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/*
* Copyright (c) 2017-2019 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_NORMALIZE_PLANAR_YUV_LAYER_FIXTURE
#define ARM_COMPUTE_TEST_NORMALIZE_PLANAR_YUV_LAYER_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/NormalizePlanarYUVLayer.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class NormalizePlanarYUVLayerValidationGenericFixture : public framework::Fixture
{
public:
template <typename...>
void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout, QuantizationInfo quantization_info)
{
_data_type = dt;
_target = compute_target(shape0, shape1, dt, data_layout, quantization_info);
_reference = compute_reference(shape0, shape1, dt, quantization_info);
}
protected:
template <typename U>
void fill(U &&src_tensor, U &&mean_tensor, U &&std_tensor)
{
if(is_data_type_float(_data_type))
{
const float min_bound = -1.f;
const float max_bound = 1.f;
std::uniform_real_distribution<> distribution(min_bound, max_bound);
std::uniform_real_distribution<> distribution_std(0.1, max_bound);
library->fill(src_tensor, distribution, 0);
library->fill(mean_tensor, distribution, 1);
library->fill(std_tensor, distribution_std, 2);
}
else if(is_data_type_quantized_asymmetric(_data_type))
{
const QuantizationInfo quant_info = src_tensor.quantization_info();
std::pair<int, int> bounds = get_quantized_bounds(quant_info, -1.f, 1.0f);
std::uniform_int_distribution<> distribution(bounds.first, bounds.second);
std::uniform_int_distribution<> distribution_std(quantize_qasymm8(0.1f, quant_info.uniform()), bounds.second);
library->fill(src_tensor, distribution, 0);
library->fill(mean_tensor, distribution, 1);
library->fill(std_tensor, distribution_std, 2);
}
}
TensorType compute_target(TensorShape shape0, const TensorShape &shape1, DataType dt, DataLayout data_layout, QuantizationInfo quantization_info)
{
if(data_layout == DataLayout::NHWC)
{
permute(shape0, PermutationVector(2U, 0U, 1U));
}
// Create tensors
TensorType src = create_tensor<TensorType>(shape0, dt, 1, quantization_info, data_layout);
TensorType mean = create_tensor<TensorType>(shape1, dt, 1, quantization_info);
TensorType std = create_tensor<TensorType>(shape1, dt, 1, quantization_info);
TensorType dst;
// Create and configure function
FunctionType norm;
norm.configure(&src, &dst, &mean, &std);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(mean.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(std.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
src.allocator()->allocate();
dst.allocator()->allocate();
mean.allocator()->allocate();
std.allocator()->allocate();
ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!mean.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!std.info()->is_resizable(), framework::LogLevel::ERRORS);
// Fill tensors
fill(AccessorType(src), AccessorType(mean), AccessorType(std));
// Compute function
norm.run();
return dst;
}
SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, DataType dt, QuantizationInfo quantization_info)
{
// Create reference
SimpleTensor<T> ref_src{ shape0, dt, 1, quantization_info };
SimpleTensor<T> ref_mean{ shape1, dt, 1, quantization_info };
SimpleTensor<T> ref_std{ shape1, dt, 1, quantization_info };
// Fill reference
fill(ref_src, ref_mean, ref_std);
return reference::normalize_planar_yuv_layer(ref_src, ref_mean, ref_std);
}
TensorType _target{};
SimpleTensor<T> _reference{};
DataType _data_type{};
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class NormalizePlanarYUVLayerValidationFixture : public NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
template <typename...>
void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout)
{
NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, dt, data_layout, QuantizationInfo());
}
};
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class NormalizePlanarYUVLayerValidationQuantizedFixture : public NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
{
public:
template <typename...>
void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout, QuantizationInfo quantization_info)
{
NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, dt, data_layout, quantization_info);
}
};
} // namespace validation
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_NORMALIZE_PLANAR_YUV_LAYER_FIXTURE */
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