127 lines
5.4 KiB
C++
127 lines
5.4 KiB
C++
/*
|
|
* Copyright (c) 2018 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/Types.h"
|
|
#include "arm_compute/runtime/CL/CLTensor.h"
|
|
#include "arm_compute/runtime/CL/CLTensorAllocator.h"
|
|
#include "arm_compute/runtime/CL/functions/CLUnstack.h"
|
|
|
|
#include "tests/CL/CLAccessor.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/UnstackFixture.h"
|
|
|
|
namespace arm_compute
|
|
{
|
|
namespace test
|
|
{
|
|
namespace validation
|
|
{
|
|
namespace
|
|
{
|
|
const auto unstack_axis_dataset = framework::dataset::make("Axis", -3, 3);
|
|
const auto unstack_num_dataset = framework::dataset::make("Num", 1, 3); // The length of the dimension axis
|
|
const auto unstack_dataset_small = datasets::Small3DShapes() * unstack_axis_dataset * unstack_num_dataset;
|
|
} //namespace
|
|
|
|
TEST_SUITE(CL)
|
|
TEST_SUITE(Unstack)
|
|
|
|
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
|
|
framework::dataset::make("InputInfo",
|
|
{
|
|
TensorInfo(TensorShape(1U, 9U, 8U), 1, DataType::U8), // Passes, 1 slice on x axis
|
|
TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::U8), // fails because axis > input's rank
|
|
TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::S32), // fails axis < (- input's rank)
|
|
TensorInfo(TensorShape(3U, 7U, 5U), 1, DataType::S32), // passes, 3 slices along X
|
|
TensorInfo(TensorShape(13U, 7U, 5U), 1, DataType::S16), // fails, too few output slices
|
|
TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::U8), // fails mismatching data types
|
|
}),
|
|
framework::dataset::make("OutputInfo",
|
|
{
|
|
std::vector<TensorInfo>{ TensorInfo(TensorShape(9U, 8U), 1, DataType::U8) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(2U, 3U), 1, DataType::U8) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(2U, 3U), 1, DataType::S32) },
|
|
|
|
std::vector<TensorInfo>{ TensorInfo(TensorShape(7U, 5U), 1, DataType::S32), TensorInfo(TensorShape(7U, 5U), 1, DataType::S32), TensorInfo(TensorShape(7U, 5U), 1, DataType::S32) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(7U, 5U), 1, DataType::S16) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(9U, 8U), 1, DataType::S32) },
|
|
})),
|
|
framework::dataset::make("Axis", { -3, 3, -4, -3, 1, 1 })),
|
|
framework::dataset::make("Num", { 1, 1, 1, 1, 0, 1 })),
|
|
framework::dataset::make("Expected", { true, false, false, true, false, false })),
|
|
input_info, output_info, axis, num, expected)
|
|
{
|
|
std::vector<TensorInfo> ti(output_info);
|
|
std::vector<ITensorInfo *> vec(num);
|
|
for(size_t j = 0; j < vec.size(); ++j)
|
|
{
|
|
vec[j] = &ti[j];
|
|
}
|
|
ARM_COMPUTE_EXPECT(bool(CLUnstack::validate(&input_info.clone()->set_is_resizable(false), vec, axis)) == expected, framework::LogLevel::ERRORS);
|
|
}
|
|
|
|
template <typename T>
|
|
using CLUnstackFixture = UnstackValidationFixture<CLTensor, ICLTensor, CLAccessor, CLUnstack, T>;
|
|
|
|
TEST_SUITE(F32)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLUnstackFixture<float>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::F32 }))
|
|
{
|
|
ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size());
|
|
// Validate output
|
|
for(size_t k = 0; k < _target.size(); ++k)
|
|
{
|
|
validate(CLAccessor(_target[k]), _reference[k]);
|
|
}
|
|
}
|
|
TEST_SUITE_END() // F32
|
|
|
|
TEST_SUITE(F16)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLUnstackFixture<half>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::F16 }))
|
|
{
|
|
ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size());
|
|
// Validate output
|
|
for(size_t k = 0; k < _target.size(); ++k)
|
|
{
|
|
validate(CLAccessor(_target[k]), _reference[k]);
|
|
}
|
|
}
|
|
TEST_SUITE_END() // F16
|
|
|
|
TEST_SUITE(Quantized)
|
|
FIXTURE_DATA_TEST_CASE(RunSmall, CLUnstackFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::QASYMM8 }))
|
|
{
|
|
ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size());
|
|
// Validate output
|
|
for(size_t k = 0; k < _target.size(); ++k)
|
|
{
|
|
validate(CLAccessor(_target[k]), _reference[k]);
|
|
}
|
|
}
|
|
TEST_SUITE_END() // QASYMM8
|
|
|
|
TEST_SUITE_END() // Unstack
|
|
TEST_SUITE_END() // CL
|
|
} // namespace validation
|
|
} // namespace test
|
|
} // namespace arm_compute
|