blob: 921582a41d3ef89755a3aba478e2f5f26d279100 [file] [log] [blame]
/*
* 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/NEDepthwiseVectorToTensorKernel.h"
#include "arm_compute/core/CPP/Validate.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"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
using namespace arm_compute;
using namespace arm_compute::misc::shape_calculator;
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, size_t conv_w, size_t conv_h)
{
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::S32, DataType::F16, DataType::F32);
if(output->total_size() != 0)
{
TensorShape output_shape = compute_vector_to_tensor_output_shape(input->tensor_shape(), conv_w, conv_h, output->data_layout());
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
return Status{};
}
} // namespace
template <typename T>
void NEDepthwiseVectorToTensorKernel::vector_to_tensor(const Window &window)
{
// 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();
const int output_stride_z = _output->info()->strides_in_bytes().z();
// Setup output window
Window window_out(window);
window_out.set(Window::DimX, Window::Dimension(0, 0, 0));
window_out.set(Window::DimY, Window::Dimension(0, 0, 0));
window_out.set(Window::DimZ, Window::Dimension(0, 0, 0));
Iterator in(_input, window);
Iterator out(_output, window_out);
const int patch_size = _conv_dims.first * _conv_dims.second;
execute_window_loop(window, [&](const Coordinates & id)
{
const int z = id.x() / patch_size;
const int index2D = id.x() - z * patch_size;
auto input_ptr = reinterpret_cast<T *>(in.ptr());
auto output_ptr = reinterpret_cast<T *>(out.ptr() + index2D % _conv_dims.first * output_stride_x + index2D / _conv_dims.first * output_stride_y + z * output_stride_z);
*output_ptr = *input_ptr;
},
in, out);
}
NEDepthwiseVectorToTensorKernel::NEDepthwiseVectorToTensorKernel()
: _func(nullptr), _input(nullptr), _output(nullptr), _conv_dims()
{
}
void NEDepthwiseVectorToTensorKernel::configure(const ITensor *input, ITensor *output, size_t conv_w, size_t conv_h)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Output auto inizialitation if not yet initialized
TensorShape output_shape = compute_vector_to_tensor_output_shape(input->info()->tensor_shape(), conv_w, conv_h, output->info()->data_layout());
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), conv_w, conv_h));
_input = input;
_output = output;
_conv_dims = std::pair<size_t, size_t>(conv_w, conv_h);
// Set appropriate function to run
switch(input->info()->data_type())
{
case DataType::QASYMM8:
_func = &NEDepthwiseVectorToTensorKernel::vector_to_tensor<uint8_t>;
break;
case DataType::S32:
_func = &NEDepthwiseVectorToTensorKernel::vector_to_tensor<int32_t>;
break;
case DataType::F16:
_func = &NEDepthwiseVectorToTensorKernel::vector_to_tensor<half>;
break;
case DataType::F32:
_func = &NEDepthwiseVectorToTensorKernel::vector_to_tensor<float>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported data type");
}
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps());
// The NEDepthwisevectorToTensorKernel 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 NEDepthwiseVectorToTensorKernel::validate(const ITensorInfo *input, const ITensorInfo *output, size_t conv_w, size_t conv_h)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, conv_w, conv_h));
return Status{};
}
void NEDepthwiseVectorToTensorKernel::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);
}
}