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/*
* Copyright (c) 2017-2019 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/NEDequantizationLayerKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/CPP/Validate.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/NEON/NEAsymm.h"
#include "arm_compute/core/NEON/wrapper/wrapper.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include <arm_neon.h>
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8);
if(output->tensor_shape().total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
}
return Status{};
}
std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
{
// Configure kernel window
Window win = calculate_max_window(*input, Steps());
// Output tensor auto initialization if not yet initialized
auto_init_if_empty(*output, input->tensor_shape(), 1, DataType::F32);
// NEDequantizationLayerKernel doesn't need padding so update_window_and_padding() can be skipped
Coordinates coord;
coord.set_num_dimensions(output->num_dimensions());
output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
return std::make_tuple(Status{}, win);
}
template <typename T>
inline void store_result(T *ptr, const float32x4x4_t &v)
{
ARM_COMPUTE_UNUSED(ptr, v);
}
template <>
inline void store_result<float>(float *ptr, const float32x4x4_t &v)
{
wrapper::vstore(ptr, v.val[0]);
wrapper::vstore(ptr + 4, v.val[1]);
wrapper::vstore(ptr + 8, v.val[2]);
wrapper::vstore(ptr + 12, v.val[3]);
}
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
template <>
inline void store_result<float16_t>(float16_t *ptr, const float32x4x4_t &v)
{
wrapper::vstore(ptr, vcombine_f16(vcvt_f16_f32(v.val[0]), vcvt_f16_f32(v.val[1])));
wrapper::vstore(ptr + 8, vcombine_f16(vcvt_f16_f32(v.val[2]), vcvt_f16_f32(v.val[3])));
}
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
template <typename T>
void run_dequantization(const ITensor *input, ITensor *output, const Window &window)
{
const QuantizationInfo &qinfo = input->info()->quantization_info();
const int window_step_x = 16;
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
// Collapse window and reset first dimension to handle tail calculations manually
Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
// Create iterators
Iterator in(input, win_collapsed);
Iterator out(output, win_collapsed);
execute_window_loop(win_collapsed, [&](const Coordinates & id)
{
const auto in_ptr = reinterpret_cast<const uint8_t *>(in.ptr());
const auto out_ptr = reinterpret_cast<T *>(out.ptr());
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
const auto vin = wrapper::vloadq(in_ptr + x);
const auto vdeq = vdequantize(vin, qinfo);
store_result<T>(reinterpret_cast<T *>(out_ptr + x), vdeq);
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
uint8_t val = *(in_ptr + x);
*(out_ptr + x) = static_cast<T>(qinfo.dequantize(val));
}
},
in, out);
}
} // namespace
NEDequantizationLayerKernel::NEDequantizationLayerKernel()
: _input(nullptr), _output(nullptr)
{
}
void NEDequantizationLayerKernel::configure(const ITensor *input, ITensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
_input = input;
_output = output;
// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), output->info());
ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
INEKernel::configure(std::get<1>(win_config));
}
Status NEDequantizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get())));
return Status{};
}
void NEDequantizationLayerKernel::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);
switch(_output->info()->data_type())
{
case DataType::F32:
run_dequantization<float>(_input, _output, window);
break;
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
run_dequantization<float16_t>(_input, _output, window);
break;
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
default:
ARM_COMPUTE_ERROR("Unsupported data type.");
}
}
} // namespace arm_compute
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