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/*
* Copyright (c) 2017-2021 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/NEON/functions/NENormalizationLayer.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "tests/NEON/Accessor.h"
#include "tests/PaddingCalculator.h"
#include "tests/datasets/NormalizationTypesDataset.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/NormalizationLayerFixture.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace
{
/** Tolerance for float operations */
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
constexpr AbsoluteTolerance<float> tolerance_f16(0.1f);
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f);
/** Input data set. */
const auto NormalizationDataset = combine(combine(combine(combine(datasets::SmallShapes(), datasets::NormalizationTypes()), framework::dataset::make("NormalizationSize", 3, 9, 2)),
framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
framework::dataset::make("IsScaled", { true }));
const auto NormalizationDatasetFP32 = combine(combine(combine(datasets::NormalizationTypes(), framework::dataset::make("NormalizationSize", 3, 9, 2)),
framework::dataset::make("Beta", { 0.5f, 1.f, 2.f })),
framework::dataset::make("IsScaled", { true, false }));
} // namespace
TEST_SUITE(NEON)
TEST_SUITE(NormalizationLayer)
// *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 type input/output
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching shapes
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Even normalization
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Non implemented IN_MAP_2D
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
}),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(27U, 11U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
})),
framework::dataset::make("NormInfo", { NormalizationLayerInfo(NormType::IN_MAP_1D, 5),
NormalizationLayerInfo(NormType::IN_MAP_1D, 5),
NormalizationLayerInfo(NormType::IN_MAP_1D, 4),
NormalizationLayerInfo(NormType::IN_MAP_2D, 5),
NormalizationLayerInfo(NormType::CROSS_MAP, 1),
})),
framework::dataset::make("Expected", { false, false, false, true, true })),
input_info, output_info, norm_info, expected)
{
bool is_valid = bool(NENormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), norm_info));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
template <typename T>
using NENormalizationLayerFixture = NormalizationValidationFixture<Tensor, Accessor, NENormalizationLayer, T>;
TEST_SUITE(Float)
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, NENormalizationLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(NormalizationDataset,
framework::dataset::make("DataType", DataType::F16)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f16);
}
TEST_SUITE_END() // FP16
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, NENormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), NormalizationDatasetFP32),
framework::dataset::make("DataType", DataType::F32)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunLarge, NENormalizationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), NormalizationDatasetFP32),
framework::dataset::make("DataType", DataType::F32)),
framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
TEST_SUITE_END() // FP32
TEST_SUITE_END() // Float
TEST_SUITE_END() // NormalizationLayer
TEST_SUITE_END() // Neon
} // namespace validation
} // namespace test
} // namespace arm_compute