernel
+ std::string data_type_name = lower_string(string_from_data_type(input->info()->data_type()));
+ std::string kernel_name = "gemm_transpose1x" + val_to_string(num_elems_processed_per_iteration) + "_" + data_type_name;
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+
+ // Configure window
+ Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration));
+
+ float scale_x = 1.f;
+
+ switch(input->info()->data_type())
+ {
+ case DataType::U8:
+ scale_x = 16.f;
+ break;
+ case DataType::F16:
+ scale_x = 8.f;
+ break;
+ case DataType::F32:
+ scale_x = 4.f;
+ break;
+ default:
+ // Do nothing
+ break;
+ }
+
+ AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
+ AccessWindowTranspose output_access(output->info(), 0, 0, num_elems_processed_per_iteration, 1, scale_x, 1.f / scale_x);
+
+ update_window_and_padding(win, input_access, output_access);
+
+ output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->info()->tensor_shape()));
+
+ ICLKernel::configure(win);
+}
+
+void CLGEMMTranspose1xWKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ // Output is transposed
+ Window out_window(window);
+ out_window.set(Window::DimX, window.y());
+ out_window.set(Window::DimY, window.x());
+
+ Window in_slice = window.first_slice_window_2D();
+ Window out_slice = out_window.first_slice_window_2D();
+
+ do
+ {
+ unsigned int idx = 0;
+ add_2D_tensor_argument(idx, _input, in_slice);
+ add_2D_tensor_argument(idx, _output, out_slice);
+ enqueue(queue, *this, in_slice, _lws_hint);
+ }
+ while(window.slide_window_slice_2D(in_slice) && out_window.slide_window_slice_2D(out_slice));
+}