tests/validation/NEON/ArgMinMax.cpp

/*
 * Copyright (c) 2018-2019 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
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 * SOFTWARE.
 */
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEArgMinMaxLayer.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/datasets/SplitDataset.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Macros.h"
#include "tests/validation/Validation.h"
#include "tests/validation/fixtures/ArgMinMaxFixture.h"

namespace arm_compute
{
namespace test
{
namespace validation
{
TEST_SUITE(NEON)
TEST_SUITE(ArgMinMax)

// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
        framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 3U, 16U, 2U), 1, DataType::F32), // Invalid axis
                                                TensorInfo(TensorShape(27U, 3U, 16U, 2U), 1, DataType::F32), // Invalid output shape
                                                TensorInfo(TensorShape(32U, 16U, 16U, 2U), 1, DataType::F32),
                                                TensorInfo(TensorShape(32U, 16U, 16U, 2U), 1, DataType::F32) // Invalid operation
        }),
        framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(27U, 3U, 1U, 2U), 1, DataType::F32),
                                                 TensorInfo(TensorShape(27U, 3U, 1U, 2U), 1, DataType::F32),
                                                 TensorInfo(TensorShape(32U, 16U, 1U, 2U), 1, DataType::U32),
                                                 TensorInfo(TensorShape(32U, 16U, 1U, 2U), 1, DataType::F32)
        })),
        framework::dataset::make("Axis", { 4, 0, 2, 0 })),
        framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MAX, ReductionOperation::ARG_IDX_MAX, ReductionOperation::ARG_IDX_MAX, ReductionOperation::MEAN_SUM })),
        framework::dataset::make("Expected", { false, false, true, false })),
        input_info, output_info, axis, operation, expected)
{
    const Status status = NEArgMinMaxLayer::validate(&input_info.clone()->set_is_resizable(false), axis, &output_info.clone()->set_is_resizable(false), operation);
    ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*

DATA_TEST_CASE(Configuration,
               framework::DatasetMode::ALL,
               combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
               shape, data_type)
{
    // Create tensors
    Tensor ref_src = create_tensor<Tensor>(shape, data_type);
    Tensor dst;

    // Create and Configure function
    NEArgMinMaxLayer arg_min_max_layer;
    arg_min_max_layer.configure(&ref_src, 1, &dst, ReductionOperation::ARG_IDX_MAX);

    // Validate valid region
    TensorShape output_shape = shape;
    output_shape.set(1, 1);
    const ValidRegion valid_region = shape_to_valid_region(output_shape);
    validate(dst.info()->valid_region(), valid_region);
}

template <typename T>
using NEArgMinMaxValidationFixture = ArgMinMaxValidationFixture<Tensor, Accessor, NEArgMinMaxLayer, T>;

TEST_SUITE(Float)
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall,
                       NEArgMinMaxValidationFixture<half>,
                       framework::DatasetMode::PRECOMMIT,
                       combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX })))
{
    // Validate output
    validate(Accessor(_target), _reference);
}

FIXTURE_DATA_TEST_CASE(RunLarge,
                       NEArgMinMaxValidationFixture<half>,
                       framework::DatasetMode::NIGHTLY,
                       combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX })))
{
    // Validate output
    validate(Accessor(_target), _reference);
}
TEST_SUITE_END() // FP16
#endif           // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC

template <typename T>
using NEArgMinMaxQuantizedValidationFixture = ArgMinMaxValidationQuantizedFixture<Tensor, Accessor, NEArgMinMaxLayer, T>;

TEST_SUITE(QASYMM8)
FIXTURE_DATA_TEST_CASE(RunSmall,
                       NEArgMinMaxQuantizedValidationFixture<uint8_t>,
                       framework::DatasetMode::PRECOMMIT,
                       combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("Axis", { 0, 1, 2, 3 })),
                                       framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX })),
                               framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })))
{
    // Validate output
    validate(Accessor(_target), _reference);
}

FIXTURE_DATA_TEST_CASE(RunLarge,
                       NEArgMinMaxQuantizedValidationFixture<uint8_t>,
                       framework::DatasetMode::NIGHTLY,
                       combine(combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("Axis", { 0, 1, 2, 3 })),
                                       framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX })),
                               framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })))
{
    // Validate output
    validate(Accessor(_target), _reference);
}
TEST_SUITE_END() // QASYMM8

TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall,
                       NEArgMinMaxValidationFixture<float>,
                       framework::DatasetMode::PRECOMMIT,
                       combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX })))
{
    // Validate output
    validate(Accessor(_target), _reference);
}

FIXTURE_DATA_TEST_CASE(RunLarge,
                       NEArgMinMaxValidationFixture<float>,
                       framework::DatasetMode::NIGHTLY,
                       combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX })))
{
    // Validate output
    validate(Accessor(_target), _reference);
}
TEST_SUITE_END() // FP32
TEST_SUITE_END() // Float
TEST_SUITE_END() // ArgMinMax
TEST_SUITE_END() // NEON
} // namespace validation
} // namespace test
} // namespace arm_compute