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/*
* Copyright (c) 2017-2018 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.
*/
#ifndef ARM_COMPUTE_TEST_CHANNEL_EXTRACT_FIXTURE
#define ARM_COMPUTE_TEST_CHANNEL_EXTRACT_FIXTURE
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.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/ChannelExtract.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename MultiImageType, typename TensorType, typename AccessorType, typename FunctionType, typename T>
class ChannelExtractValidationFixture : public framework::Fixture
{
public:
template <typename...>
void setup(TensorShape shape, Format format, Channel channel)
{
shape = adjust_odd_shape(shape, format);
_target = compute_target(shape, format, channel);
_reference = compute_reference(shape, format, channel);
}
protected:
template <typename U>
void fill(U &&tensor, int i)
{
library->fill_tensor_uniform(tensor, i);
}
std::vector<SimpleTensor<T>> create_tensor_planes_reference(const TensorShape &shape, Format format)
{
TensorShape input = adjust_odd_shape(shape, format);
std::vector<SimpleTensor<T>> tensor_planes;
switch(format)
{
case Format::RGB888:
case Format::RGBA8888:
case Format::YUYV422:
case Format::UYVY422:
{
tensor_planes.emplace_back(input, format);
break;
}
case Format::NV12:
case Format::NV21:
{
const TensorShape shape_uv88 = calculate_subsampled_shape(shape, Format::UV88);
tensor_planes.emplace_back(input, Format::U8);
tensor_planes.emplace_back(shape_uv88, Format::UV88);
break;
}
case Format::IYUV:
{
const TensorShape shape_sub2 = calculate_subsampled_shape(shape, Format::IYUV);
tensor_planes.emplace_back(input, Format::U8);
tensor_planes.emplace_back(shape_sub2, Format::U8);
tensor_planes.emplace_back(shape_sub2, Format::U8);
break;
}
case Format::YUV444:
tensor_planes.emplace_back(input, Format::U8);
tensor_planes.emplace_back(input, Format::U8);
tensor_planes.emplace_back(input, Format::U8);
break;
default:
ARM_COMPUTE_ERROR("Not supported");
break;
}
return tensor_planes;
}
TensorType compute_target(const TensorShape &shape, Format format, Channel channel)
{
const unsigned int num_planes = num_planes_from_format(format);
TensorShape dst_shape = calculate_subsampled_shape(shape, format, channel);
// Create tensors
MultiImageType ref_src = create_multi_image<MultiImageType>(shape, format);
TensorType dst = create_tensor<TensorType>(dst_shape, Format::U8);
// Create and configure function
FunctionType channel_extract;
if(1U == num_planes)
{
const TensorType *plane_src = static_cast<TensorType *>(ref_src.plane(0));
channel_extract.configure(plane_src, channel, &dst);
}
else
{
channel_extract.configure(&ref_src, channel, &dst);
}
for(unsigned int plane_idx = 0; plane_idx < num_planes; ++plane_idx)
{
const TensorType *src_plane = static_cast<const TensorType *>(ref_src.plane(plane_idx));
ARM_COMPUTE_EXPECT(src_plane->info()->is_resizable(), framework::LogLevel::ERRORS);
}
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
ref_src.allocate();
dst.allocator()->allocate();
for(unsigned int plane_idx = 0; plane_idx < num_planes; ++plane_idx)
{
const TensorType *src_plane = static_cast<const TensorType *>(ref_src.plane(plane_idx));
ARM_COMPUTE_EXPECT(!src_plane->info()->is_resizable(), framework::LogLevel::ERRORS);
}
ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Fill tensor planes
for(unsigned int plane_idx = 0; plane_idx < num_planes; ++plane_idx)
{
TensorType *src_plane = static_cast<TensorType *>(ref_src.plane(plane_idx));
fill(AccessorType(*src_plane), plane_idx);
}
// Compute function
channel_extract.run();
return dst;
}
SimpleTensor<T> compute_reference(const TensorShape &shape, Format format, Channel channel)
{
const unsigned int num_planes = num_planes_from_format(format);
// Create reference
std::vector<SimpleTensor<T>> ref_src = create_tensor_planes_reference(shape, format);
// Fill references
for(unsigned int plane_idx = 0; plane_idx < num_planes; ++plane_idx)
{
fill(ref_src[plane_idx], plane_idx);
}
return reference::channel_extract<T>(shape, ref_src, format, channel);
}
TensorType _target{};
SimpleTensor<T> _reference{};
};
} // namespace validation
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_CHANNEL_EXTRACT_FIXTURE */
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