156 lines
9.4 KiB
C++
156 lines
9.4 KiB
C++
/*
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* Copyright (c) 2017-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "arm_compute/core/Types.h"
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#include "arm_compute/runtime/NEON/functions/NEDequantizationLayer.h"
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#include "arm_compute/runtime/Tensor.h"
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#include "arm_compute/runtime/TensorAllocator.h"
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#include "tests/NEON/Accessor.h"
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#include "tests/PaddingCalculator.h"
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#include "tests/datasets/DatatypeDataset.h"
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#include "tests/datasets/ShapeDatasets.h"
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#include "tests/framework/Asserts.h"
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#include "tests/framework/Macros.h"
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#include "tests/framework/datasets/Datasets.h"
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#include "tests/validation/Validation.h"
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#include "tests/validation/fixtures/DequantizationLayerFixture.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace
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{
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#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
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const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 });
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#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
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const auto data_types = framework::dataset::make("DataType", { DataType::F32 });
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#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
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const auto dataset_quant_f32 = combine(combine(combine(datasets::SmallShapes(), datasets::QuantizedTypes()),
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framework::dataset::make("DataType", DataType::F32)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW }));
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const auto dataset_quant_f16 = combine(combine(combine(datasets::SmallShapes(), datasets::QuantizedTypes()),
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framework::dataset::make("DataType", DataType::F16)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW }));
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const auto dataset_quant_asymm_signed_f32 = combine(combine(combine(datasets::SmallShapes(),
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framework::dataset::make("QuantizedTypes", { DataType::QASYMM8_SIGNED })),
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framework::dataset::make("DataType", DataType::F32)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW }));
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const auto dataset_quant_asymm_signed_f16 = combine(combine(combine(datasets::SmallShapes(),
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framework::dataset::make("QuantizedTypes", { DataType::QASYMM8_SIGNED })),
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framework::dataset::make("DataType", DataType::F16)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW }));
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const auto dataset_quant_per_channel_f32 = combine(combine(combine(datasets::SmallShapes(), datasets::QuantizedPerChannelTypes()),
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framework::dataset::make("DataType", DataType::F32)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }));
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const auto dataset_quant_per_channel_f16 = combine(combine(combine(datasets::SmallShapes(), datasets::QuantizedPerChannelTypes()),
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framework::dataset::make("DataType", DataType::F16)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }));
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const auto dataset_quant_nightly_f32 = combine(combine(combine(datasets::LargeShapes(), datasets::QuantizedTypes()),
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framework::dataset::make("DataType", DataType::F32)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW }));
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const auto dataset_quant_nightly_f16 = combine(combine(combine(datasets::LargeShapes(), datasets::QuantizedTypes()),
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framework::dataset::make("DataType", DataType::F16)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW }));
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const auto dataset_quant_per_channel_nightly_f32 = combine(combine(combine(datasets::LargeShapes(), datasets::QuantizedPerChannelTypes()),
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framework::dataset::make("DataType", DataType::F32)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }));
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const auto dataset_quant_per_channel_nightly_f16 = combine(combine(combine(datasets::LargeShapes(), datasets::QuantizedPerChannelTypes()),
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framework::dataset::make("DataType", DataType::F16)),
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framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }));
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const auto dataset_precommit_f16 = concat(concat(dataset_quant_f16, dataset_quant_per_channel_f16), dataset_quant_asymm_signed_f16);
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const auto dataset_precommit_f32 = concat(concat(dataset_quant_f32, dataset_quant_per_channel_f32), dataset_quant_asymm_signed_f32);
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const auto dataset_nightly_f16 = concat(dataset_quant_f16, dataset_quant_per_channel_f16);
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const auto dataset_nightly_f32 = concat(dataset_quant_f32, dataset_quant_per_channel_f32);
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} // namespace
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TEST_SUITE(NEON)
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TEST_SUITE(DequantizationLayer)
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// *INDENT-OFF*
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// clang-format off
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DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
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framework::dataset::make("InputInfo", { TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32), // Wrong input data type
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TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Wrong output data type
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TensorInfo(TensorShape(16U, 16U, 2U, 5U), 1, DataType::QASYMM8), // Missmatching shapes
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TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Valid
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TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8), // Valid
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TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::QASYMM8_SIGNED), // Valid
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}),
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framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::U8),
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TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
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TensorInfo(TensorShape(17U, 16U, 16U, 5U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
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TensorInfo(TensorShape(16U, 16U, 16U, 5U), 1, DataType::F32),
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})),
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framework::dataset::make("Expected", { false, false, false, true, true, true })),
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input_info, output_info, expected)
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{
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ARM_COMPUTE_EXPECT(bool(NEDequantizationLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS);
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}
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// clang-format on
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// *INDENT-ON*
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template <typename T>
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using NEDequantizationLayerFixture = DequantizationValidationFixture<Tensor, Accessor, NEDequantizationLayer, T>;
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#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
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TEST_SUITE(FP16)
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FIXTURE_DATA_TEST_CASE(RunSmall, NEDequantizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, dataset_precommit_f16)
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{
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// Validate output
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validate(Accessor(_target), _reference);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, NEDequantizationLayerFixture<half>, framework::DatasetMode::NIGHTLY, dataset_nightly_f16)
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{
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// Validate output
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validate(Accessor(_target), _reference);
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}
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TEST_SUITE_END() // FP16
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#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
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TEST_SUITE(FP32)
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FIXTURE_DATA_TEST_CASE(RunSmall, NEDequantizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, dataset_precommit_f32)
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{
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// Validate output
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validate(Accessor(_target), _reference);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, NEDequantizationLayerFixture<float>, framework::DatasetMode::NIGHTLY, dataset_nightly_f32)
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{
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// Validate output
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validate(Accessor(_target), _reference);
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}
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TEST_SUITE_END() // FP32
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TEST_SUITE_END() // DequantizationLayer
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TEST_SUITE_END() // NEON
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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