From 92fd94336e4b169005d88af401fe57bcbd50521b Mon Sep 17 00:00:00 2001 From: giuros01 Date: Mon, 3 Dec 2018 17:30:00 +0000 Subject: COMPMID-1754: NEON: Implement Maximum, Minumum, SquaredDifference Change-Id: I77e8c6a8af6ad841293ed5e66ed582035cc1424b Reviewed-on: https://review.mlplatform.org/339 Reviewed-by: Michalis Spyrou Tested-by: Arm Jenkins Reviewed-by: Gian Marco Iodice Reviewed-by: Georgios Pinitas --- tests/validation/NEON/ElementwiseMax.cpp | 264 ++++++++++++++++++++ tests/validation/NEON/ElementwiseMin.cpp | 265 ++++++++++++++++++++ tests/validation/NEON/ElementwiseSquareDiff.cpp | 268 +++++++++++++++++++++ .../fixtures/ElementwiseOperationsFixture.h | 45 ++++ .../validation/reference/ElementwiseOperations.cpp | 4 + 5 files changed, 846 insertions(+) create mode 100644 tests/validation/NEON/ElementwiseMax.cpp create mode 100644 tests/validation/NEON/ElementwiseMin.cpp create mode 100644 tests/validation/NEON/ElementwiseSquareDiff.cpp (limited to 'tests') diff --git a/tests/validation/NEON/ElementwiseMax.cpp b/tests/validation/NEON/ElementwiseMax.cpp new file mode 100644 index 0000000000..c77f485d29 --- /dev/null +++ b/tests/validation/NEON/ElementwiseMax.cpp @@ -0,0 +1,264 @@ +/* + * Copyright (c) 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 CONCLCTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/NEON/functions/NEElementwiseOperations.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" +#include "tests/NEON/Accessor.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/ElementwiseOperationsFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +RelativeTolerance tolerance_fp32(0.000001f); +/** Input data sets **/ +const auto ElementwiseMaxQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataType", + DataType::QASYMM8)); +/** Input data sets **/ +const auto ElementwiseMaxS32Dataset = combine(combine(framework::dataset::make("DataType", DataType::S32), framework::dataset::make("DataType", DataType::S32)), framework::dataset::make("DataType", + DataType::S32)); +const auto ElementwiseMaxS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), + framework::dataset::make("DataType", DataType::S16)); +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +const auto ElementwiseMaxFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataType", DataType::F16)); +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +const auto ElementwiseMaxFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("DataType", DataType::F32)); +} // namespace + +TEST_SUITE(NEON) +TEST_SUITE(ElementwiseMax) + +template +using NEElementwiseMaxFixture = ElementwiseMaxValidationFixture; + +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), // Invalid data type combination + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, true, false, false})), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(NEElementwiseMax::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + +TEST_SUITE(S32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::S32); + Tensor ref_src2 = create_tensor(shape, DataType::S32); + Tensor dst = create_tensor(shape, DataType::S32); + + // Create and Configure function + NEElementwiseMax add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxS32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // S32 + +TEST_SUITE(S16) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::S16 })), + shape, data_type) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, data_type); + Tensor ref_src2 = create_tensor(shape, DataType::S16); + Tensor dst = create_tensor(shape, DataType::S16); + + // Create and Configure function + NEElementwiseMax add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxS16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseMaxFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMaxS16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // S16 + +template +using NEElementwiseMaxQuantizedFixture = ElementwiseMaxValidationQuantizedFixture; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::QASYMM8); + Tensor ref_src2 = create_tensor(shape, DataType::QASYMM8); + Tensor dst = create_tensor(shape, DataType::QASYMM8); + + // Create and Configure function + NEElementwiseMin add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), + ElementwiseMaxQASYMM8Dataset), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) }))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32, 0.01); +} + +template +using NEElementwiseMaxQuantizedBroadcastFixture = ElementwiseMaxQuantizedBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseMaxQuantizedBroadcastFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapesBroadcast(), + ElementwiseMaxQASYMM8Dataset), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE(Float) +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +TEST_SUITE(F16) +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseMaxFP16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // F16 +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + +TEST_SUITE(F32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::F32); + Tensor ref_src2 = create_tensor(shape, DataType::F32); + Tensor dst = create_tensor(shape, DataType::F32); + + // Create and Configure function + NEElementwiseMax add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMaxFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseMaxFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMaxFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +template +using NEElementwiseMaxBroadcastFixture = ElementwiseMaxBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseMaxBroadcastFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(), + ElementwiseMaxFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, NEElementwiseMaxBroadcastFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(), + ElementwiseMaxFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // F32 +TEST_SUITE_END() // Float + +TEST_SUITE_END() // ElementwiseMax +TEST_SUITE_END() // NEON +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/NEON/ElementwiseMin.cpp b/tests/validation/NEON/ElementwiseMin.cpp new file mode 100644 index 0000000000..a7ce2d61b0 --- /dev/null +++ b/tests/validation/NEON/ElementwiseMin.cpp @@ -0,0 +1,265 @@ +/* + * Copyright (c) 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 CONCLCTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/NEON/functions/NEElementwiseOperations.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" +#include "tests/NEON/Accessor.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/ElementwiseOperationsFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +RelativeTolerance tolerance_fp32(0.000001f); +/** Input data sets **/ +const auto ElementwiseMinQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataType", + DataType::QASYMM8)); +const auto ElementwiseMinS32Dataset = combine(combine(framework::dataset::make("DataType", DataType::S32), framework::dataset::make("DataType", DataType::S32)), framework::dataset::make("DataType", + DataType::S32)); +const auto ElementwiseMinS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), + framework::dataset::make("DataType", DataType::S16)); +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +const auto ElementwiseMinFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataType", DataType::F16)); +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +const auto ElementwiseMinFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("DataType", DataType::F32)); +} // namespace + +TEST_SUITE(NEON) +TEST_SUITE(ElementwiseMin) + +template +using NEElementwiseMinFixture = ElementwiseMinValidationFixture; + +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), // Invalid data type combination + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, true, false, false})), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(NEElementwiseMin::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + +TEST_SUITE(S32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::S32); + Tensor ref_src2 = create_tensor(shape, DataType::S32); + Tensor dst = create_tensor(shape, DataType::S32); + + // Create and Configure function + NEElementwiseMin add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMinFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMinS32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // S32 + +TEST_SUITE(S16) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::S16 })), + shape, data_type) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, data_type); + Tensor ref_src2 = create_tensor(shape, DataType::S16); + Tensor dst = create_tensor(shape, DataType::S16); + + // Create and Configure function + NEElementwiseMin add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMinFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMinS16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseMinFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMinS16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // S16 + +template +using NEElementwiseMinQuantizedFixture = ElementwiseMinValidationQuantizedFixture; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::QASYMM8); + Tensor ref_src2 = create_tensor(shape, DataType::QASYMM8); + Tensor dst = create_tensor(shape, DataType::QASYMM8); + + // Create and Configure function + NEElementwiseMin add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +template +using NEElementwiseMinQuantizedBroadcastFixture = ElementwiseMinQuantizedBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseMinQuantizedBroadcastFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapesBroadcast(), + ElementwiseMinQASYMM8Dataset), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMinQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), + ElementwiseMinQASYMM8Dataset), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) })) + + ) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32, 0.01); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE(Float) +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +TEST_SUITE(F16) +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMinFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseMinFP16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // F16 +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + +TEST_SUITE(F32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::F32); + Tensor ref_src2 = create_tensor(shape, DataType::F32); + Tensor dst = create_tensor(shape, DataType::F32); + + // Create and Configure function + NEElementwiseMin add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseMinFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMinFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseMinFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMinFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +template +using NEElementwiseMinBroadcastFixture = ElementwiseMinBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseMinBroadcastFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(), + ElementwiseMinFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, NEElementwiseMinBroadcastFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(), + ElementwiseMinFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // F32 +TEST_SUITE_END() // Float + +TEST_SUITE_END() // ElementwiseMin +TEST_SUITE_END() // NEON +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/NEON/ElementwiseSquareDiff.cpp b/tests/validation/NEON/ElementwiseSquareDiff.cpp new file mode 100644 index 0000000000..0c3fab609e --- /dev/null +++ b/tests/validation/NEON/ElementwiseSquareDiff.cpp @@ -0,0 +1,268 @@ +/* + * Copyright (c) 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 CONCLCTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/NEON/functions/NEElementwiseOperations.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" +#include "tests/NEON/Accessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/ElementwiseOperationsFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +RelativeTolerance tolerance_fp32(0.000001f); +/** Input data sets **/ +const auto ElementwiseSquaredDiffQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataType", + DataType::QASYMM8)); +/** Input data sets **/ +const auto ElementwiseSquaredDiffS32Dataset = combine(combine(framework::dataset::make("DataType", DataType::S32), framework::dataset::make("DataType", DataType::S32)), + framework::dataset::make("DataType", + DataType::S32)); +const auto ElementwiseSquaredDiffS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), + framework::dataset::make("DataType", DataType::S16)); +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +const auto ElementwiseSquaredDiffFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataType", DataType::F16)); +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +const auto ElementwiseSquaredDiffFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("DataType", DataType::F32)); +} // namespace + +TEST_SUITE(NEON) +TEST_SUITE(ElementwiseSquaredDiff) + +template +using NEElementwiseSquaredDiffFixture = ElementwiseSquaredDiffValidationFixture; + +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), // Invalid data type combination + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, true, false, false})), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(NEElementwiseSquaredDiff::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + +TEST_SUITE(S32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::S32); + Tensor ref_src2 = create_tensor(shape, DataType::S32); + Tensor dst = create_tensor(shape, DataType::S32); + + // Create and Configure function + NEElementwiseSquaredDiff add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseSquaredDiffFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseSquaredDiffS32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // S32 + +TEST_SUITE(S16) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::S16 })), + shape, data_type) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, data_type); + Tensor ref_src2 = create_tensor(shape, DataType::S16); + Tensor dst = create_tensor(shape, DataType::S16); + + // Create and Configure function + NEElementwiseSquaredDiff add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseSquaredDiffFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseSquaredDiffS16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseSquaredDiffFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseSquaredDiffS16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // S16 + +template +using NEElementwiseSquaredDiffQuantizedFixture = ElementwiseSquaredDiffValidationQuantizedFixture; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::QASYMM8); + Tensor ref_src2 = create_tensor(shape, DataType::QASYMM8); + Tensor dst = create_tensor(shape, DataType::QASYMM8); + + // Create and Configure function + NEElementwiseMin add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseSquaredDiffQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), + ElementwiseSquaredDiffQASYMM8Dataset), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) })) + + ) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32, 0.01); +} +template +using NEElementwiseSquaredDiffQuantizedBroadcastFixture = ElementwiseSquaredDiffQuantizedBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseSquaredDiffQuantizedBroadcastFixture, framework::DatasetMode::PRECOMMIT, + combine(combine(combine(combine(datasets::SmallShapesBroadcast(), + ElementwiseSquaredDiffQASYMM8Dataset), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(1.f / 255.f, 5) }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE(Float) +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +TEST_SUITE(F16) +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseSquaredDiffFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseSquaredDiffFP16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // F16 +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + +TEST_SUITE(F32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::F32); + Tensor ref_src2 = create_tensor(shape, DataType::F32); + Tensor dst = create_tensor(shape, DataType::F32); + + // Create and Configure function + NEElementwiseSquaredDiff add; + add.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwiseSquaredDiffFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseSquaredDiffFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwiseSquaredDiffFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseSquaredDiffFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +template +using NEElementwiseSquaredDiffBroadcastFixture = ElementwiseSquaredDiffBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwiseSquaredDiffBroadcastFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(), + ElementwiseSquaredDiffFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, NEElementwiseSquaredDiffBroadcastFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(), + ElementwiseSquaredDiffFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // F32 +TEST_SUITE_END() // Float + +TEST_SUITE_END() // ElementwiseSquaredDiff +TEST_SUITE_END() // NEON +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/fixtures/ElementwiseOperationsFixture.h b/tests/validation/fixtures/ElementwiseOperationsFixture.h index b051c858c2..8190b2405a 100644 --- a/tests/validation/fixtures/ElementwiseOperationsFixture.h +++ b/tests/validation/fixtures/ElementwiseOperationsFixture.h @@ -199,6 +199,21 @@ public: } }; +template +class ElementwiseMaxQuantizedBroadcastValidationFixture : public ArithmeticOperationsGenericFixture +{ +public: + template + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationsGenericFixture::setup(ArithmeticOperation::MAX, shape0, shape1, + data_type0, data_type1, output_data_type, + qinfo0, qinfo1, qinfo_out); + } +}; + template class ElementwiseMinBroadcastValidationFixture : public ArithmeticOperationsGenericFixture { @@ -240,6 +255,21 @@ public: } }; +template +class ElementwiseMinQuantizedBroadcastValidationFixture : public ArithmeticOperationsGenericFixture +{ +public: + template + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationsGenericFixture::setup(ArithmeticOperation::MIN, shape0, shape1, + data_type0, data_type1, output_data_type, + qinfo0, qinfo1, qinfo_out); + } +}; + template class ElementwiseSquaredDiffBroadcastValidationFixture : public ArithmeticOperationsGenericFixture { @@ -280,6 +310,21 @@ public: qinfo0, qinfo1, qinfo_out); } }; + +template +class ElementwiseSquaredDiffQuantizedBroadcastValidationFixture : public ArithmeticOperationsGenericFixture +{ +public: + template + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationsGenericFixture::setup(ArithmeticOperation::SQUARED_DIFF, shape0, shape1, + data_type0, data_type1, output_data_type, + qinfo0, qinfo1, qinfo_out); + } +}; } // namespace validation } // namespace test } // namespace arm_compute diff --git a/tests/validation/reference/ElementwiseOperations.cpp b/tests/validation/reference/ElementwiseOperations.cpp index fe0467fe5e..1f0d42b26e 100644 --- a/tests/validation/reference/ElementwiseOperations.cpp +++ b/tests/validation/reference/ElementwiseOperations.cpp @@ -158,6 +158,8 @@ SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleT } } +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, + ConvertPolicy convert_policy); template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, ConvertPolicy convert_policy); template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, SimpleTensor &dst, @@ -175,6 +177,8 @@ SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor< return dst; } +template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, + ConvertPolicy convert_policy); template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); template SimpleTensor arithmetic_operation(ArithmeticOperation op, const SimpleTensor &src1, const SimpleTensor &src2, DataType dst_data_type, ConvertPolicy convert_policy); -- cgit v1.2.1