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/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/*
* 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/NEMuliplyScaleFactorKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include "src/core/CPP/Validate.h"
#include "src/core/NEON/INEKernel.h"
#include "src/core/NEON/NEAsymm.h"
#include "src/core/NEON/wrapper/wrapper.h"
#include "src/core/helpers/WindowHelpers.h"
#include <arm_neon.h>
using namespace arm_compute;
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *scale_factor,
const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 2);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32);
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(output);
ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape().total_size() == 0);
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);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(scale_factor, 1, DataType::F16,
DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON(scale_factor->tensor_shape().total_size() == 0);
ARM_COMPUTE_RETURN_ERROR_ON(scale_factor->num_dimensions() > 1);
ARM_COMPUTE_RETURN_ERROR_ON(scale_factor->dimension(0) != input->dimension(1));
// Checks performed when output is configured
if ((output->total_size() != 0))
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
}
return Status{};
}
inline int32x4x4_t load_value(const int32_t *input_ptr)
{
return {wrapper::vloadq(input_ptr), wrapper::vloadq(input_ptr + 4),
wrapper::vloadq(input_ptr + 8), wrapper::vloadq(input_ptr + 12)};
}
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
inline const float32x4x4_t load_value(const float16_t *input_ptr)
{
return {vcvt_f32_f16(wrapper::vload(input_ptr)), vcvt_f32_f16(wrapper::vload(input_ptr + 4)),
vcvt_f32_f16(wrapper::vload(input_ptr + 8)),
vcvt_f32_f16(wrapper::vload(input_ptr + 12))};
}
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
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 */
inline float32x4x4_t multiply_scale_vec(const int32x4x4_t &iv, float scale)
{
const float32x4_t vscale = vdupq_n_f32(scale);
const float32x4x4_t ret = {{
vmulq_f32(vcvtq_f32_s32(iv.val[0]), vscale),
vmulq_f32(vcvtq_f32_s32(iv.val[1]), vscale),
vmulq_f32(vcvtq_f32_s32(iv.val[2]), vscale),
vmulq_f32(vcvtq_f32_s32(iv.val[3]), vscale),
}};
return ret;
}
} // namespace
NEMultiplyScaleFactorKernel::NEMultiplyScaleFactorKernel()
: _input(nullptr), _scale_factor(nullptr), _output(nullptr), _multiplier(1.f)
{
}
void NEMultiplyScaleFactorKernel::configure(const ITensor *input, const ITensor *scale_factor,
ITensor *output, float multiplier)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(
validate_arguments(input->info(), scale_factor->info(), output->info()));
_input = input;
_scale_factor = scale_factor;
_output = output;
_multiplier = multiplier;
// Configure kernel window
Window win_config = calculate_max_window(*input->info(), Steps());
Coordinates coord;
coord.set_num_dimensions(output->info()->num_dimensions());
output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
INEKernel::configure(win_config);
}
Status NEMultiplyScaleFactorKernel::validate(const ITensorInfo *input,
const ITensorInfo *scale_factor,
const ITensorInfo *output, float multiplier)
{
ARM_COMPUTE_UNUSED(multiplier);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, scale_factor, output));
return Status{};
}
template <typename T> void NEMultiplyScaleFactorKernel::multiply(const Window &window)
{
constexpr auto window_step = 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
// Support Only 2D input
Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
Iterator input(_input, win_collapsed);
Iterator output(_output, win_collapsed);
win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
execute_window_loop(
win_collapsed,
[&](const Coordinates &id) {
auto scale = *reinterpret_cast<T *>(_scale_factor->ptr_to_element({id.y()}));
scale *= _multiplier;
const auto input_ptr = reinterpret_cast<const int32_t *>(input.ptr());
auto output_ptr = reinterpret_cast<T *>(output.ptr());
int x = window_start_x;
for (; x <= (window_end_x - window_step); x += window_step)
{
store_result<float>(&output_ptr[x], multiply_scale_vec(load_value(&input_ptr[x]), scale));
}
// Compute left-over elements
for (; x < window_end_x; ++x)
{
output_ptr[x] = input_ptr[x] * scale;
}
},
input, output);
}
void NEMultiplyScaleFactorKernel::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:
NEMultiplyScaleFactorKernel::multiply<float>(window);
break;
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
NEMultiplyScaleFactorKernel::multiply<float16_t>(window);
break;
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
default:
ARM_COMPUTE_ERROR("Unsupported data type.");
}
}
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