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/*
* 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
* 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.
*/
#ifndef ARM_COMPUTE_TEST_GATHER_FIXTURE
#define ARM_COMPUTE_TEST_GATHER_FIXTURE
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "tests/AssetsLibrary.h"
#include "tests/Globals.h"
#include "tests/IAccessor.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Fixture.h"
#include "tests/validation/Helpers.h"
#include "tests/validation/reference/Gather.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class GatherFixture : public framework::Fixture
{
public:
template <typename...>
void setup(TensorShape input_shape, TensorShape indices_shape, int axis, DataType data_type)
{
_target = compute_target(input_shape, data_type, axis, indices_shape);
_reference = compute_reference(input_shape, data_type, axis, indices_shape);
}
protected:
template <typename U>
void fill(U &&tensor)
{
library->fill_tensor_uniform(tensor, 0);
}
template <typename U>
void generate_indices(U &&indices, const TensorShape &input_shape, uint32_t actual_axis, TensorShape indices_shape)
{
std::mt19937 gen(library->seed());
uint32_t *indices_ptr = static_cast<uint32_t *>(indices.data());
std::uniform_int_distribution<uint32_t> dist_index(0, input_shape[actual_axis] - 1);
//Let's consider 1D indices
for(unsigned int ind = 0; ind < indices_shape[0]; ind++)
{
indices_ptr[ind] = dist_index(gen);
}
}
TensorType compute_target(const TensorShape &input_shape,
DataType data_type,
int axis,
const TensorShape indices_shape)
{
// Create tensors
TensorType src = create_tensor<TensorType>(input_shape, data_type);
TensorType indices_tensor = create_tensor<TensorType>(indices_shape, DataType::U32);
const uint32_t actual_axis = wrap_around(axis, static_cast<int>(input_shape.num_dimensions()));
TensorShape output_shape = arm_compute::misc::shape_calculator::compute_gather_shape(input_shape, indices_shape, actual_axis);
TensorType dst = create_tensor<TensorType>(output_shape, data_type);
// Create and configure function
FunctionType gather;
gather.configure(&src, &indices_tensor, &dst, axis);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(indices_tensor.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
src.allocator()->allocate();
indices_tensor.allocator()->allocate();
dst.allocator()->allocate();
ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!indices_tensor.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Fill tensors
fill(AccessorType(src));
generate_indices(AccessorType(indices_tensor), input_shape, actual_axis, indices_shape);
// Compute function
gather.run();
return dst;
}
SimpleTensor<T> compute_reference(const TensorShape &input_shape,
DataType data_type,
int axis,
const TensorShape indices_shape)
{
// Create reference tensor
SimpleTensor<T> src{ input_shape, data_type };
SimpleTensor<uint32_t> indices_tensor{ indices_shape, DataType::U32 };
const uint32_t actual_axis = wrap_around(axis, static_cast<int>(input_shape.num_dimensions()));
// Fill reference tensor
fill(src);
generate_indices(indices_tensor, input_shape, actual_axis, indices_shape);
return reference::gather(src, indices_tensor, actual_axis);
}
TensorType _target{};
SimpleTensor<T> _reference{};
};
} // namespace validation
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_GATHER_FIXTURE */
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