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/*
* Copyright (c) 2018-2020 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/CL/kernels/CLCol2ImKernel.h"
#include "arm_compute/core/Types.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 = CLSynthetizeFunction<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 = 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 = 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 = CLCol2ImKernel::validate(&input, &output, conv_size);
ARM_COMPUTE_EXPECT(bool(status) == false, framework::LogLevel::ERRORS);
}
}
template <typename T>
using CLCol2ImFixture = Col2ImValidationFixture<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
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