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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/CLDepthwiseConvolutionKernel.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/ICLKernel.h"
#include "arm_compute/core/CL/ICLTensor.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/Utils.h"
using namespace arm_compute;
CLDepthwiseConvolutionKernel::CLDepthwiseConvolutionKernel()
: _border_size(0), _input(), _output(), _weights(), _conv_stride_x(0), _conv_stride_y(0), _conv_pad_x(0), _conv_pad_y(0)
{
}
BorderSize CLDepthwiseConvolutionKernel::border_size() const
{
return _border_size;
}
void CLDepthwiseConvolutionKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *weights, const PadStrideInfo &conv_info)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32);
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::F32);
ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != 3 || weights->info()->dimension(1) != 3);
_input = input;
_output = output;
_weights = weights;
_conv_stride_x = conv_info.stride().first;
_conv_stride_y = conv_info.stride().second;
_border_size = BorderSize(weights->info()->dimension(1) / 2, weights->info()->dimension(0) / 2);
_conv_pad_x = std::min(border_size().right, conv_info.pad().first);
_conv_pad_y = std::min(border_size().bottom, conv_info.pad().second);
// Set build options
std::set<std::string> options;
options.emplace("-DCONV_STRIDE_X=" + support::cpp11::to_string(_conv_stride_x));
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("depthwise_convolution_3x3", options));
// Configure kernel window
const unsigned int num_elems_processed_per_iteration = 2;
const unsigned int num_elems_written_per_iteration = 2;
const unsigned int num_elems_read_per_iteration = (_conv_stride_x == 1) ? 4 : (_conv_stride_x == 2) ? 5 : 6;
const unsigned int num_rows_read_per_iteration = 3;
Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration));
const int access_right = border_size().left + ceil_to_multiple(border_size().left + input->info()->dimension(0), num_elems_read_per_iteration);
const int access_bottom = border_size().bottom + ceil_to_multiple(border_size().bottom + input->info()->dimension(1), num_rows_read_per_iteration);
AccessWindowStatic input_access(input->info(), -border_size().left, -border_size().bottom, access_right, access_bottom);
AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration);
AccessWindowStatic weights_access(weights->info(), 0, 0, weights->info()->dimension(0), weights->info()->dimension(1));
update_window_and_padding(win, input_access, weights_access, output_access);
output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape()));
ICLKernel::configure(win);
}
void CLDepthwiseConvolutionKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
Window slice_in = window.first_slice_window_3D();
Window slice_out = window.first_slice_window_3D();
Window slice_weights = window.first_slice_window_3D();
slice_in.adjust(Window::DimX, -_conv_pad_x, true);
slice_in.adjust(Window::DimY, -_conv_pad_y, true);
slice_in.set_dimension_step(Window::DimX, window.x().step() * _conv_stride_x);
slice_in.set_dimension_step(Window::DimY, window.y().step() * _conv_stride_y);
slice_weights.set_dimension_step(Window::DimX, 0);
slice_weights.set_dimension_step(Window::DimY, 0);
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice_in);
add_3D_tensor_argument(idx, _output, slice_out);
add_3D_tensor_argument(idx, _weights, slice_weights);
enqueue(queue, *this, slice_out);
}
while(window.slide_window_slice_3D(slice_out));
}
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