/*
 * Copyright (c) 2018-2021, 2023 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
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 * SOFTWARE.
 */
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEElementwiseUnaryLayer.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/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/ElementwiseUnaryFixture.h"

namespace arm_compute
{
namespace test
{
namespace validation
{
namespace
{
RelativeTolerance<float> tolerance_fp32(0.000001f);
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
RelativeTolerance<float> tolerance_fp16(0.01f);
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
#if defined(__aarch64__)
constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(0);
constexpr AbsoluteTolerance<int8_t>  tolerance_qasymm8_signed(0);
#else  // #if !defined(__aarch64__)
constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); // There is difference of 1, because quantizing in reference uses round policy "TO_NEAREST_UP", where the armv7a neon kernel uses "TO_ZERO"
constexpr AbsoluteTolerance<int8_t>  tolerance_qasymm8_signed(1);
#endif // #if !defined(__aarch64__)
} // namespace
TEST_SUITE(NEON)
TEST_SUITE(RsqrtLayer)

// Test test cases will execute the function with dynamic-stated shapes
// Since other elementwise unary operations share the same kernel, this tests are added only here.
// Also, only FP32 is tested since data type doesn't/shouldn't matter with dynamic shapes.
TEST_SUITE(DynamicShape)
TEST_SUITE(FP32)

template <typename T>
using CpuRsqrtDynamicShapeFixture = RsqrtDynamicShapeValidationFixture<Tensor, Accessor, NERsqrtLayer, T>;

FIXTURE_DATA_TEST_CASE(RunSmall, CpuRsqrtDynamicShapeFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
                                                                                                          DataType::F32)))
{
    // Validate output
    validate(Accessor(_target), _reference, tolerance_fp32);
}

TEST_SUITE_END() // FP32
TEST_SUITE_END() // DynamicShape

template <typename T>
using NERsqrtLayerFixture = RsqrtValidationFixture<Tensor, Accessor, NERsqrtLayer, T>;

template <typename T>
using NERsqrtLayerQuantizedFixture = RsqrtQuantizedValidationFixture<Tensor, Accessor, NERsqrtLayer, T>;

TEST_SUITE(Float)
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, NERsqrtLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
                                                                                                       DataType::F16)))
{
    // Validate output
    validate(Accessor(_target), _reference, tolerance_fp16);
}
FIXTURE_DATA_TEST_CASE(RunLarge, NERsqrtLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), framework::dataset::make("DataType",
                                                                                                     DataType::F16)))
{
    // Validate output
    validate(Accessor(_target), _reference, tolerance_fp16);
}

TEST_SUITE_END() // FP16
#endif           // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC

TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, NERsqrtLayerFixture<float>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), framework::dataset::make("DataType",
                                                                                                  DataType::F32)))
{
    // Validate output
    validate(Accessor(_target), _reference, tolerance_fp32);
}

TEST_SUITE_END() // FP32
TEST_SUITE_END() // Float

TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
FIXTURE_DATA_TEST_CASE(RunSmall, NERsqrtLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(
                       datasets::SmallShapes(),
                       framework::dataset::make("DataType", DataType::QASYMM8)),
                       framework::dataset::make("InputQInfo", { QuantizationInfo(20, 0) })),
                       framework::dataset::make("OutputQInfo", { QuantizationInfo(0.5, 10) })))
{
    // Validate output
    validate(Accessor(_target), _reference, tolerance_qasymm8);
}
TEST_SUITE_END() // QASYMM8

TEST_SUITE(QASYMM8_SIGNED)
FIXTURE_DATA_TEST_CASE(RunSmall, NERsqrtLayerQuantizedFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(
                       datasets::SmallShapes(),
                       framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
                       framework::dataset::make("InputQInfo", { QuantizationInfo(25, -128) })),
                       framework::dataset::make("OutputQInfo", { QuantizationInfo(0.1, -7) })))
{
    // Validate output
    validate(Accessor(_target), _reference, tolerance_qasymm8_signed);
}
TEST_SUITE_END() // QASYMM8_SIGNED
TEST_SUITE_END() // Quantized

TEST_SUITE_END() // RsqrtLayer
TEST_SUITE_END() // Neon
} // namespace validation
} // namespace test
} // namespace arm_compute