tests/validation/CL/Col2Im.cpp

/*
 * Copyright (c) 2018-2021 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
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 * furnished to do so, subject to the following conditions:
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 * The above copyright notice and this permission notice shall be included in all
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#include "arm_compute/core/Types.h"
#include "src/gpu/cl/kernels/ClCol2ImKernel.h"
#include "tests/CL/CLAccessor.h"
#include "tests/CL/Helper.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/Col2ImFixture.h"

namespace arm_compute
{
namespace test
{
namespace validation
{
TEST_SUITE(CL)
TEST_SUITE(Col2Im)

using ClCol2Im = ClSynthetizeOperatorWithBorder<opencl::kernels::ClCol2ImKernel>;

/** Negative tests
 *
 * A series of validation tests on configurations which according to the API specification
 * the function should fail against.
 *
 * Checks performed in order:
 *     - Pass unsupported data type for input
 *     - Pass NHWC as output data layout
 *     - Pass an invalid output shape
 */
TEST_CASE(Negative, framework::DatasetMode::ALL)
{
    // Unsupported data type
    {
        const auto input     = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::SIZET);
        const auto output    = TensorInfo(TensorShape(3U, 4U, 10U, 1U, 2U), 1, DataType::F32);
        const auto conv_size = Size2D(3, 4);
        const auto status    = opencl::kernels::ClCol2ImKernel::validate(&input, &output, conv_size);
        ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
    }

    // NHWC as output data layout
    {
        const auto input     = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32);
        const auto output    = TensorInfo(TensorShape(3U, 4U, 10U, 1U, 2U), 1, DataType::F32, DataLayout::NHWC);
        const auto conv_size = Size2D(3, 4);
        const auto status    = opencl::kernels::ClCol2ImKernel::validate(&input, &output, conv_size);
        ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
    }

    // Invalid output size
    {
        const auto input     = TensorInfo(TensorShape(10U, 12U, 1U, 2U), 1, DataType::F32);
        const auto output    = TensorInfo(TensorShape(3U, 4U, 10U, 2U, 2U), 1, DataType::F32);
        const auto conv_size = Size2D(3, 4);
        const auto status    = opencl::kernels::ClCol2ImKernel::validate(&input, &output, conv_size);
        ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
    }
}

template <typename T>
using ClCol2ImFixture = Col2ImOpValidationFixture<CLTensor, CLAccessor, ClCol2Im, T, true>;

/** Test kernel for single-precision floating point
 *
 * @note 8 elements processed per iteration
 *
 * Three main tests will be run:
 *  - Channels are multiple of elements processed
 *  - Channels larger and non multiple of elements used
 *  - Channels smaller and not multiple of elements used
 *
 *  The above will be repeated with a different group size
 *
 *  Kernel tested col2im
 */
FIXTURE_DATA_TEST_CASE(FP32,
                       ClCol2ImFixture<float>,
                       framework::DatasetMode::ALL,
                       combine(combine(combine(combine(
                                                   framework::dataset::make("InputShape", { TensorShape(8U, 16U, 3U, 1U), TensorShape(17U, 16U, 3U, 1U), TensorShape(7U, 16U, 3U, 1U) }),
                                                   framework::dataset::make("ConvolvedWidth", 4)),
                                               framework::dataset::make("ConvolvedHeight", 4)),
                                       framework::dataset::make("Groups", { 1, 3 })),
                               framework::dataset::make("DataType", DataType::F32)))
{
    // Validate output
    validate(CLAccessor(_target), _reference);
}

/** Test kernel for half-precision floating point
 *
 * @note 8 elements processed per iteration
 *
 * One main tests will be run:
 *  - Channels larger and non multiple of elements used
 *
 *  We just need to test the difference in the data type size.
 *  Any other issues can be identified by the main FP32 tests
 *
 *  Kernel tested col2im
 */
FIXTURE_DATA_TEST_CASE(F16,
                       ClCol2ImFixture<half>,
                       framework::DatasetMode::ALL,
                       combine(combine(combine(combine(
                                                   framework::dataset::make("InputShape", TensorShape(17U, 16U, 3U, 1U)),
                                                   framework::dataset::make("ConvolvedWidth", 4)),
                                               framework::dataset::make("ConvolvedHeight", 4)),
                                       framework::dataset::make("Groups", 3)),
                               framework::dataset::make("DataType", DataType::F16)))
{
    // Validate output
    validate(CLAccessor(_target), _reference);
}

/** Test kernel for unsigned asymmetric quantized type
 *
 * @note 8 elements processed per iteration
 *
 * One main tests will be run:
 *  - Channels larger and non multiple of elements used
 *
 *  We just need to test the difference in the data type size.
 *  Any other issues can be identified by the main FP32 tests
 *
 *  Kernel tested col2im
 */
FIXTURE_DATA_TEST_CASE(QASYMM8,
                       ClCol2ImFixture<uint8_t>,
                       framework::DatasetMode::ALL,
                       combine(combine(combine(combine(
                                                   framework::dataset::make("InputShape", TensorShape(17U, 16U, 3U, 1U)),
                                                   framework::dataset::make("ConvolvedWidth", 4)),
                                               framework::dataset::make("ConvolvedHeight", 4)),
                                       framework::dataset::make("Groups", 3)),
                               framework::dataset::make("DataType", DataType::QASYMM8)))
{
    // Validate output
    validate(CLAccessor(_target), _reference);
}

TEST_SUITE_END() // CL
TEST_SUITE_END() // Col2Im
} // namespace validation
} // namespace test
} // namespace arm_compute