blob: 2243e6ff592e8d927e5063f183f8a6130e661610 [file] [log] [blame]
/*
* Copyright (c) 2017 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 "ActivationLayer.h"
#include "arm_compute/core/Types.h"
#include "tests/validation/FixedPoint.h"
#include "tests/validation/Helpers.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info)
{
// Create reference
SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
// Compute reference
const T a(info.a());
const T b(info.b());
for(int i = 0; i < src.num_elements(); ++i)
{
T x = src[i];
switch(info.activation())
{
case ActivationLayerInfo::ActivationFunction::ABS:
dst[i] = std::abs(x);
break;
case ActivationLayerInfo::ActivationFunction::LINEAR:
dst[i] = a * x + b;
break;
case ActivationLayerInfo::ActivationFunction::LOGISTIC:
dst[i] = static_cast<T>(1) / (static_cast<T>(1) + std::exp(-x));
break;
case ActivationLayerInfo::ActivationFunction::RELU:
dst[i] = std::max<T>(static_cast<T>(0), x);
break;
case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
dst[i] = std::min<T>(a, std::max(static_cast<T>(0), x));
break;
case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
dst[i] = std::min<T>(a, std::max<T>(b, x));
break;
case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
dst[i] = (x > 0) ? x : a * x;
break;
case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
dst[i] = std::log(static_cast<T>(1) + std::exp(x));
break;
case ActivationLayerInfo::ActivationFunction::SQRT:
dst[i] = std::sqrt(x);
break;
case ActivationLayerInfo::ActivationFunction::SQUARE:
dst[i] = x * x;
break;
case ActivationLayerInfo::ActivationFunction::TANH:
dst[i] = a * std::tanh(b * x);
break;
default:
ARM_COMPUTE_ERROR("Unsupported activation function");
}
}
return dst;
}
template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type>
SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info)
{
using namespace fixed_point_arithmetic;
// Create reference
SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
// Compute reference
const int fixed_point_position = src.fixed_point_position();
const fixed_point<T> a(info.a(), fixed_point_position);
const fixed_point<T> b(info.b(), fixed_point_position);
const fixed_point<T> const_0(0, fixed_point_position);
const fixed_point<T> const_1(1, fixed_point_position);
for(int i = 0; i < src.num_elements(); ++i)
{
fixed_point<T> x(src[i], fixed_point_position, true);
switch(info.activation())
{
case ActivationLayerInfo::ActivationFunction::ABS:
dst[i] = abs(x).raw();
break;
case ActivationLayerInfo::ActivationFunction::LINEAR:
dst[i] = add(b, mul(a, x)).raw();
break;
case ActivationLayerInfo::ActivationFunction::LOGISTIC:
dst[i] = (const_1 / (const_1 + exp(-x))).raw();
break;
case ActivationLayerInfo::ActivationFunction::RELU:
dst[i] = max(const_0, x).raw();
break;
case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
dst[i] = min(a, max(const_0, x)).raw();
break;
case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
dst[i] = min(a, max(b, x)).raw();
break;
case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
dst[i] = (x > const_0) ? x.raw() : mul(a, x).raw();
break;
case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
dst[i] = log(const_1 + exp(x)).raw();
break;
case ActivationLayerInfo::ActivationFunction::SQRT:
dst[i] = (const_1 / inv_sqrt(x)).raw();
break;
case ActivationLayerInfo::ActivationFunction::SQUARE:
dst[i] = mul(x, x).raw();
break;
case ActivationLayerInfo::ActivationFunction::TANH:
dst[i] = mul(a, tanh(mul(b, x))).raw();
break;
default:
ARM_COMPUTE_ERROR("Unsupported activation function");
}
}
return dst;
}
template SimpleTensor<float> activation_layer(const SimpleTensor<float> &src, ActivationLayerInfo info);
template SimpleTensor<half> activation_layer(const SimpleTensor<half> &src, ActivationLayerInfo info);
template SimpleTensor<qint8_t> activation_layer(const SimpleTensor<qint8_t> &src, ActivationLayerInfo info);
template SimpleTensor<qint16_t> activation_layer(const SimpleTensor<qint16_t> &src, ActivationLayerInfo info);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute