/*
 * 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