tests/validation/NEON/ElementwiseMax.cpp

/*
 * Copyright (c) 2018 ARM Limited.
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#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEElementwiseOperations.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "tests/NEON/Accessor.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/ElementwiseOperationsFixture.h"

namespace arm_compute
{
namespace test
{
namespace validation
{
namespace
{
RelativeTolerance<float> tolerance_fp32(0.000001f);
/** Input data sets **/
const auto ElementwiseMaxQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)),
                                                  framework::dataset::make("DataType",
                                                                           DataType::QASYMM8));
/** Input data sets **/
const auto ElementwiseMaxS32Dataset = combine(combine(framework::dataset::make("DataType", DataType::S32), framework::dataset::make("DataType", DataType::S32)), framework::dataset::make("DataType",
                                              DataType::S32));
const auto ElementwiseMaxS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::S16 }), framework::dataset::make("DataType", DataType::S16)),
                                              framework::dataset::make("DataType", DataType::S16));
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
const auto ElementwiseMaxFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)),
                                               framework::dataset::make("DataType", DataType::F16));
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
const auto ElementwiseMaxFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)),
                                               framework::dataset::make("DataType", DataType::F32));
} // namespace

TEST_SUITE(NEON)
TEST_SUITE(ElementwiseMax)

template <typename T>
using NEElementwiseMaxFixture = ElementwiseMaxValidationFixture<Tensor, Accessor, NEElementwiseMax, T>;

// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
               framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),      // Invalid data type combination
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),     // Mismatching shapes
                                                      }),
               framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32),
                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16),
                                                       TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
                                                     })),
               framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
                                                       TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32),
                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32),
                                                       TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32),
                                                     })),
               framework::dataset::make("Expected", { true, true, true, false, false})),
               input1_info, input2_info, output_info, expected)
{
    ARM_COMPUTE_EXPECT(bool(NEElementwiseMax::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*

TEST_SUITE(S32)
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()),
               shape)
{
    // Create tensors
    Tensor ref_src1 = create_tensor<Tensor>(shape, DataType::S32);
    Tensor ref_src2 = create_tensor<Tensor>(shape, DataType::S32);
    Tensor dst      = create_tensor<Tensor>(shape, DataType::S32);

    // Create and Configure function
    NEElementwiseMax add;
    add.configure(&ref_src1, &ref_src2, &dst);

    // Validate valid region
    const ValidRegion valid_region = shape_to_valid_region(shape);
    validate(dst.info()->valid_region(), valid_region);
}

FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture<int32_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxS32Dataset))
{
    // Validate output
    validate(Accessor(_target), _reference);
}
TEST_SUITE_END() // S32

TEST_SUITE(S16)
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::S16 })),
               shape, data_type)
{
    // Create tensors
    Tensor ref_src1 = create_tensor<Tensor>(shape, data_type);
    Tensor ref_src2 = create_tensor<Tensor>(shape, DataType::S16);
    Tensor dst      = create_tensor<Tensor>(shape, DataType::S16);

    // Create and Configure function
    NEElementwiseMax add;
    add.configure(&ref_src1, &ref_src2, &dst);

    // Validate valid region
    const ValidRegion valid_region = shape_to_valid_region(shape);
    validate(dst.info()->valid_region(), valid_region);
}

FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxS16Dataset))
{
    // Validate output
    validate(Accessor(_target), _reference);
}

FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseMaxFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMaxS16Dataset))
{
    // Validate output
    validate(Accessor(_target), _reference);
}
TEST_SUITE_END() // S16

template <typename T>
using NEElementwiseMaxQuantizedFixture = ElementwiseMaxValidationQuantizedFixture<Tensor, Accessor, NEElementwiseMax, T>;

TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()),
               shape)
{
    // Create tensors
    Tensor ref_src1 = create_tensor<Tensor>(shape, DataType::QASYMM8);
    Tensor ref_src2 = create_tensor<Tensor>(shape, DataType::QASYMM8);
    Tensor dst      = create_tensor<Tensor>(shape, DataType::QASYMM8);

    // Create and Configure function
    NEElementwiseMin add;
    add.configure(&ref_src1, &ref_src2, &dst);

    // Validate valid region
    const ValidRegion valid_region = shape_to_valid_region(shape);
    validate(dst.info()->valid_region(), valid_region);
}

FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(),
                                                                                                                       ElementwiseMaxQASYMM8Dataset),
                                                                                                                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })),
                                                                                                                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
                                                                                                                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) })))
{
    // Validate output
    validate(Accessor(_target), _reference, tolerance_fp32, 0.01);
}

template <typename T>
using NEElementwiseMaxQuantizedBroadcastFixture = ElementwiseMaxQuantizedBroadcastValidationFixture<Tensor, Accessor, NEElementwiseMax, T>;

FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseMaxQuantizedBroadcastFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapesBroadcast(),
                       ElementwiseMaxQASYMM8Dataset),
                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })),
                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })),
                       framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) })))
{
    // Validate output
    validate(Accessor(_target), _reference);
}
TEST_SUITE_END()
TEST_SUITE_END()

TEST_SUITE(Float)
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(F16)
FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture<half>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseMaxFP16Dataset))
{
    // Validate output
    validate(Accessor(_target), _reference);
}
TEST_SUITE_END() // F16
#endif           /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */

TEST_SUITE(F32)
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()),
               shape)
{
    // Create tensors
    Tensor ref_src1 = create_tensor<Tensor>(shape, DataType::F32);
    Tensor ref_src2 = create_tensor<Tensor>(shape, DataType::F32);
    Tensor dst      = create_tensor<Tensor>(shape, DataType::F32);

    // Create and Configure function
    NEElementwiseMax add;
    add.configure(&ref_src1, &ref_src2, &dst);

    // Validate valid region
    const ValidRegion valid_region = shape_to_valid_region(shape);
    validate(dst.info()->valid_region(), valid_region);
}

FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxFP32Dataset))
{
    // Validate output
    validate(Accessor(_target), _reference);
}

FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseMaxFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMaxFP32Dataset))
{
    // Validate output
    validate(Accessor(_target), _reference);
}

template <typename T>
using NEElementwiseMaxBroadcastFixture = ElementwiseMaxBroadcastValidationFixture<Tensor, Accessor, NEElementwiseMax, T>;

FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseMaxBroadcastFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(),
                       ElementwiseMaxFP32Dataset))
{
    // Validate output
    validate(Accessor(_target), _reference);
}

FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, NEElementwiseMaxBroadcastFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(),
                       ElementwiseMaxFP32Dataset))
{
    // Validate output
    validate(Accessor(_target), _reference);
}
TEST_SUITE_END() // F32
TEST_SUITE_END() // Float

TEST_SUITE_END() // ElementwiseMax
TEST_SUITE_END() // NEON
} // namespace validation
} // namespace test
} // namespace arm_compute