| /* |
| * Copyright (c) 2017-2020 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/Types.h" |
| #include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.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/FullyConnectedLayerDataset.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/FullyConnectedLayerFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| /** Tolerance for float operations */ |
| constexpr RelativeTolerance<float> rel_tolerance_f32(0.01f); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F32 */ |
| constexpr AbsoluteTolerance<float> abs_tolerance_f32(0.001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for DataType::F32 */ |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| const AbsoluteTolerance<float> abs_tolerance_f16(0.3f); /**< Absolute tolerance value for comparing reference's output against implementation's output for DataType::F16 */ |
| const RelativeTolerance<half_float::half> rel_tolerance_f16(half_float::half(0.2f)); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F16 */ |
| constexpr float tolerance_num_f16 = 0.07f; /**< Tolerance number for FP16 */ |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC*/ |
| |
| /** Tolerance for quantized asymmetric operations */ |
| constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); |
| constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_signed(1); |
| |
| /** CNN data types */ |
| const auto CNNDataTypes = framework::dataset::make("DataType", |
| { |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| DataType::F16, |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| DataType::F32, |
| }); |
| |
| const auto FullyConnectedParameters = combine(framework::dataset::make("TransposeWeights", { false, true }), framework::dataset::make("ReshapeWeights", { false, true })); |
| |
| const auto QuantizationData = framework::dataset::make("QuantizationInfo", |
| { |
| QuantizationInfo(1.f / 256.f, 10), |
| QuantizationInfo(1.1f, 10), |
| }); |
| const auto EmptyActivationFunctionDataset = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(), |
| }); |
| const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.75f, 0.25f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH), |
| }); |
| |
| const auto ActivationFunctionsQuantizedDataset = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.75f, 0.25f), |
| }); |
| } // namespace |
| |
| TEST_SUITE(NEON) |
| TEST_SUITE(FullyConnectedLayer) |
| |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Mismatching data types |
| TensorInfo(TensorShape(8U, 4U, 6U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(8U, 4U, 6U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Invalid weights dimensions |
| TensorInfo(TensorShape(9U, 5U, 7U, 3U), 1, DataType::F32), // Wrongly reshaped weights |
| TensorInfo(TensorShape(8U, 4U, 6U, 4U), 1, DataType::F32), |
| }), |
| framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(315U, 271U), 1, DataType::F16), |
| TensorInfo(TensorShape(192U, 192U), 1, DataType::F32), |
| TensorInfo(TensorShape(192U, 192U), 1, DataType::F32), |
| TensorInfo(TensorShape(217U, 315U), 1, DataType::F32), |
| TensorInfo(TensorShape(217U, 315U), 1, DataType::F32), |
| TensorInfo(TensorShape(192U, 192U), 1, DataType::F32), |
| })), |
| framework::dataset::make("BiasInfo",{ TensorInfo(TensorShape(271U), 1, DataType::F32), |
| TensorInfo(TensorShape(192U), 1, DataType::F32), |
| TensorInfo(TensorShape(192U), 1, DataType::F32), |
| TensorInfo(TensorShape(271U), 1, DataType::F32), |
| TensorInfo(TensorShape(271U), 1, DataType::F32), |
| TensorInfo(TensorShape(192U), 1, DataType::F32), |
| })), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), |
| TensorInfo(TensorShape(192U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(192U, 4U), 1, DataType::F32), |
| TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), |
| TensorInfo(TensorShape(271U, 3U), 1, DataType::F32), |
| TensorInfo(TensorShape(192U, 4U), 1, DataType::F32), |
| })), |
| framework::dataset::make("TransposeWeights",{ true, true, false, true, true, true })), |
| framework::dataset::make("ReshapedWeights",{ false, false, false, false, false , false})), |
| framework::dataset::make("Expected", { false, true, true, false, false, true })), |
| input_info, weights_info, bias_info, output_info, transpose_weights, reshaped_weights, expected) |
| { |
| // Create Fully Connected layer info |
| FullyConnectedLayerInfo fc_info; |
| fc_info.transpose_weights = transpose_weights; |
| fc_info.are_weights_reshaped = reshaped_weights; |
| |
| Status status = NEFullyConnectedLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), fc_info); |
| ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| |
| template <typename T> |
| using NEFullyConnectedLayerFixture = FullyConnectedLayerValidationFixture<Tensor, Accessor, NEFullyConnectedLayer, T>; |
| |
| TEST_SUITE(Float) |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| TEST_SUITE(FP16) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F16)), |
| EmptyActivationFunctionDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); |
| } |
| FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine( |
| combine(datasets::FullyConnectedLayerWithActivationDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F16)), |
| ActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F16)), |
| EmptyActivationFunctionDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num_f16, abs_tolerance_f16); |
| } |
| TEST_SUITE_END() |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| |
| TEST_SUITE(FP32) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallFullyConnectedLayerDataset(), FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F32)), |
| EmptyActivationFunctionDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine( |
| combine(datasets::FullyConnectedLayerWithActivationDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F32)), |
| ActivationFunctionsDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); |
| } |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeFullyConnectedLayerDataset(), FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::F32)), |
| EmptyActivationFunctionDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, rel_tolerance_f32, 0, abs_tolerance_f32); |
| } |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| |
| template <typename T> |
| using NEFullyConnectedLayerQuantizedFixture = FullyConnectedLayerValidationQuantizedFixture<Tensor, Accessor, NEFullyConnectedLayer, T>; |
| |
| TEST_SUITE(Quantized) |
| TEST_SUITE(QASYMM8) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine( |
| combine(datasets::SmallFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| QuantizationData), |
| EmptyActivationFunctionDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine( |
| combine(datasets::FullyConnectedLayerWithActivationDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| QuantizationData), |
| ActivationFunctionsQuantizedDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunLarge, NEFullyConnectedLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine( |
| combine(datasets::LargeFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::QASYMM8)), |
| QuantizationData), |
| EmptyActivationFunctionDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8); |
| } |
| TEST_SUITE_END() |
| TEST_SUITE(QASYMM8_SIGNED) |
| FIXTURE_DATA_TEST_CASE(RunSmall, NEFullyConnectedLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine( |
| combine(datasets::SmallFullyConnectedLayerDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), |
| QuantizationData), |
| EmptyActivationFunctionDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8_signed); |
| } |
| |
| FIXTURE_DATA_TEST_CASE(RunWithActivation, NEFullyConnectedLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine( |
| combine(datasets::FullyConnectedLayerWithActivationDataset(), |
| FullyConnectedParameters), |
| framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), |
| QuantizationData), |
| ActivationFunctionsQuantizedDataset)) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qasymm8_signed); |
| } |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |