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/*
* Copyright (c) 2017-2020 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/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 "arm_compute/runtime/RuntimeContext.h"
#include "tests/CL/CLAccessor.h"
#include "tests/PaddingCalculator.h"
#include "tests/datasets/ActivationFunctionsDataset.h"
#include "tests/datasets/ShapeDatasets.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "tests/validation/Validation.h"
#include "tests/validation/fixtures/ActivationLayerFixture.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace
{
constexpr AbsoluteTolerance<float> tolerance_qsymm16(1.f);
/** Define tolerance of the activation layer.
*
* @param[in] activation The activation function used.
* @param[in] data_type Data type.
*
* @return Tolerance depending on the activation function.
*/
AbsoluteTolerance<float> tolerance(ActivationLayerInfo::ActivationFunction activation, DataType data_type)
{
constexpr float epsilon = 1e-6f;
switch(activation)
{
case ActivationLayerInfo::ActivationFunction::LINEAR:
return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.2f : epsilon);
case ActivationLayerInfo::ActivationFunction::SQUARE:
return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.1f : epsilon);
case ActivationLayerInfo::ActivationFunction::LOGISTIC:
return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.001f : epsilon);
case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.00001f : epsilon);
case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
case ActivationLayerInfo::ActivationFunction::ELU:
case ActivationLayerInfo::ActivationFunction::SQRT:
return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.01f : 0.00001f);
case ActivationLayerInfo::ActivationFunction::TANH:
return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.001f : 0.00001f);
case ActivationLayerInfo::ActivationFunction::HARD_SWISH:
return AbsoluteTolerance<float>(data_type == DataType::F16 ? 0.01f : epsilon);
default:
return AbsoluteTolerance<float>(epsilon);
}
}
/** CNN data types */
const auto CNNDataTypes = framework::dataset::make("DataType",
{
DataType::F16,
DataType::F32
});
/** Input data sets. */
const auto ActivationDataset = combine(combine(framework::dataset::make("InPlace", { false, true }), datasets::ActivationFunctions()), framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
} // namespace
TEST_SUITE(CL)
TEST_SUITE(ActivationLayer)
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), CNNDataTypes), framework::dataset::make("InPlace", { false, true })),
shape, data_type, in_place)
{
// Create context
auto ctx = parameters->get_ctx<CLTensor>();
// Create tensors
CLTensor src = create_tensor<CLTensor>(shape, data_type, 1, QuantizationInfo(), DataLayout::NCHW, ctx);
CLTensor dst = create_tensor<CLTensor>(shape, data_type, 1, QuantizationInfo(), DataLayout::NCHW, ctx);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Create and configure function
CLActivationLayer act_layer(ctx);
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(data_type);
const PaddingSize padding = PaddingCalculator(shape.x(), step).required_padding();
validate(src.info()->padding(), padding);
if(!in_place)
{
validate(dst.info()->padding(), padding);
}
}
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data types
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), // Invalid quantization info
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching shapes
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16), // Invalid activation function for QSYMM16
}),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8),
TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f / 32768.f, 0)),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f / 32768.f, 0)),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QSYMM16, QuantizationInfo(1.f / 32768.f, 0)),
})),
framework::dataset::make("ActivationInfo", { ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::SQRT),
})),
framework::dataset::make("Expected", { false, false, true, true, false, false, true, true, false })),
input_info, output_info, act_info, expected)
{
ARM_COMPUTE_EXPECT(bool(CLActivationLayer::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), act_info)) == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
/** [CLActivationLayerFixture snippet] **/
template <typename T>
using CLActivationLayerFixture = ActivationValidationFixture<CLTensor, CLAccessor, CLActivationLayer, T>;
/** [CLActivationLayerFixture snippet] **/
TEST_SUITE(Float)
TEST_SUITE(FP16)
/** [CLActivationLayer Test snippet] **/
FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), ActivationDataset),
framework::dataset::make("DataType",
DataType::F16)))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
}
/** [CLActivationLayer Test snippet] **/
TEST_SUITE_END() // FP16
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(datasets::SmallShapes(), ActivationDataset), framework::dataset::make("DataType",
DataType::F32)))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
}
TEST_SUITE_END() // FP32
TEST_SUITE_END() // Float
template <typename T>
using CLActivationLayerQuantizedFixture = ActivationValidationQuantizedFixture<CLTensor, CLAccessor, CLActivationLayer, T>;
const auto QuantizedActivationDataset8 = combine(combine(framework::dataset::make("InPlace", { false }),
concat(datasets::ActivationFunctionsQuantized(), framework::dataset::make("ActivationFunction", ActivationLayerInfo::ActivationFunction::HARD_SWISH))),
framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
const auto QuantizedActivationDataset16 = combine(combine(framework::dataset::make("InPlace", { false }),
datasets::ActivationFunctionsQuantized()),
framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallShapes(), QuantizedActivationDataset8),
framework::dataset::make("DataType",
DataType::QASYMM8)),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 128.0f) })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
}
TEST_SUITE_END() // QASYMM8
TEST_SUITE(QASYMM8_SIGNED)
FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallShapes(), QuantizedActivationDataset8),
framework::dataset::make("DataType",
DataType::QASYMM8_SIGNED)),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.1f, 10.0f) })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
}
TEST_SUITE_END() // QASYMM8_SIGNED
TEST_SUITE(QSYMM16)
FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerQuantizedFixture<int16_t>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallShapes(), QuantizedActivationDataset16),
framework::dataset::make("DataType",
DataType::QSYMM16)),
framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 32768.f, 0) })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_qsymm16);
}
TEST_SUITE_END() // QSYMM16
TEST_SUITE_END() // Quantized
TEST_SUITE_END() // ActivationLayer
TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
} // namespace arm_compute
|
