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/*
* Copyright (c) 2017-2019 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/Types.h"
#include "arm_compute/runtime/GLES_COMPUTE/GCTensor.h"
#include "arm_compute/runtime/GLES_COMPUTE/GCTensorAllocator.h"
#include "arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h"
#include "tests/GLES_COMPUTE/GCAccessor.h"
#include "tests/PaddingCalculator.h"
#include "tests/datasets/RandomBatchNormalizationLayerDataset.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/Helpers.h"
#include "tests/validation/Validation.h"
#include "tests/validation/fixtures/BatchNormalizationLayerFixture.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace
{
constexpr AbsoluteTolerance<float> tolerance_f(0.00001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
const auto act_infos = framework::dataset::make("ActivationInfo",
{
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
});
const auto data_GB = combine(framework::dataset::make("UseGamma", { false, true }),
framework::dataset::make("UseBeta", { false, true }));
const auto data_f16 = combine(combine(combine(data_GB, act_infos), framework::dataset::make("DataType", DataType::F16)),
framework::dataset::make("DataLayout", { DataLayout::NCHW }));
const auto data_f32 = combine(combine(combine(data_GB, act_infos), framework::dataset::make("DataType", DataType::F32)),
framework::dataset::make("DataLayout", { DataLayout::NCHW }));
} // namespace
TEST_SUITE(GC)
TEST_SUITE(BatchNormalizationLayer)
template <typename T>
using GCBatchNormalizationLayerFixture = BatchNormalizationLayerValidationFixture<GCTensor, GCAccessor, GCBatchNormalizationLayer, T>;
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallRandomBatchNormalizationLayerDataset(),
data_GB),
framework::dataset::make("DataType", { DataType::F32 })),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
shape0, shape1, epsilon, use_beta, use_gamma, dt, data_layout)
{
TensorShape src_dst_shapes = shape0;
if(data_layout == DataLayout::NHWC)
{
permute(src_dst_shapes, PermutationVector(2U, 0U, 1U));
}
// Create tensors
GCTensor src = create_tensor<GCTensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
GCTensor dst = create_tensor<GCTensor>(src_dst_shapes, dt, 1, QuantizationInfo(), data_layout);
GCTensor mean = create_tensor<GCTensor>(shape1, dt, 1);
GCTensor var = create_tensor<GCTensor>(shape1, dt, 1);
GCTensor beta = create_tensor<GCTensor>(shape1, dt, 1);
GCTensor gamma = create_tensor<GCTensor>(shape1, dt, 1);
// Create and Configure function
GCBatchNormalizationLayer norm;
GCTensor *beta_ptr = use_beta ? &beta : nullptr;
GCTensor *gamma_ptr = use_gamma ? &gamma : nullptr;
norm.configure(&src, &dst, &mean, &var, beta_ptr, gamma_ptr, epsilon);
// Validate valid region
const ValidRegion valid_region = shape_to_valid_region(src_dst_shapes);
validate(dst.info()->valid_region(), valid_region);
}
TEST_SUITE(Float)
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallRandomBatchNormalizationLayerDataset(), data_f16))
{
// Validate output
validate(GCAccessor(_target), _reference, tolerance_f16, 0);
}
TEST_SUITE_END()
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::LargeRandomBatchNormalizationLayerDataset(), data_f32))
{
// Validate output
validate(GCAccessor(_target), _reference, tolerance_f, 0);
}
TEST_SUITE_END()
TEST_SUITE_END()
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace validation
} // namespace test
} // namespace arm_compute
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