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/*
* 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 "AssetsLibrary.h"
#include "CL/CLAccessor.h"
#include "Globals.h"
#include "PaddingCalculator.h"
#include "TypePrinter.h"
#include "Utils.h"
#include "validation/Datasets.h"
#include "validation/Helpers.h"
#include "validation/Reference.h"
#include "validation/Validation.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/CLTensorAllocator.h"
#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
#include "boost_wrapper.h"
#include <random>
#include <string>
#include <tuple>
using namespace arm_compute;
using namespace arm_compute::test;
using namespace arm_compute::test::validation;
namespace
{
/** Define tolerance of the activation layer
*
* @param[in] activation The activation function used.
* @param[in] fixed_point_position Number of bits for the fractional part..
*
* @return Tolerance depending on the activation function.
*/
float activation_layer_tolerance(ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 0)
{
switch(activation)
{
case ActivationLayerInfo::ActivationFunction::LOGISTIC:
case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
case ActivationLayerInfo::ActivationFunction::SQRT:
case ActivationLayerInfo::ActivationFunction::TANH:
return (fixed_point_position != 0) ? 5.f : 0.00001f;
break;
default:
return 0.f;
}
}
/** Compute CL activation layer function.
*
* @param[in] in_place Compute the activation layer in-place.
* @param[in] shape Shape of the input and output tensors.
* @param[in] dt Shape Data type of tensors.
* @param[in] act_info Activation layer information.
* @param[in] fixed_point_position (Optional) Number of bits for the fractional part of fixed point numbers.
*
* @return Computed output tensor.
*/
CLTensor compute_activation_layer(bool in_place, const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0)
{
// Create tensors
CLTensor src = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position);
CLTensor dst = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position);
// Create and configure function
CLActivationLayer act_layer;
if(in_place)
{
act_layer.configure(&src, nullptr, act_info);
}
else
{
act_layer.configure(&src, &dst, act_info);
}
// Allocate tensors
src.allocator()->allocate();
BOOST_TEST(!src.info()->is_resizable());
if(!in_place)
{
dst.allocator()->allocate();
BOOST_TEST(!dst.info()->is_resizable());
}
// Fill tensors
if(dt == DataType::F32)
{
float min_bound = 0;
float max_bound = 0;
std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<float>(act_info.activation());
std::uniform_real_distribution<> distribution(min_bound, max_bound);
library->fill(CLAccessor(src), distribution, 0);
}
else
{
int min_bound = 0;
int max_bound = 0;
if(dt == DataType::QS8)
{
std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position);
}
else
{
std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position);
}
std::uniform_int_distribution<> distribution(min_bound, max_bound);
library->fill(CLAccessor(src), distribution, 0);
}
// Compute function
act_layer.run();
if(in_place)
{
return src;
}
else
{
return dst;
}
}
} // namespace
#ifndef DOXYGEN_SKIP_THIS
BOOST_AUTO_TEST_SUITE(CL)
BOOST_AUTO_TEST_SUITE(ActivationLayer)
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true }) * (SmallShapes() + LargeShapes()) * CNNDataTypes(), in_place, shape, dt)
{
// Set fixed point position data type allowed
const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0;
// Create tensors
CLTensor src = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position);
CLTensor dst = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position);
BOOST_TEST(src.info()->is_resizable());
BOOST_TEST(dst.info()->is_resizable());
// Create and configure function
CLActivationLayer act_layer;
if(in_place)
{
act_layer.configure(&src, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
}
else
{
act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
}
// Validate valid region
const ValidRegion valid_region = shape_to_valid_region(shape);
validate(src.info()->valid_region(), valid_region);
if(!in_place)
{
validate(dst.info()->valid_region(), valid_region);
}
// Validate padding
const int step = 16 / arm_compute::data_size_from_type(dt);
const PaddingSize padding = PaddingCalculator(shape.x(), step).required_padding();
validate(src.info()->padding(), padding);
if(!in_place)
{
validate(dst.info()->padding(), padding);
}
}
BOOST_AUTO_TEST_SUITE(Float)
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }),
in_place, shape, dt, act_function, alpha_beta)
{
// Create activation layer info
ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
// Compute function
CLTensor dst = compute_activation_layer(in_place, shape, dt, act_info);
// Compute reference
RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info);
// Validate output
validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function));
}
BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * LargeShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }),
in_place, shape, dt, act_function, alpha_beta)
{
// Create activation layer info
ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
// Compute function
CLTensor dst = compute_activation_layer(in_place, shape, dt, act_info);
// Compute reference
RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info);
// Validate output
validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function));
}
BOOST_AUTO_TEST_SUITE_END()
/** @note We test for fixed point precision [3,5] because [1,2] and [6,7] ranges
* cause overflowing issues in most of the transcendentals functions.
*/
BOOST_AUTO_TEST_SUITE(Quantized)
BOOST_AUTO_TEST_SUITE(QS8)
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 6, 1) * boost::unit_test::data::make({ 0.5f, 1.f }),
in_place, shape, act_function, fixed_point_position, alpha_beta)
{
// Create activation layer info
ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
// Compute function
CLTensor dst = compute_activation_layer(in_place, shape, DataType::QS8, act_info, fixed_point_position);
// Compute reference
RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS8, act_info, fixed_point_position);
// Validate output
validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position));
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE(QS16)
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 14, 1) * boost::unit_test::data::make({ 0.5f, 1.f }),
in_place, shape, act_function, fixed_point_position, alpha_beta)
{
// Create activation layer info
ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
// Compute function
CLTensor dst = compute_activation_layer(in_place, shape, DataType::QS16, act_info, fixed_point_position);
// Compute reference
RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS16, act_info, fixed_point_position);
// Validate output
validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position));
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
#endif /* DOXYGEN_SKIP_THIS */