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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.
*/
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEDequantizationLayer.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "tests/NEON/Accessor.h"
#include "tests/PaddingCalculator.h"
#include "tests/datasets/ShapeDatasets.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/fixtures/DequantizationLayerFixture.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace
{
/** Tolerance for float operations */
constexpr AbsoluteTolerance<float> tolerance_f32(0.001f);
const auto DequantizationShapes = concat(concat(concat(datasets::Small3DShapes(),
datasets::Large3DShapes()),
datasets::Small4DShapes()),
datasets::Large4DShapes());
} // namespace
TEST_SUITE(NEON)
TEST_SUITE(DequantizationLayer)
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), // Wrong input data type
TensorInfo(TensorShape(16U, 5U, 16U), 1, DataType::U8), // Invalid shape
TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), // Wrong output data type
TensorInfo(TensorShape(16U, 16U, 2U, 5U), 1, DataType::U8), // Missmatching shapes
TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::U8), // Shrink window
TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8), // Valid
}),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
TensorInfo(TensorShape(16U, 5U, 16U), 1, DataType::U8),
TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8),
TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::F32),
TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
})),
framework::dataset::make("MinMax",{ TensorInfo(TensorShape(2U), 1, DataType::F32),
TensorInfo(TensorShape(2U), 1, DataType::U8),
TensorInfo(TensorShape(2U), 1, DataType::F32),
TensorInfo(TensorShape(2U), 1, DataType::F32),
TensorInfo(TensorShape(2U), 1, DataType::U8),
TensorInfo(TensorShape(2U), 1, DataType::U8),
})),
framework::dataset::make("Expected", { false, false, false, false, false, true})),
input_info, output_info, min_max, expected)
{
ARM_COMPUTE_EXPECT(bool(NEDequantizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), &min_max.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS);
}
// clang-format on
// *INDENT-ON*
DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(DequantizationShapes, framework::dataset::make("DataType", DataType::U8)), shape, data_type)
{
TensorShape shape_min_max = shape;
shape_min_max.set(Window::DimX, 2);
// Remove Y and Z dimensions and keep the batches
shape_min_max.remove_dimension(1);
shape_min_max.remove_dimension(1);
// Create tensors
Tensor src = create_tensor<Tensor>(shape, data_type);
Tensor dst = create_tensor<Tensor>(shape, DataType::F32);
Tensor min_max = create_tensor<Tensor>(shape_min_max, DataType::F32);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(min_max.info()->is_resizable(), framework::LogLevel::ERRORS);
// Create and configure function
NEDequantizationLayer dequant_layer;
dequant_layer.configure(&src, &dst, &min_max);
// Validate valid region
const ValidRegion valid_region = shape_to_valid_region(shape);
validate(src.info()->valid_region(), valid_region);
validate(dst.info()->valid_region(), valid_region);
// Validate valid region of min_max tensor
const ValidRegion valid_region_min_max = shape_to_valid_region(shape_min_max);
validate(min_max.info()->valid_region(), valid_region_min_max);
// Validate padding
const PaddingSize padding = PaddingCalculator(shape.x(), 8).required_padding();
validate(src.info()->padding(), padding);
validate(dst.info()->padding(), padding);
// Validate padding of min_max tensor
const PaddingSize padding_min_max = PaddingCalculator(shape_min_max.x(), 2).required_padding();
validate(min_max.info()->padding(), padding_min_max);
}
template <typename T>
using NEDequantizationLayerFixture = DequantizationValidationFixture<Tensor, Accessor, NEDequantizationLayer, T>;
TEST_SUITE(Integer)
TEST_SUITE(U8)
FIXTURE_DATA_TEST_CASE(RunSmall, NEDequantizationLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(concat(datasets::Small3DShapes(), datasets::Small4DShapes()),
framework::dataset::make("DataType", DataType::U8)))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
FIXTURE_DATA_TEST_CASE(RunLarge, NEDequantizationLayerFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(concat(datasets::Large3DShapes(), datasets::Large4DShapes()),
framework::dataset::make("DataType", DataType::U8)))
{
// Validate output
validate(Accessor(_target), _reference, tolerance_f32);
}
TEST_SUITE_END() // U8
TEST_SUITE_END() // Integer
TEST_SUITE_END() // DequantizationLayer
TEST_SUITE_END() // NEON
} // namespace validation
} // namespace test
} // namespace arm_compute
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