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/*
* Copyright (c) 2016-2019 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/NEGEMMMatrixAdditionKernel.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/NEFixedPoint.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include <arm_neon.h>
namespace arm_compute
{
namespace
{
constexpr unsigned int num_elems_processed_per_iteration = 16;
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, float beta)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_UNUSED(beta);
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
if(output->total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
}
return Status{};
}
void matrix_addition_f32(const ITensor *input, ITensor *output, const Window &window, float beta)
{
const float32x4_t beta_f32 = vdupq_n_f32(beta);
Iterator in(input, window);
Iterator out(output, window);
execute_window_loop(window, [&](const Coordinates &)
{
const auto in_ptr = reinterpret_cast<const float *>(in.ptr());
const auto out_ptr = reinterpret_cast<float *>(out.ptr());
float32x4x4_t alpha_ab = vld4q_f32(out_ptr);
const float32x4x4_t c = vld4q_f32(in_ptr);
// Multiply matrix C by its weight and accumulate
alpha_ab.val[0] = vmlaq_f32(alpha_ab.val[0], c.val[0], beta_f32);
alpha_ab.val[1] = vmlaq_f32(alpha_ab.val[1], c.val[1], beta_f32);
alpha_ab.val[2] = vmlaq_f32(alpha_ab.val[2], c.val[2], beta_f32);
alpha_ab.val[3] = vmlaq_f32(alpha_ab.val[3], c.val[3], beta_f32);
vst4q_f32(out_ptr, alpha_ab);
},
in, out);
}
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
void matrix_addition_f16(const ITensor *input, ITensor *output, const Window &window, float beta)
{
const float16x8_t beta_f16 = vdupq_n_f16(beta);
Iterator in(input, window);
Iterator out(output, window);
execute_window_loop(window, [&](const Coordinates &)
{
const auto in_ptr = reinterpret_cast<const float16_t *>(in.ptr());
const auto out_ptr = reinterpret_cast<float16_t *>(out.ptr());
float16x8x2_t alpha_ab = vld2q_f16(out_ptr);
const float16x8x2_t c = vld2q_f16(in_ptr);
// Multiply matrix C by its weight and accumulate
alpha_ab.val[0] = vaddq_f16(alpha_ab.val[0], vmulq_f16(c.val[0], beta_f16));
alpha_ab.val[1] = vaddq_f16(alpha_ab.val[1], vmulq_f16(c.val[1], beta_f16));
vst2q_f16(out_ptr + 0, alpha_ab);
},
in, out);
}
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
} // namespace
NEGEMMMatrixAdditionKernel::NEGEMMMatrixAdditionKernel()
: INESimpleKernel(), _func(nullptr), _beta(0.0f)
{
}
void NEGEMMMatrixAdditionKernel::configure(const ITensor *input, ITensor *output, float beta)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), beta));
switch(input->info()->data_type())
{
case DataType::F32:
_func = &matrix_addition_f32;
break;
case DataType::F16:
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
_func = &matrix_addition_f16;
break;
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
default:
ARM_COMPUTE_ERROR("Data type not supported");
break;
}
// Configure kernel window
INESimpleKernel::configure(input, output, num_elems_processed_per_iteration);
_beta = beta;
}
Status NEGEMMMatrixAdditionKernel::validate(const ITensorInfo *input, const ITensorInfo *output, float beta)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, beta));
ARM_COMPUTE_RETURN_ON_ERROR(INESimpleKernel::validate(input->clone().get(), output->clone().get(), num_elems_processed_per_iteration));
return Status{};
}
void NEGEMMMatrixAdditionKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INESimpleKernel::window(), window);
if(_beta != 0.0f)
{
(*_func)(_input, _output, window, _beta);
}
}
} // namespace arm_compute
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