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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_DEQUANTIZATION_LAYER_FIXTURE
#define ARM_COMPUTE_TEST_DEQUANTIZATION_LAYER_FIXTURE
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/Tensor.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/DequantizationLayer.h"
#include <random>
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class DequantizationValidationFixture : public framework::Fixture
{
public:
template <typename...>
void setup(TensorShape shape, DataType src_data_type, DataType dst_datatype, DataLayout data_layout)
{
_quantization_info = generate_quantization_info(src_data_type, shape.z());
_target = compute_target(shape, src_data_type, dst_datatype, data_layout);
_reference = compute_reference(shape, src_data_type);
}
protected:
template <typename U>
void fill(U &&tensor)
{
library->fill_tensor_uniform(tensor, 0);
}
TensorType compute_target(TensorShape shape, DataType src_data_type, DataType dst_datatype, DataLayout data_layout)
{
if(data_layout == DataLayout::NHWC)
{
permute(shape, PermutationVector(2U, 0U, 1U));
}
// Create tensors
TensorType src = create_tensor<TensorType>(shape, src_data_type, 1, _quantization_info, data_layout);
TensorType dst = create_tensor<TensorType>(shape, dst_datatype, 1, QuantizationInfo(), data_layout);
// Create and configure function
FunctionType dequantization_layer;
dequantization_layer.configure(&src, &dst);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
src.allocator()->allocate();
dst.allocator()->allocate();
ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
// Fill tensors
fill(AccessorType(src));
// Compute function
dequantization_layer.run();
return dst;
}
SimpleTensor<T> compute_reference(const TensorShape &shape, DataType src_data_type)
{
switch(src_data_type)
{
case DataType::QASYMM8:
{
SimpleTensor<uint8_t> src{ shape, src_data_type, 1, _quantization_info };
fill(src);
return reference::dequantization_layer<T>(src);
}
case DataType::QASYMM8_SIGNED:
case DataType::QSYMM8_PER_CHANNEL:
case DataType::QSYMM8:
{
SimpleTensor<int8_t> src{ shape, src_data_type, 1, _quantization_info };
fill(src);
return reference::dequantization_layer<T>(src);
}
case DataType::QSYMM16:
{
SimpleTensor<int16_t> src{ shape, src_data_type, 1, _quantization_info };
fill(src);
return reference::dequantization_layer<T>(src);
}
default:
ARM_COMPUTE_ERROR("Unsupported data type");
}
}
protected:
QuantizationInfo generate_quantization_info(DataType data_type, int32_t num_channels)
{
std::mt19937 gen(library.get()->seed());
std::uniform_int_distribution<> distribution_scale_q8(1, 255);
std::uniform_int_distribution<> distribution_offset_q8(1, 127);
std::uniform_int_distribution<> distribution_scale_q16(1, 32768);
switch(data_type)
{
case DataType::QSYMM16:
return QuantizationInfo(1.f / distribution_scale_q16(gen));
case DataType::QSYMM8:
return QuantizationInfo(1.f / distribution_scale_q8(gen));
case DataType::QSYMM8_PER_CHANNEL:
{
std::vector<float> scale(num_channels);
for(int32_t i = 0; i < num_channels; ++i)
{
scale[i] = 1.f / distribution_offset_q8(gen);
}
return QuantizationInfo(scale);
}
case DataType::QASYMM8:
return QuantizationInfo(1.f / distribution_scale_q8(gen), distribution_offset_q8(gen));
case DataType::QASYMM8_SIGNED:
return QuantizationInfo(1.f / distribution_scale_q8(gen), -distribution_offset_q8(gen));
default:
ARM_COMPUTE_ERROR("Unsupported data type");
}
}
protected:
TensorType _target{};
SimpleTensor<T> _reference{};
QuantizationInfo _quantization_info{};
};
} // namespace validation
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_DEQUANTIZATION_LAYER_FIXTURE */
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