| /* |
| * Copyright (c) 2017-2018 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/NEBatchNormalizationLayer.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/RandomBatchNormalizationLayerDataset.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/BatchNormalizationLayerFixture.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace |
| { |
| constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */ |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| constexpr AbsoluteTolerance<float> tolerance_qs8(3.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */ |
| constexpr AbsoluteTolerance<float> tolerance_qs16(6.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */ |
| const auto act_infos = framework::dataset::make("ActivationInfo", |
| { |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f), |
| }); |
| } // namespace |
| |
| TEST_SUITE(NEON) |
| TEST_SUITE(BatchNormalizationLayer) |
| |
| template <typename T> |
| using NEBatchNormalizationLayerFixture = BatchNormalizationLayerValidationFixture<Tensor, Accessor, NEBatchNormalizationLayer, T>; |
| |
| DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(datasets::RandomBatchNormalizationLayerDataset(), |
| combine(framework::dataset::make("UseBeta", { false, true }), framework::dataset::make("UseGamma", { false, true }))), |
| framework::dataset::make("DataType", { DataType::QS8, DataType::QS16, DataType::F32 })), |
| shape0, shape1, epsilon, use_beta, use_gamma, dt) |
| { |
| // Set fixed point position data type allowed |
| const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0; |
| |
| // Create tensors |
| Tensor src = create_tensor<Tensor>(shape0, dt, 1, fixed_point_position); |
| Tensor dst = create_tensor<Tensor>(shape0, dt, 1, fixed_point_position); |
| Tensor mean = create_tensor<Tensor>(shape1, dt, 1, fixed_point_position); |
| Tensor var = create_tensor<Tensor>(shape1, dt, 1, fixed_point_position); |
| Tensor beta = create_tensor<Tensor>(shape1, dt, 1, fixed_point_position); |
| Tensor gamma = create_tensor<Tensor>(shape1, dt, 1, fixed_point_position); |
| |
| // Create and Configure function |
| NEBatchNormalizationLayer norm; |
| Tensor *beta_ptr = use_beta ? &beta : nullptr; |
| Tensor *gamma_ptr = use_gamma ? &gamma : nullptr; |
| norm.configure(&src, &dst, &mean, &var, beta_ptr, gamma_ptr, epsilon); |
| |
| // Validate valid region |
| const ValidRegion valid_region = shape_to_valid_region(shape0); |
| validate(dst.info()->valid_region(), valid_region); |
| } |
| |
| // *INDENT-OFF* |
| // clang-format off |
| DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( |
| framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Window shrink |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching data types |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid mean/var/beta/gamma shape |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point position |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Fused activation with fixed point not supported |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Fused activation's a < b |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), |
| }), |
| framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16), |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3), |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3), |
| TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), |
| TensorInfo(), |
| })), |
| framework::dataset::make("MVBGInfo",{ TensorInfo(TensorShape(2U), 1, DataType::F32), |
| TensorInfo(TensorShape(2U), 1, DataType::F32), |
| TensorInfo(TensorShape(2U), 1, DataType::F16), |
| TensorInfo(TensorShape(2U), 1, DataType::F32), |
| TensorInfo(TensorShape(5U), 1, DataType::F32), |
| TensorInfo(TensorShape(2U), 1, DataType::QS8, 2), |
| TensorInfo(TensorShape(2U), 1, DataType::QS8, 2), |
| TensorInfo(TensorShape(2U), 1, DataType::F32), |
| TensorInfo(TensorShape(2U), 1, DataType::QS8, 2), |
| TensorInfo(TensorShape(2U), 1, DataType::QS8, 2), |
| })), |
| framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f), |
| ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f), |
| ActivationLayerInfo(), |
| ActivationLayerInfo(), |
| })), |
| framework::dataset::make("Expected", { true, false, false, false, false, false, false, false, true, true})), |
| input_info, output_info, mvbg_info, act_info, expected) |
| { |
| const auto &mean_info = mvbg_info; |
| const auto &var_info = mvbg_info; |
| const auto &beta_info = mvbg_info; |
| const auto &gamma_info = mvbg_info; |
| bool has_error = bool(NEBatchNormalizationLayer::validate( |
| &input_info.clone()->set_is_resizable(false), output_info.total_size() ? &output_info.clone()->set_is_resizable(false) : nullptr, |
| &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false), |
| &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info)); |
| ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS); |
| } |
| // clang-format on |
| // *INDENT-ON* |
| |
| TEST_SUITE(Float) |
| FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(), |
| combine(framework::dataset::make("UseBeta", { false, true }), |
| framework::dataset::make("UseGamma", { false, true }))), |
| act_infos), |
| framework::dataset::make("DataType", DataType::F32))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_f32, 0); |
| } |
| TEST_SUITE_END() |
| |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| TEST_SUITE(Float16) |
| FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(), |
| combine(framework::dataset::make("UseBeta", { false, true }), |
| framework::dataset::make("UseGamma", { false, true }))), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo())), |
| framework::dataset::make("DataType", DataType::F16))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_f16, 0); |
| } |
| TEST_SUITE_END() |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| |
| TEST_SUITE(Quantized) |
| template <typename T> |
| using NEBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture<Tensor, Accessor, NEBatchNormalizationLayer, T>; |
| |
| TEST_SUITE(QS8) |
| FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(), |
| framework::dataset::make("UseBeta", false)), |
| framework::dataset::make("UseGamma", false)), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo())), |
| framework::dataset::make("DataType", DataType::QS8)), |
| framework::dataset::make("FractionalBits", 1, 6))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qs8, 0); |
| } |
| TEST_SUITE_END() |
| |
| TEST_SUITE(QS16) |
| FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, |
| combine(combine(combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(), |
| framework::dataset::make("UseBeta", false)), |
| framework::dataset::make("UseGamma", false)), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo())), |
| framework::dataset::make("DataType", DataType::QS16)), |
| framework::dataset::make("FractionalBits", 1, 14))) |
| { |
| // Validate output |
| validate(Accessor(_target), _reference, tolerance_qs16, 0); |
| } |
| TEST_SUITE_END() |
| |
| TEST_SUITE_END() |
| |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |