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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/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h"
#include "arm_compute/core/AccessWindowTranspose.h"
#include "arm_compute/core/Coordinates.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensor.h"
#include "arm_compute/core/NEON/INEKernel.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
using namespace arm_compute;
NEDepthwiseWeightsReshapeKernel::NEDepthwiseWeightsReshapeKernel()
: _input(nullptr), _output(nullptr), _biases(nullptr)
{
}
void NEDepthwiseWeightsReshapeKernel::configure(const ITensor *input, ITensor *output, const ITensor *biases)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != output->info()->dimension(1));
ARM_COMPUTE_ERROR_ON(output->info()->dimension(0) != (input->info()->dimension(0) * input->info()->dimension(1) + ((biases != nullptr) ? 1 : 0)));
if(biases != nullptr)
{
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases);
ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, biases);
ARM_COMPUTE_ERROR_ON(biases->info()->dimension(0) != input->info()->dimension(2));
ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() > 1);
}
_input = input;
_output = output;
_biases = biases;
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps());
// The NEDepthwiseWeightsReshapeKernel doesn't need padding so update_window_and_padding() can be skipped
output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
INEKernel::configure(win);
}
void NEDepthwiseWeightsReshapeKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
const int input_w = _input->info()->dimension(0);
const int output_stride_x = _output->info()->strides_in_bytes().x();
const int output_stride_y = _output->info()->strides_in_bytes().y();
Window window_in(window);
// The first three dimensions of the input are increased by the inner loops
window_in.set(Window::DimX, Window::Dimension(0, _input->info()->dimension(0), _input->info()->dimension(0)));
window_in.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(1), 1));
window_in.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(2), 1));
// Setup output window
Window window_out;
window_out.set(Window::DimX, Window::Dimension(0, 0, 0));
window_out.set(Window::DimY, Window::Dimension(0, 0, 0));
Iterator in(_input, window_in);
Iterator out(_output, window_out);
execute_window_loop(window_in, [&](const Coordinates & id)
{
auto input_ptr = reinterpret_cast<float *>(in.ptr());
auto output_ptr = reinterpret_cast<float *>(out.ptr() + id.y() * input_w * output_stride_x + id.z() * output_stride_y);
for(int i = 0; i < input_w; ++i, ++input_ptr)
{
*(output_ptr + i) = *input_ptr;
}
if(_biases != nullptr)
{
*(output_ptr + input_w) = *(reinterpret_cast<float *>(_biases->ptr_to_element(Coordinates(id.z()))));
}
},
in, out);
}
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