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/*
* Copyright (c) 2017-2018 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/NEDepthwiseIm2ColKernel.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;
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
{
ARM_COMPUTE_UNUSED(conv_info);
//Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions.
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_asymmetric(input->data_type()) && has_bias);
ARM_COMPUTE_RETURN_ERROR_ON((input->dimension(2) * depth_multiplier) != output->dimension(2));
ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != (kernel_dims.width * kernel_dims.height + ((has_bias) ? 1 : 0)));
return Status{};
}
} // namespace
template <typename T>
void NEDepthwiseIm2ColKernel::run_generic(const Window &window)
{
const int input_w = _input->info()->dimension(0);
const int input_h = _input->info()->dimension(1);
const int input_stride_x = _input->info()->strides_in_bytes().x();
const int input_stride_y = _input->info()->strides_in_bytes().y();
const int input_stride_z = _input->info()->strides_in_bytes().z();
const int stride_x = _conv_info.stride().first;
const int stride_y = _conv_info.stride().second;
const int pad_left = _conv_info.pad_left();
const int pad_right = _conv_info.pad_right();
const int pad_top = _conv_info.pad_top();
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, 0, 0));
window_in.set(Window::DimY, Window::Dimension(0, 0, 0));
window_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
// Setup output window
Window window_out(window);
window_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _output->info()->dimension(0)));
window_out.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 1));
window_out.set(Window::DimZ, Window::Dimension(0, _output->info()->dimension(2), 1));
Iterator in(_input, window_in);
Iterator out(_output, window_out);
const int full_length = input_w + pad_left + pad_right;
const int max_initial_x = stride_x * (((full_length - _kernel_dims.width) / stride_x) + 1);
// Define pad value
auto zero = static_cast<T>(0);
if(std::is_same<T, uint8_t>::value)
{
zero = _input->info()->quantization_info().offset;
}
execute_window_loop(window_out, [&](const Coordinates & id)
{
const int src_pixel_linear = id.y() * stride_x;
const int src_x = -pad_left + src_pixel_linear % max_initial_x;
const int src_y = -pad_top + src_pixel_linear / max_initial_x * stride_y;
// Get pointers
const uint8_t *const input_ptr = in.ptr() + id.z() / _depth_multiplier * input_stride_z;
auto output_ptr = reinterpret_cast<T *>(out.ptr());
const int height = src_y + _kernel_dims.height;
const int width = src_x + _kernel_dims.width;
for(int y = src_y; y < height; ++y)
{
for(int x = src_x; x < width; ++x, ++output_ptr)
{
if(x < 0 || x >= input_w || y < 0 || y >= input_h)
{
*output_ptr = zero;
}
else
{
*output_ptr = *(reinterpret_cast<const T *>(input_ptr + x * input_stride_x + y * input_stride_y));
}
}
}
if(_has_bias)
{
*output_ptr = static_cast<T>(1);
}
},
in, out);
}
NEDepthwiseIm2ColKernel::NEDepthwiseIm2ColKernel()
: _func(nullptr), _input(nullptr), _output(nullptr), _kernel_dims(), _conv_info(), _has_bias(), _depth_multiplier(1)
{
}
void NEDepthwiseIm2ColKernel::configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, depth_multiplier));
_input = input;
_output = output;
_kernel_dims = kernel_dims;
_conv_info = conv_info;
_has_bias = has_bias;
_depth_multiplier = depth_multiplier;
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps());
// Set appropriate function to run
switch(input->info()->data_type())
{
case DataType::QASYMM8:
_func = &NEDepthwiseIm2ColKernel::run_generic<uint8_t>;
break;
case DataType::F16:
_func = &NEDepthwiseIm2ColKernel::run_generic<half>;
break;
case DataType::F32:
_func = &NEDepthwiseIm2ColKernel::run_generic<float>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported data type");
}
// The NEDepthwiseIm2ColKernel 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);
}
Status NEDepthwiseIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, kernel_dims, conv_info, has_bias, depth_multiplier));
return Status{};
}
void NEDepthwiseIm2ColKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
if(_func != nullptr)
{
(this->*_func)(window);
}
}
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