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/*
* Copyright (c) 2019-2020 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/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "tests/AssetsLibrary.h"
#include "tests/Globals.h"
#include "tests/SimpleTensor.h"
#include "tests/SimpleTensorAccessor.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/reference/ConvolutionLayer.h"
#include "tests/validation/reference/DFT.h"
#include <random>
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace
{
auto shapes_1d_dft = framework::dataset::make("TensorShape", { TensorShape(33U),
TensorShape(8U),
TensorShape(23U, 7U),
TensorShape(16U, 8U, 4U)
});
auto shapes_2d_dft = framework::dataset::make("TensorShape", { TensorShape(33U, 14U),
TensorShape(8U, 9U),
TensorShape(23U, 7U, 3U),
TensorShape(16U, 8U, 4U)
});
auto conv_dataset_dft = framework::dataset::zip(framework::dataset::zip(framework::dataset::make("InputShape", { TensorShape(8U, 7U, 3U, 2U),
TensorShape(18U, 22U, 4U),
TensorShape(32U, 48U, 8U)
}),
framework::dataset::make("WeightShape", { TensorShape(3U, 3U, 3U, 6U),
TensorShape(5U, 5U, 4U, 3U),
TensorShape(9U, 9U, 8U, 3U)
})),
framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 1, 1),
PadStrideInfo(1, 1, 2, 2),
PadStrideInfo(1, 1, 4, 4)
}));
} // namespace
TEST_SUITE(CPP)
TEST_SUITE(DFT)
TEST_SUITE(DFT1D)
DATA_TEST_CASE(Real, framework::DatasetMode::ALL, shapes_1d_dft,
shape)
{
SimpleTensor<float> src{ shape, DataType::F32, 1 };
std::uniform_real_distribution<float> distribution(-5.f, 5.f);
library->fill(src, distribution, 0);
const bool is_odd = shape.x() % 2;
// Forward pass
auto forward = reference::rdft_1d(src);
// Backward pass
auto backward = reference::ridft_1d(forward, is_odd);
// Validate with input
validate(SimpleTensorAccessor<float>(src), backward, RelativeTolerance<float>(0.1f));
}
DATA_TEST_CASE(Complex, framework::DatasetMode::ALL, shapes_1d_dft,
shape)
{
SimpleTensor<float> src{ shape, DataType::F32, 2 };
std::uniform_real_distribution<float> distribution(-5.f, 5.f);
library->fill(src, distribution, 0);
// Forward pass
auto forward = reference::dft_1d(src, reference::FFTDirection::Forward);
// Backward pass
auto backward = reference::dft_1d(forward, reference::FFTDirection::Inverse);
// Validate with input
validate(SimpleTensorAccessor<float>(src), backward, RelativeTolerance<float>(0.1f));
}
TEST_SUITE_END() // DFT1D
TEST_SUITE(DFT2D)
DATA_TEST_CASE(Real, framework::DatasetMode::ALL, shapes_2d_dft,
shape)
{
SimpleTensor<float> src{ shape, DataType::F32, 1 };
std::uniform_real_distribution<float> distribution(-5.f, 5.f);
library->fill(src, distribution, 0);
const bool is_odd = shape.x() % 2;
// Forward pass
auto forward = reference::rdft_2d(src);
// Backward pass
auto backward = reference::ridft_2d(forward, is_odd);
// Validate with input
validate(SimpleTensorAccessor<float>(src), backward, RelativeTolerance<float>(0.1f));
}
DATA_TEST_CASE(Complex, framework::DatasetMode::ALL, shapes_2d_dft,
shape)
{
SimpleTensor<float> src{ shape, DataType::F32, 2 };
std::uniform_real_distribution<float> distribution(-5.f, 5.f);
library->fill(src, distribution, 0);
// Forward pass
auto forward = reference::dft_2d(src, reference::FFTDirection::Forward);
// Backward pass
auto backward = reference::dft_2d(forward, reference::FFTDirection::Inverse);
// Validate with input
validate(SimpleTensorAccessor<float>(src), backward, RelativeTolerance<float>(0.1f), 0.f, AbsoluteTolerance<float>(0.001f));
}
TEST_SUITE_END() // DFT2D
TEST_SUITE(Conv)
DATA_TEST_CASE(Real2Real, framework::DatasetMode::ALL, conv_dataset_dft,
shape_in, shape_w, conv_info)
{
std::uniform_real_distribution<float> distribution(-1.f, 1.f);
std::uniform_real_distribution<float> distribution_b(0.f, 0.f);
SimpleTensor<float> src{ shape_in, DataType::F32, 1 };
SimpleTensor<float> w{ shape_w, DataType::F32, 1 };
SimpleTensor<float> b{ TensorShape(shape_w[3]), DataType::F32, 1 };
library->fill(src, distribution, 0);
library->fill(w, distribution, 1);
library->fill(b, distribution_b, 2);
const auto output_wh = arm_compute::scaled_dimensions(shape_in.x(), shape_in.y(), shape_w.x(), shape_w.y(), conv_info);
TensorShape dst_shape = shape_in;
dst_shape.set(0, output_wh.first);
dst_shape.set(1, output_wh.second);
dst_shape.set(2, shape_w[3]);
// FFT based convolution
auto dst = reference::conv2d_dft(src, w, conv_info);
// Reference convolution
auto dst_ref = reference::convolution_layer(src, w, b, dst_shape, conv_info);
// Validate with input
validate(SimpleTensorAccessor<float>(dst), dst_ref, RelativeTolerance<float>(0.1f), 0.f, AbsoluteTolerance<float>(0.001f));
}
TEST_SUITE_END() // Conv
TEST_SUITE_END() // DFT
TEST_SUITE_END() // CPP
} // namespace validation
} // namespace test
} // namespace arm_compute
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