From 9688378ce14f0c2663a27b2c879ed1928247a08e Mon Sep 17 00:00:00 2001 From: Sanghoon Lee Date: Fri, 15 Sep 2017 14:10:48 +0100 Subject: COMPMID-494: Port BatchNormalizationLayer to new validation Change-Id: Ief5334dd1cf571d977acf4ce9e5f580c5c9ab433 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/88158 Tested-by: Kaizen Reviewed-by: Pablo Tello --- .../RandomBatchNormalizationLayerDataset.h | 53 +++++ tests/validation/CL/BatchNormalizationLayer.cpp | 119 ++++++++++ tests/validation/CPP/BatchNormalizationLayer.cpp | 125 ++++++++++ tests/validation/CPP/BatchNormalizationLayer.h | 49 ++++ tests/validation/Helpers.h | 25 ++ tests/validation/NEON/BatchNormalizationLayer.cpp | 133 +++++++++++ .../fixtures/BatchNormalizationLayerFixture.h | 167 +++++++++++++ .../validation_old/CL/BatchNormalizationLayer.cpp | 227 ------------------ .../NEON/BatchNormalizationLayer.cpp | 258 --------------------- tests/validation_old/Reference.cpp | 62 ----- tests/validation_old/Reference.h | 11 - tests/validation_old/ReferenceCPP.cpp | 13 -- tests/validation_old/ReferenceCPP.h | 14 -- tests/validation_old/TensorOperations.h | 64 ----- tests/validation_old/TensorVisitors.h | 27 --- 15 files changed, 671 insertions(+), 676 deletions(-) create mode 100644 tests/datasets/RandomBatchNormalizationLayerDataset.h create mode 100644 tests/validation/CL/BatchNormalizationLayer.cpp create mode 100644 tests/validation/CPP/BatchNormalizationLayer.cpp create mode 100644 tests/validation/CPP/BatchNormalizationLayer.h create mode 100644 tests/validation/NEON/BatchNormalizationLayer.cpp create mode 100644 tests/validation/fixtures/BatchNormalizationLayerFixture.h delete mode 100644 tests/validation_old/CL/BatchNormalizationLayer.cpp delete mode 100644 tests/validation_old/NEON/BatchNormalizationLayer.cpp diff --git a/tests/datasets/RandomBatchNormalizationLayerDataset.h b/tests/datasets/RandomBatchNormalizationLayerDataset.h new file mode 100644 index 0000000000..f4c61e06d5 --- /dev/null +++ b/tests/datasets/RandomBatchNormalizationLayerDataset.h @@ -0,0 +1,53 @@ +/* + * Copyright (c) 2017 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. + */ +#ifndef ARM_COMPUTE_TEST_RANDOM_BATCH_NORMALIZATION_LAYER_DATASET +#define ARM_COMPUTE_TEST_RANDOM_BATCH_NORMALIZATION_LAYER_DATASET + +#include "tests/datasets/BatchNormalizationLayerDataset.h" + +#include "tests/TypePrinter.h" + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" + +namespace arm_compute +{ +namespace test +{ +namespace datasets +{ +class RandomBatchNormalizationLayerDataset final : public BatchNormalizationLayerDataset +{ +public: + RandomBatchNormalizationLayerDataset() + { + add_config(TensorShape(15U, 16U, 2U, 12U), TensorShape(2U), 0.1f); + add_config(TensorShape(21U, 11U, 12U, 7U), TensorShape(12U), 0.1f); + add_config(TensorShape(7U, 3U, 6U, 11U), TensorShape(6U), 0.1f); + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_RANDOM_BATCH_NORMALIZATION_LAYER_DATASET */ diff --git a/tests/validation/CL/BatchNormalizationLayer.cpp b/tests/validation/CL/BatchNormalizationLayer.cpp new file mode 100644 index 0000000000..ac30c638b5 --- /dev/null +++ b/tests/validation/CL/BatchNormalizationLayer.cpp @@ -0,0 +1,119 @@ +/* + * Copyright (c) 2017 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/CL/CLTensor.h" +#include "arm_compute/runtime/CL/CLTensorAllocator.h" +#include "arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h" +#include "tests/CL/CLAccessor.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 tolerance_f(0.00001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ +constexpr AbsoluteTolerance tolerance_qs8(3.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */ +constexpr AbsoluteTolerance tolerance_qs16(6.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */ +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(BatchNormalizationLayer) + +template +using CLBatchNormalizationLayerFixture = BatchNormalizationLayerValidationFixture; + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::RandomBatchNormalizationLayerDataset(), framework::dataset::make("DataType", { DataType::QS8, DataType::QS16, DataType::F32 })), + shape0, shape1, epsilon, dt) +{ + // Set fixed point position data type allowed + int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0; + + // Create tensors + CLTensor src = create_tensor(shape0, dt, 1, fixed_point_position); + CLTensor dst = create_tensor(shape0, dt, 1, fixed_point_position); + CLTensor mean = create_tensor(shape1, dt, 1, fixed_point_position); + CLTensor var = create_tensor(shape1, dt, 1, fixed_point_position); + CLTensor beta = create_tensor(shape1, dt, 1, fixed_point_position); + CLTensor gamma = create_tensor(shape1, dt, 1, fixed_point_position); + + // Create and Configure function + CLBatchNormalizationLayer norm; + norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape0); + validate(dst.info()->valid_region(), valid_region); +} + +TEST_SUITE(Float) +FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(), + framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f, 0); +} +TEST_SUITE_END() + +TEST_SUITE(Quantized) +template +using CLBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture; + +TEST_SUITE(QS8) +FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(), + framework::dataset::make("DataType", DataType::QS8)), + framework::dataset::make("FractionalBits", 1, 6))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_qs8, 0); +} +TEST_SUITE_END() + +TEST_SUITE(QS16) +FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(), + framework::dataset::make("DataType", DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_qs16, 0); +} +TEST_SUITE_END() + +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/CPP/BatchNormalizationLayer.cpp b/tests/validation/CPP/BatchNormalizationLayer.cpp new file mode 100644 index 0000000000..37e2d55bf1 --- /dev/null +++ b/tests/validation/CPP/BatchNormalizationLayer.cpp @@ -0,0 +1,125 @@ +/* + * Copyright (c) 2017 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 "BatchNormalizationLayer.h" + +#include "tests/validation/FixedPoint.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +// Batch Normalization Layer for fixed point type +template ::value, int>::type *> +SimpleTensor batch_normalization_layer(const SimpleTensor &src, const SimpleTensor &mean, const SimpleTensor &var, const SimpleTensor &beta, const SimpleTensor &gamma, float epsilon, + int fixed_point_position) +{ + SimpleTensor result(src.shape(), src.data_type()); + + const auto cols = static_cast(src.shape()[0]); + const auto rows = static_cast(src.shape()[1]); + const auto depth = static_cast(src.shape()[2]); + int upper_dims = src.shape().total_size() / (cols * rows * depth); + + for(int r = 0; r < upper_dims; ++r) + { + for(int i = 0; i < depth; ++i) + { + for(int k = 0; k < rows; ++k) + { + for(int l = 0; l < cols; ++l) + { + const int pos = l + k * cols + i * rows * cols + r * cols * rows * depth; + + fixed_point_arithmetic::fixed_point src_qs(src[pos], fixed_point_position, true); + fixed_point_arithmetic::fixed_point var_qs(var[i], fixed_point_position, true); + fixed_point_arithmetic::fixed_point mean_qs(mean[i], fixed_point_position, true); + fixed_point_arithmetic::fixed_point beta_qs(beta[i], fixed_point_position, true); + fixed_point_arithmetic::fixed_point gamma_qs(gamma[i], fixed_point_position, true); + fixed_point_arithmetic::fixed_point epsilon_qs(epsilon, fixed_point_position); + + auto denominator = fixed_point_arithmetic::inv_sqrt(var_qs + epsilon_qs); + auto numerator = src_qs - mean_qs; + auto x_bar = numerator * denominator; + x_bar = beta_qs + x_bar * gamma_qs; + result[pos] = x_bar.raw(); + } + } + } + } + + return result; +} + +// Batch Normalization Layer for floating point type +template ::value, int>::type *> +SimpleTensor batch_normalization_layer(const SimpleTensor &src, const SimpleTensor &mean, const SimpleTensor &var, const SimpleTensor &beta, const SimpleTensor &gamma, float epsilon, + int fixed_point_position) +{ + ARM_COMPUTE_UNUSED(fixed_point_position); + + SimpleTensor result(src.shape(), src.data_type()); + + const auto cols = static_cast(src.shape()[0]); + const auto rows = static_cast(src.shape()[1]); + const auto depth = static_cast(src.shape()[2]); + int upper_dims = src.shape().total_size() / (cols * rows * depth); + + for(int r = 0; r < upper_dims; ++r) + { + for(int i = 0; i < depth; ++i) + { + for(int k = 0; k < rows; ++k) + { + for(int l = 0; l < cols; ++l) + { + const int pos = l + k * cols + i * rows * cols + r * cols * rows * depth; + const float denominator = sqrt(var[i] + epsilon); + const float numerator = src[pos] - mean[i]; + const float x_bar = numerator / denominator; + result[pos] = beta[i] + x_bar * gamma[i]; + } + } + } + } + return result; +} +template SimpleTensor batch_normalization_layer(const SimpleTensor &src, const SimpleTensor &mean, const SimpleTensor &var, const SimpleTensor &beta, + const SimpleTensor &gamma, float epsilon, int fixed_point_position); +template SimpleTensor batch_normalization_layer(const SimpleTensor &src, const SimpleTensor &mean, const SimpleTensor &var, const SimpleTensor &beta, + const SimpleTensor &gamma, float epsilon, int fixed_point_position); +template SimpleTensor batch_normalization_layer(const SimpleTensor &src, const SimpleTensor &mean, const SimpleTensor &var, const SimpleTensor &beta, + const SimpleTensor &gamma, float epsilon, int fixed_point_position); +template SimpleTensor batch_normalization_layer(const SimpleTensor &src, const SimpleTensor &mean, const SimpleTensor &var, + const SimpleTensor &beta, + const SimpleTensor &gamma, float epsilon, int fixed_point_position); + +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/CPP/BatchNormalizationLayer.h b/tests/validation/CPP/BatchNormalizationLayer.h new file mode 100644 index 0000000000..1a554adf7e --- /dev/null +++ b/tests/validation/CPP/BatchNormalizationLayer.h @@ -0,0 +1,49 @@ +/* + * Copyright (c) 2017 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. + */ +#ifndef __ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_H__ +#define __ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_H__ + +#include "tests/SimpleTensor.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +template ::value, int>::type * = nullptr> +SimpleTensor batch_normalization_layer(const SimpleTensor &src, const SimpleTensor &mean, const SimpleTensor &var, const SimpleTensor &beta, const SimpleTensor &gamma, float epsilon, + int fixed_point_position); + +template ::value, int>::type * = nullptr> +SimpleTensor batch_normalization_layer(const SimpleTensor &src, const SimpleTensor &mean, const SimpleTensor &var, const SimpleTensor &beta, const SimpleTensor &gamma, float epsilon, + int fixed_point_position); +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* __ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_H__ */ diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h index 85002eb599..30c67245a2 100644 --- a/tests/validation/Helpers.h +++ b/tests/validation/Helpers.h @@ -202,6 +202,31 @@ void fill_lookuptable(T &&table) table[i] = distribution(generator); } } + +/** Helper function to get the testing range for batch normalization layer. + * + * @param[in] fixed_point_position (Optional) Number of bits for the fractional part. Defaults to 1. + * + * @return A pair containing the lower upper testing bounds. + */ +template +std::pair get_batchnormalization_layer_test_bounds(int fixed_point_position = 1) +{ + bool is_float = std::is_floating_point::value; + std::pair bounds; + + // Set initial values + if(is_float) + { + bounds = std::make_pair(-1.f, 1.f); + } + else + { + bounds = std::make_pair(1, 1 << (fixed_point_position)); + } + + return bounds; +} } // namespace validation } // namespace test } // namespace arm_compute diff --git a/tests/validation/NEON/BatchNormalizationLayer.cpp b/tests/validation/NEON/BatchNormalizationLayer.cpp new file mode 100644 index 0000000000..9ca26ebdaa --- /dev/null +++ b/tests/validation/NEON/BatchNormalizationLayer.cpp @@ -0,0 +1,133 @@ +/* + * Copyright (c) 2017 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 tolerance_f32(0.00001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ +#ifdef ARM_COMPUTE_ENABLE_FP16 +constexpr AbsoluteTolerance tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */ +#endif /* ARM_COMPUTE_ENABLE_FP16 */ +constexpr AbsoluteTolerance tolerance_qs8(3.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */ +constexpr AbsoluteTolerance tolerance_qs16(6.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */ +} // namespace + +TEST_SUITE(NEON) +TEST_SUITE(BatchNormalizationLayer) + +template +using NEBatchNormalizationLayerFixture = BatchNormalizationLayerValidationFixture; + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::RandomBatchNormalizationLayerDataset(), framework::dataset::make("DataType", { DataType::QS8, DataType::QS16, DataType::F32 })), + shape0, shape1, epsilon, dt) +{ + // Set fixed point position data type allowed + int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0; + + // Create tensors + Tensor src = create_tensor(shape0, dt, 1, fixed_point_position); + Tensor dst = create_tensor(shape0, dt, 1, fixed_point_position); + Tensor mean = create_tensor(shape1, dt, 1, fixed_point_position); + Tensor var = create_tensor(shape1, dt, 1, fixed_point_position); + Tensor beta = create_tensor(shape1, dt, 1, fixed_point_position); + Tensor gamma = create_tensor(shape1, dt, 1, fixed_point_position); + + // Create and Configure function + NEBatchNormalizationLayer norm; + norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape0); + validate(dst.info()->valid_region(), valid_region); +} + +TEST_SUITE(Float) +FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(), + framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_f32, 0); +} +TEST_SUITE_END() + +#ifdef ARM_COMPUTE_ENABLE_FP16 +TEST_SUITE(Float16) +FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(), + framework::dataset::make("DataType", DataType::F16))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_f16, 0); +} +TEST_SUITE_END() +#endif /* ARM_COMPUTE_ENABLE_FP16 */ + +TEST_SUITE(Quantized) +template +using NEBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture; + +TEST_SUITE(QS8) +FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(), + 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, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(), + 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 diff --git a/tests/validation/fixtures/BatchNormalizationLayerFixture.h b/tests/validation/fixtures/BatchNormalizationLayerFixture.h new file mode 100644 index 0000000000..f4772a8dd9 --- /dev/null +++ b/tests/validation/fixtures/BatchNormalizationLayerFixture.h @@ -0,0 +1,167 @@ +/* + * Copyright (c) 2017 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. + */ +#ifndef ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FIXTURE +#define ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FIXTURE + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "tests/AssetsLibrary.h" +#include "tests/Globals.h" +#include "tests/IAccessor.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Fixture.h" +#include "tests/validation/CPP/BatchNormalizationLayer.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template +class BatchNormalizationLayerValidationFixedPointFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape shape0, TensorShape shape1, float epsilon, DataType dt, int fractional_bits) + { + _fractional_bits = fractional_bits; + _data_type = dt; + _target = compute_target(shape0, shape1, epsilon, dt, fractional_bits); + _reference = compute_reference(shape0, shape1, epsilon, dt, fractional_bits); + } + +protected: + template + void fill(U &&src_tensor, U &&mean_tensor, U &&var_tensor, U &&beta_tensor, U &&gamma_tensor) + { + if(is_data_type_float(_data_type)) + { + float min_bound = 0.f; + float max_bound = 0.f; + std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds(); + std::uniform_real_distribution<> distribution(min_bound, max_bound); + std::uniform_real_distribution<> distribution_var(0, max_bound); + library->fill(src_tensor, distribution, 0); + library->fill(mean_tensor, distribution, 1); + library->fill(var_tensor, distribution_var, 0); + library->fill(beta_tensor, distribution, 3); + library->fill(gamma_tensor, distribution, 4); + } + else + { + int min_bound = 0; + int max_bound = 0; + std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds(_fractional_bits); + std::uniform_int_distribution<> distribution(min_bound, max_bound); + std::uniform_int_distribution<> distribution_var(0, max_bound); + library->fill(src_tensor, distribution, 0); + library->fill(mean_tensor, distribution, 1); + library->fill(var_tensor, distribution_var, 0); + library->fill(beta_tensor, distribution, 3); + library->fill(gamma_tensor, distribution, 4); + } + } + + TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, float epsilon, DataType dt, int fixed_point_position) + { + // Create tensors + TensorType src = create_tensor(shape0, dt, 1, fixed_point_position); + TensorType dst = create_tensor(shape0, dt, 1, fixed_point_position); + TensorType mean = create_tensor(shape1, dt, 1, fixed_point_position); + TensorType var = create_tensor(shape1, dt, 1, fixed_point_position); + TensorType beta = create_tensor(shape1, dt, 1, fixed_point_position); + TensorType gamma = create_tensor(shape1, dt, 1, fixed_point_position); + + // Create and configure function + FunctionType norm; + norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon); + + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(mean.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(var.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(beta.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(gamma.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + src.allocator()->allocate(); + dst.allocator()->allocate(); + mean.allocator()->allocate(); + var.allocator()->allocate(); + beta.allocator()->allocate(); + gamma.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!mean.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!var.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!beta.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!gamma.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(src), AccessorType(mean), AccessorType(var), AccessorType(beta), AccessorType(gamma)); + + // Compute function + norm.run(); + + return dst; + } + + SimpleTensor compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, DataType dt, int fixed_point_position) + { + // Create reference + SimpleTensor ref_src{ shape0, dt, 1, fixed_point_position }; + SimpleTensor ref_mean{ shape1, dt, 1, fixed_point_position }; + SimpleTensor ref_var{ shape1, dt, 1, fixed_point_position }; + SimpleTensor ref_beta{ shape1, dt, 1, fixed_point_position }; + SimpleTensor ref_gamma{ shape1, dt, 1, fixed_point_position }; + + // Fill reference + fill(ref_src, ref_mean, ref_var, ref_beta, ref_gamma); + + return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, fixed_point_position); + } + + TensorType _target{}; + SimpleTensor _reference{}; + int _fractional_bits{}; + DataType _data_type{}; +}; + +template +class BatchNormalizationLayerValidationFixture : public BatchNormalizationLayerValidationFixedPointFixture +{ +public: + template + void setup(TensorShape shape0, TensorShape shape1, float epsilon, DataType dt) + { + BatchNormalizationLayerValidationFixedPointFixture::setup(shape0, shape1, epsilon, dt, 0); + } +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_BATCH_NORMALIZATION_LAYER_FIXTURE */ diff --git a/tests/validation_old/CL/BatchNormalizationLayer.cpp b/tests/validation_old/CL/BatchNormalizationLayer.cpp deleted file mode 100644 index 75c9a580ea..0000000000 --- a/tests/validation_old/CL/BatchNormalizationLayer.cpp +++ /dev/null @@ -1,227 +0,0 @@ -/* - * Copyright (c) 2017 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 "CL/CLAccessor.h" -#include "TypePrinter.h" -#include "Utils.h" -#include "tests/AssetsLibrary.h" -#include "tests/Globals.h" -#include "tests/validation_old/Datasets.h" -#include "tests/validation_old/Helpers.h" -#include "tests/validation_old/Reference.h" -#include "tests/validation_old/Validation.h" -#include "tests/validation_old/dataset/BatchNormalizationLayerDataset.h" - -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h" -#include "arm_compute/runtime/Tensor.h" -#include "arm_compute/runtime/TensorAllocator.h" - -#include - -using namespace arm_compute; -using namespace arm_compute::test; -using namespace arm_compute::test::validation; - -namespace -{ -const float tolerance_f = 1e-05; /**< Tolerance value for comparing reference's output against floating point implementation's output */ -const float tolerance_qs8 = 3; /**< Tolerance value for comparing reference's output against quantized implementation's output */ -const float tolerance_qs16 = 6; /**< Tolerance value for comparing reference's output against quantized implementation's output */ - -/** Compute Neon batch normalization function. - * - * @param[in] shape Shape of the input and output tensors. - * @param[in] dt Data type of input and output tensors. - * @param[in] norm_info Normalization Layer information. - * - * @return Computed output tensor. - */ -CLTensor compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position = 0) -{ - // Create tensors - CLTensor src = create_tensor(shape0, dt, 1, fixed_point_position); - CLTensor dst = create_tensor(shape0, dt, 1, fixed_point_position); - CLTensor mean = create_tensor(shape1, dt, 1, fixed_point_position); - CLTensor var = create_tensor(shape1, dt, 1, fixed_point_position); - CLTensor beta = create_tensor(shape1, dt, 1, fixed_point_position); - CLTensor gamma = create_tensor(shape1, dt, 1, fixed_point_position); - - // Create and configure function - CLBatchNormalizationLayer norm; - norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon); - - // Allocate tensors - src.allocator()->allocate(); - dst.allocator()->allocate(); - mean.allocator()->allocate(); - var.allocator()->allocate(); - beta.allocator()->allocate(); - gamma.allocator()->allocate(); - - BOOST_TEST(!src.info()->is_resizable()); - BOOST_TEST(!dst.info()->is_resizable()); - BOOST_TEST(!mean.info()->is_resizable()); - BOOST_TEST(!var.info()->is_resizable()); - BOOST_TEST(!beta.info()->is_resizable()); - BOOST_TEST(!gamma.info()->is_resizable()); - - // Fill tensors - if(dt == DataType::F32) - { - float min_bound = 0.f; - float max_bound = 0.f; - std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds(); - std::uniform_real_distribution<> distribution(min_bound, max_bound); - std::uniform_real_distribution<> distribution_var(0, max_bound); - library->fill(CLAccessor(src), distribution, 0); - library->fill(CLAccessor(mean), distribution, 1); - library->fill(CLAccessor(var), distribution_var, 0); - library->fill(CLAccessor(beta), distribution, 3); - library->fill(CLAccessor(gamma), distribution, 4); - } - else - { - int min_bound = 0; - int max_bound = 0; - if(dt == DataType::QS8) - { - std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds(fixed_point_position); - } - else - { - std::tie(min_bound, max_bound) = get_batchnormalization_layer_test_bounds(fixed_point_position); - } - std::uniform_int_distribution<> distribution(min_bound, max_bound); - std::uniform_int_distribution<> distribution_var(0, max_bound); - library->fill(CLAccessor(src), distribution, 0); - library->fill(CLAccessor(mean), distribution, 1); - library->fill(CLAccessor(var), distribution_var, 0); - library->fill(CLAccessor(beta), distribution, 3); - library->fill(CLAccessor(gamma), distribution, 4); - } - - // Compute function - norm.run(); - - return dst; -} -} // namespace - -#ifndef DOXYGEN_SKIP_THIS -BOOST_AUTO_TEST_SUITE(CL) -BOOST_AUTO_TEST_SUITE(BatchNormalizationLayer) - -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly")) -BOOST_DATA_TEST_CASE(Configuration, RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make({ DataType::QS8, DataType::QS16, DataType::F32 }), obj, dt) -{ - // Set fixed point position data type allowed - int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0; - - // Create tensors - CLTensor src = create_tensor(obj.shape0, dt, 1, fixed_point_position); - CLTensor dst = create_tensor(obj.shape0, dt, 1, fixed_point_position); - CLTensor mean = create_tensor(obj.shape1, dt, 1, fixed_point_position); - CLTensor var = create_tensor(obj.shape1, dt, 1, fixed_point_position); - CLTensor beta = create_tensor(obj.shape1, dt, 1, fixed_point_position); - CLTensor gamma = create_tensor(obj.shape1, dt, 1, fixed_point_position); - - BOOST_TEST(src.info()->is_resizable()); - BOOST_TEST(dst.info()->is_resizable()); - BOOST_TEST(mean.info()->is_resizable()); - BOOST_TEST(var.info()->is_resizable()); - BOOST_TEST(beta.info()->is_resizable()); - BOOST_TEST(gamma.info()->is_resizable()); - - // Create and configure function - CLBatchNormalizationLayer norm; - norm.configure(&src, &dst, &mean, &var, &beta, &gamma, obj.epsilon); - - // Validate valid region - const ValidRegion valid_region = shape_to_valid_region(obj.shape0); - const ValidRegion valid_region_vec = shape_to_valid_region(obj.shape1); - validate(src.info()->valid_region(), valid_region); - validate(dst.info()->valid_region(), valid_region); - validate(mean.info()->valid_region(), valid_region_vec); - validate(var.info()->valid_region(), valid_region_vec); - validate(beta.info()->valid_region(), valid_region_vec); - validate(gamma.info()->valid_region(), valid_region_vec); -} - -BOOST_AUTO_TEST_SUITE(Float) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(Random, - RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make(DataType::F32), - obj, dt) -{ - // Compute function - CLTensor dst = compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon); - - // Validate output - validate(CLAccessor(dst), ref_dst, tolerance_f, 0); -} -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE(Quantized) - -BOOST_AUTO_TEST_SUITE(QS8) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(Random, - RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make(DataType::QS8) * boost::unit_test::data::xrange(1, 6), - obj, dt, fixed_point_position) -{ - // Compute function - CLTensor dst = compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon, fixed_point_position); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon, fixed_point_position); - - // Validate output - validate(CLAccessor(dst), ref_dst, tolerance_qs8, 0); -} -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE(QS16) -BOOST_DATA_TEST_CASE(Random, - RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make(DataType::QS16) * boost::unit_test::data::xrange(1, 14), - obj, dt, fixed_point_position) -{ - // Compute function - CLTensor dst = compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon, fixed_point_position); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon, fixed_point_position); - - // Validate output - validate(CLAccessor(dst), ref_dst, tolerance_qs16, 0); -} -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE_END() -BOOST_AUTO_TEST_SUITE_END() -BOOST_AUTO_TEST_SUITE_END() -#endif /* DOXYGEN_SKIP_THIS */ diff --git a/tests/validation_old/NEON/BatchNormalizationLayer.cpp b/tests/validation_old/NEON/BatchNormalizationLayer.cpp deleted file mode 100644 index d98f99a63c..0000000000 --- a/tests/validation_old/NEON/BatchNormalizationLayer.cpp +++ /dev/null @@ -1,258 +0,0 @@ -/* - * Copyright (c) 2017 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 "NEON/Accessor.h" -#include "TypePrinter.h" -#include "tests/Globals.h" -#include "tests/NEON/Helper.h" -#include "tests/Utils.h" -#include "tests/validation_old/Datasets.h" -#include "tests/validation_old/Helpers.h" -#include "tests/validation_old/Reference.h" -#include "tests/validation_old/Validation.h" -#include "tests/validation_old/dataset/BatchNormalizationLayerDataset.h" - -#include "arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h" - -#include - -using namespace arm_compute; -using namespace arm_compute::test; -using namespace arm_compute::test::validation; - -namespace -{ -const float tolerance_qs8 = 6; /**< Tolerance value for comparing reference's output against quantized implementation's output */ -const float tolerance_qs16 = 6; /**< Tolerance value for comparing reference's output against quantized implementation's output */ -const float tolerance_f32 = 1e-05f; /**< Tolerance value for comparing reference's output against floating point implementation's output */ -#ifdef ARM_COMPUTE_ENABLE_FP16 -const float tolerance_f16 = 0.01f; /**< Tolerance value for comparing reference's output against half precision floating point implementation's output */ -#endif /* ARM_COMPUTE_ENABLE_FP16 */ - -/** Compute Neon batch normalization function. - * - * @param[in] shape Shape of the input and output tensors. - * @param[in] dt Data type of input and output tensors. - * @param[in] norm_info Normalization Layer information. - * - * @return Computed output tensor. - */ -Tensor compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position = 0) -{ - // Create tensors - Tensor src = create_tensor(shape0, dt, 1, fixed_point_position); - Tensor dst = create_tensor(shape0, dt, 1, fixed_point_position); - Tensor mean = create_tensor(shape1, dt, 1, fixed_point_position); - Tensor var = create_tensor(shape1, dt, 1, fixed_point_position); - Tensor beta = create_tensor(shape1, dt, 1, fixed_point_position); - Tensor gamma = create_tensor(shape1, dt, 1, fixed_point_position); - - // Create and configure function - NEBatchNormalizationLayer norm; - norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon); - - // Allocate tensors - src.allocator()->allocate(); - dst.allocator()->allocate(); - mean.allocator()->allocate(); - var.allocator()->allocate(); - beta.allocator()->allocate(); - gamma.allocator()->allocate(); - - BOOST_TEST(!src.info()->is_resizable()); - BOOST_TEST(!dst.info()->is_resizable()); - BOOST_TEST(!mean.info()->is_resizable()); - BOOST_TEST(!var.info()->is_resizable()); - BOOST_TEST(!beta.info()->is_resizable()); - BOOST_TEST(!gamma.info()->is_resizable()); - - // Fill tensors - switch(dt) - { - case DataType::QS8: - { - const std::pair bounds = get_batchnormalization_layer_test_bounds(fixed_point_position); - std::uniform_int_distribution<> distribution(bounds.first, bounds.second); - std::uniform_int_distribution<> distribution_var(0, bounds.second); - test::fill_tensors(distribution, { 0, 1, 3, 4 }, &src, &mean, &beta, &gamma); - test::fill_tensors(distribution_var, { 0 }, &var); - break; - } - case DataType::QS16: - { - const std::pair bounds = get_batchnormalization_layer_test_bounds(fixed_point_position); - std::uniform_int_distribution<> distribution(bounds.first, bounds.second); - std::uniform_int_distribution<> distribution_var(0, bounds.second); - test::fill_tensors(distribution, { 0, 1, 3, 4 }, &src, &mean, &beta, &gamma); - test::fill_tensors(distribution_var, { 0 }, &var); - break; - } -#ifdef ARM_COMPUTE_ENABLE_FP16 - case DataType::F16: - { - const std::pair bounds = get_batchnormalization_layer_test_bounds(); - std::uniform_real_distribution<> distribution(bounds.first, bounds.second); - std::uniform_real_distribution<> distribution_var(0, bounds.second); - test::fill_tensors(distribution, { 0, 1, 3, 4 }, &src, &mean, &beta, &gamma); - test::fill_tensors(distribution_var, { 0 }, &var); - break; - } -#endif /* ARM_COMPUTE_ENABLE_FP16 */ - case DataType::F32: - { - const std::pair bounds = get_batchnormalization_layer_test_bounds(); - std::uniform_real_distribution<> distribution(bounds.first, bounds.second); - std::uniform_real_distribution<> distribution_var(0, bounds.second); - test::fill_tensors(distribution, { 0, 1, 3, 4 }, &src, &mean, &beta, &gamma); - test::fill_tensors(distribution_var, { 0 }, &var); - break; - } - default: - { - ARM_COMPUTE_ERROR("Not supported"); - break; - } - } - - // Compute function - norm.run(); - - return dst; -} -} // namespace - -#ifndef DOXYGEN_SKIP_THIS -BOOST_AUTO_TEST_SUITE(NEON) -BOOST_AUTO_TEST_SUITE(BatchNormalizationLayer) - -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly")) -BOOST_DATA_TEST_CASE(Configuration, RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make({ DataType::QS8, DataType::QS16, DataType::F32 }), obj, dt) -{ - // Set fixed point position data type allowed - int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0; - - // Create tensors - Tensor src = create_tensor(obj.shape0, dt, 1, fixed_point_position); - Tensor dst = create_tensor(obj.shape0, dt, 1, fixed_point_position); - Tensor mean = create_tensor(obj.shape1, dt, 1, fixed_point_position); - Tensor var = create_tensor(obj.shape1, dt, 1, fixed_point_position); - Tensor beta = create_tensor(obj.shape1, dt, 1, fixed_point_position); - Tensor gamma = create_tensor(obj.shape1, dt, 1, fixed_point_position); - - BOOST_TEST(src.info()->is_resizable()); - BOOST_TEST(dst.info()->is_resizable()); - BOOST_TEST(mean.info()->is_resizable()); - BOOST_TEST(var.info()->is_resizable()); - BOOST_TEST(beta.info()->is_resizable()); - BOOST_TEST(gamma.info()->is_resizable()); - - // Create and configure function - NEBatchNormalizationLayer norm; - norm.configure(&src, &dst, &mean, &var, &beta, &gamma, obj.epsilon); - - // Validate valid region - const ValidRegion valid_region = shape_to_valid_region(obj.shape0); - const ValidRegion valid_region_vec = shape_to_valid_region(obj.shape1); - validate(src.info()->valid_region(), valid_region); - validate(dst.info()->valid_region(), valid_region); - validate(mean.info()->valid_region(), valid_region_vec); - validate(var.info()->valid_region(), valid_region_vec); - validate(beta.info()->valid_region(), valid_region_vec); - validate(gamma.info()->valid_region(), valid_region_vec); -} - -BOOST_AUTO_TEST_SUITE(Float) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(Random, - RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make(DataType::F32), - obj, dt) -{ - // Compute function - Tensor dst = compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon); - - // Validate output - validate(Accessor(dst), ref_dst, tolerance_f32, 0); -} -BOOST_AUTO_TEST_SUITE_END() - -#ifdef ARM_COMPUTE_ENABLE_FP16 -BOOST_AUTO_TEST_SUITE(Float16) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(Random, - RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make(DataType::F16), - obj, dt) -{ - // Compute function - Tensor dst = compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon); - - // Validate output - validate(Accessor(dst), ref_dst, tolerance_f16, 0); -} -BOOST_AUTO_TEST_SUITE_END() -#endif /* ARM_COMPUTE_ENABLE_FP16 */ - -BOOST_AUTO_TEST_SUITE(Quantized) -BOOST_AUTO_TEST_SUITE(QS8) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(Random, - RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make(DataType::QS8) * boost::unit_test::data::xrange(1, 6), - obj, dt, fixed_point_position) -{ - // Compute function - Tensor dst = compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon, fixed_point_position); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon, fixed_point_position); - - // Validate output - validate(Accessor(dst), ref_dst, tolerance_qs8); -} -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE(QS16) -BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit")) -BOOST_DATA_TEST_CASE(Random, - RandomBatchNormalizationLayerDataset() * boost::unit_test::data::make(DataType::QS16) * boost::unit_test::data::xrange(1, 14), - obj, dt, fixed_point_position) -{ - // Compute function - Tensor dst = compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon, fixed_point_position); - - // Compute reference - RawTensor ref_dst = Reference::compute_reference_batch_normalization_layer(obj.shape0, obj.shape1, dt, obj.epsilon, fixed_point_position); - - // Validate output - validate(Accessor(dst), ref_dst, tolerance_qs16); -} -BOOST_AUTO_TEST_SUITE_END() -BOOST_AUTO_TEST_SUITE_END() - -BOOST_AUTO_TEST_SUITE_END() -BOOST_AUTO_TEST_SUITE_END() -#endif /* DOXYGEN_SKIP_THIS */ diff --git a/tests/validation_old/Reference.cpp b/tests/validation_old/Reference.cpp index 6a52cd016f..fc5484606e 100644 --- a/tests/validation_old/Reference.cpp +++ b/tests/validation_old/Reference.cpp @@ -284,68 +284,6 @@ RawTensor Reference::compute_reference_warp_perspective(const TensorShape &shape return ref_dst; } -RawTensor Reference::compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position) -{ - // Create reference - RawTensor ref_src(shape0, dt, 1, fixed_point_position); - RawTensor ref_dst(shape0, dt, 1, fixed_point_position); - RawTensor ref_mean(shape1, dt, 1, fixed_point_position); - RawTensor ref_var(shape1, dt, 1, fixed_point_position); - RawTensor ref_beta(shape1, dt, 1, fixed_point_position); - RawTensor ref_gamma(shape1, dt, 1, fixed_point_position); - - // Fill tensors - switch(dt) - { - case DataType::QS8: - { - const std::pair bounds = get_batchnormalization_layer_test_bounds(fixed_point_position); - std::uniform_int_distribution<> distribution(bounds.first, bounds.second); - std::uniform_int_distribution<> distribution_var(0, bounds.second); - fill_tensors(distribution, { 0, 1, 3, 4 }, &ref_src, &ref_mean, &ref_beta, &ref_gamma); - fill_tensors(distribution_var, { 0 }, &ref_var); - break; - } - case DataType::QS16: - { - const std::pair bounds = get_batchnormalization_layer_test_bounds(fixed_point_position); - std::uniform_int_distribution<> distribution(bounds.first, bounds.second); - std::uniform_int_distribution<> distribution_var(0, bounds.second); - fill_tensors(distribution, { 0, 1, 3, 4 }, &ref_src, &ref_mean, &ref_beta, &ref_gamma); - fill_tensors(distribution_var, { 0 }, &ref_var); - break; - } - case DataType::F16: - { - const std::pair bounds = get_batchnormalization_layer_test_bounds(); - std::uniform_real_distribution<> distribution(bounds.first, bounds.second); - std::uniform_real_distribution<> distribution_var(0, bounds.second); - fill_tensors(distribution, { 0, 1, 3, 4 }, &ref_src, &ref_mean, &ref_beta, &ref_gamma); - fill_tensors(distribution_var, { 0 }, &ref_var); - break; - } - case DataType::F32: - { - const std::pair bounds = get_batchnormalization_layer_test_bounds(); - std::uniform_real_distribution<> distribution(bounds.first, bounds.second); - std::uniform_real_distribution<> distribution_var(0, bounds.second); - fill_tensors(distribution, { 0, 1, 3, 4 }, &ref_src, &ref_mean, &ref_beta, &ref_gamma); - fill_tensors(distribution_var, { 0 }, &ref_var); - break; - } - default: - { - ARM_COMPUTE_ERROR("Not supported"); - break; - } - } - - // Compute reference - ReferenceCPP::batch_normalization_layer(ref_src, ref_dst, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, fixed_point_position); - - return ref_dst; -} - RawTensor Reference::compute_reference_roi_pooling_layer(const TensorShape &shape, DataType dt, const std::vector &rois, const ROIPoolingLayerInfo &pool_info) { TensorShape shape_dst; diff --git a/tests/validation_old/Reference.h b/tests/validation_old/Reference.h index 9c7baacbf6..e363bb2ecd 100644 --- a/tests/validation_old/Reference.h +++ b/tests/validation_old/Reference.h @@ -204,17 +204,6 @@ public: static RawTensor compute_reference_warp_perspective(const TensorShape &shape, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value); - /** Compute reference batch normalization layer. - * - * @param[in] shape0 Shape of the input and output tensors. - * @param[in] shape1 Shape of the vector tensors. - * @param[in] dt Data type of all input and output tensors. - * @param[in] epsilon Small value to avoid division with zero. - * @param[in] fixed_point_position Fixed point position. - * - * @return Computed raw tensor. - */ - static RawTensor compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position = 0); /** Compute reference roi pooling layer. * * @param[in] shape Shape of the input tensor. diff --git a/tests/validation_old/ReferenceCPP.cpp b/tests/validation_old/ReferenceCPP.cpp index 86dc589bb1..eae892af26 100644 --- a/tests/validation_old/ReferenceCPP.cpp +++ b/tests/validation_old/ReferenceCPP.cpp @@ -212,19 +212,6 @@ void ReferenceCPP::warp_perspective(const RawTensor &src, RawTensor &dst, RawTen tensor_operations::warp_perspective(s, d, vmask, matrix, policy, border_mode, constant_border_value); } -// Batch Normalization Layer -void ReferenceCPP::batch_normalization_layer(const RawTensor &src, RawTensor &dst, const RawTensor &mean, const RawTensor &var, const RawTensor &beta, const RawTensor &gamma, float epsilon, - int fixed_point_position) -{ - const TensorVariant s = TensorFactory::get_tensor(src); - TensorVariant d = TensorFactory::get_tensor(dst); - const TensorVariant m = TensorFactory::get_tensor(mean); - const TensorVariant v = TensorFactory::get_tensor(var); - const TensorVariant b = TensorFactory::get_tensor(beta); - const TensorVariant g = TensorFactory::get_tensor(gamma); - boost::apply_visitor(tensor_visitors::batch_normalization_layer_visitor(s, m, v, b, g, epsilon, fixed_point_position), d); -} - // ROI Pooling Layer void ReferenceCPP::roi_pooling_layer(const RawTensor &src, RawTensor &dst, const std::vector &rois, const ROIPoolingLayerInfo &pool_info) { diff --git a/tests/validation_old/ReferenceCPP.h b/tests/validation_old/ReferenceCPP.h index 5bc10a512f..2f02afc30e 100644 --- a/tests/validation_old/ReferenceCPP.h +++ b/tests/validation_old/ReferenceCPP.h @@ -198,20 +198,6 @@ public: * @param[in] constant_border_value Constant value to use for borders if border_mode is set to CONSTANT. */ static void warp_perspective(const RawTensor &src, RawTensor &dst, RawTensor &valid_mask, const float *matrix, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value); - - /** Batch Normalization of @p src based on the information from @p norm_info. - * - * @param[in] src Input tensor. - * @param[out] dst Result tensor. - * @param[out] mean Mean vector tensor. - * @param[out] var Var vector tensor. - * @param[out] beta Beta vector tensor. - * @param[out] gamma Gamma vector tensor. - * @param[in] epsilon Small value to avoid division with zero. - * @param[in] fixed_point_position Fixed point position. - */ - static void batch_normalization_layer(const RawTensor &src, RawTensor &dst, const RawTensor &mean, const RawTensor &var, const RawTensor &beta, const RawTensor &gamma, float epsilon, - int fixed_point_position = 0); /** ROI Pooling layer of @p src based on the information from @p pool_info and @p rois. * * @param[in] src Input tensor. diff --git a/tests/validation_old/TensorOperations.h b/tests/validation_old/TensorOperations.h index 0c1ab4134e..04a79f0de3 100644 --- a/tests/validation_old/TensorOperations.h +++ b/tests/validation_old/TensorOperations.h @@ -861,70 +861,6 @@ void warp_perspective(const Tensor &in, Tensor &out, Tensor &valid_mask } } -// Batch Normalization Layer for fixed point type -template ::value, int>::type * = nullptr> -void batch_normalization_layer(const Tensor &in, Tensor &out, const Tensor &mean, const Tensor &var, const Tensor &beta, const Tensor &gamma, float epsilon, int fixed_point_position) -{ - const int cols = static_cast(in.shape()[0]); - const int rows = static_cast(in.shape()[1]); - const int depth = static_cast(in.shape()[2]); - int upper_dims = in.shape().total_size() / (cols * rows * depth); - - for(int r = 0; r < upper_dims; ++r) - { - for(int i = 0; i < depth; ++i) - { - for(int k = 0; k < rows; ++k) - { - for(int l = 0; l < cols; ++l) - { - const int pos = l + k * cols + i * rows * cols + r * cols * rows * depth; - fixed_point_arithmetic::fixed_point in_qs(in[pos], fixed_point_position, true); - fixed_point_arithmetic::fixed_point var_qs(var[i], fixed_point_position, true); - fixed_point_arithmetic::fixed_point mean_qs(mean[i], fixed_point_position, true); - fixed_point_arithmetic::fixed_point beta_qs(beta[i], fixed_point_position, true); - fixed_point_arithmetic::fixed_point gamma_qs(gamma[i], fixed_point_position, true); - fixed_point_arithmetic::fixed_point epsilon_qs(epsilon, fixed_point_position); - - auto denominator = fixed_point_arithmetic::inv_sqrt(var_qs + epsilon_qs); - auto numerator = in_qs - mean_qs; - auto x_bar = numerator * denominator; - x_bar = beta_qs + x_bar * gamma_qs; - out[pos] = x_bar.raw(); - } - } - } - } -} - -// Batch Normalization Layer for floating point type -template ::value, int>::type * = nullptr> -void batch_normalization_layer(const Tensor &in, Tensor &out, const Tensor &mean, const Tensor &var, const Tensor &beta, const Tensor &gamma, float epsilon, int fixed_point_position) -{ - const int cols = static_cast(in.shape()[0]); - const int rows = static_cast(in.shape()[1]); - const int depth = static_cast(in.shape()[2]); - int upper_dims = in.shape().total_size() / (cols * rows * depth); - - for(int r = 0; r < upper_dims; ++r) - { - for(int i = 0; i < depth; ++i) - { - for(int k = 0; k < rows; ++k) - { - for(int l = 0; l < cols; ++l) - { - const int pos = l + k * cols + i * rows * cols + r * cols * rows * depth; - const float denominator = sqrt(var[i] + epsilon); - const float numerator = in[pos] - mean[i]; - const float x_bar = numerator / denominator; - out[pos] = beta[i] + x_bar * gamma[i]; - } - } - } - } -} - // ROI Pooling layer template void roi_pooling_layer(const Tensor &in, Tensor &out, const std::vector &rois, const ROIPoolingLayerInfo &pool_info) diff --git a/tests/validation_old/TensorVisitors.h b/tests/validation_old/TensorVisitors.h index dafbfe0235..8af035be08 100644 --- a/tests/validation_old/TensorVisitors.h +++ b/tests/validation_old/TensorVisitors.h @@ -128,33 +128,6 @@ private: RoundingPolicy _rounding_policy; }; -// Batch Normalization Layer visitor -struct batch_normalization_layer_visitor : public boost::static_visitor<> -{ -public: - explicit batch_normalization_layer_visitor(const TensorVariant &in, const TensorVariant &mean, const TensorVariant &var, const TensorVariant &beta, const TensorVariant &gamma, float epsilon, - int fixed_point_position = 0) - : _in(in), _mean(mean), _var(var), _beta(beta), _gamma(gamma), _epsilon(epsilon), _fixed_point_position(fixed_point_position) - { - } - - template - void operator()(Tensor &out) const - { - const Tensor &in = boost::get>(_in); - const Tensor &mean = boost::get>(_mean); - const Tensor &var = boost::get>(_var); - const Tensor &beta = boost::get>(_beta); - const Tensor &gamma = boost::get>(_gamma); - tensor_operations::batch_normalization_layer(in, out, mean, var, beta, gamma, _epsilon, _fixed_point_position); - } - -private: - const TensorVariant &_in, &_mean, &_var, &_beta, &_gamma; - float _epsilon; - int _fixed_point_position; -}; - // ROI Pooling layer struct roi_pooling_layer_visitor : public boost::static_visitor<> { -- cgit v1.2.1