diff options
author | giuros01 <giuseppe.rossini@arm.com> | 2018-11-20 18:34:46 +0000 |
---|---|---|
committer | Giuseppe Rossini <giuseppe.rossini@arm.com> | 2018-11-30 18:00:25 +0000 |
commit | 164a2727d3bbce0e575d24b7db787c85e2e2c203 (patch) | |
tree | 983fc1f519032ac9a056e19f87e32597ca1874a1 /tests/validation/CL | |
parent | 7930db48e12dd3a14c1971f41f5b83527efea281 (diff) | |
download | ComputeLibrary-164a2727d3bbce0e575d24b7db787c85e2e2c203.tar.gz |
COMPMID-1717: CL: Implement Maximum, Minimum, SquaredDifference
Change-Id: Ice653e48211053bd3cd20a693bd76de6b4efc370
Reviewed-on: https://review.mlplatform.org/270
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests/validation/CL')
-rw-r--r-- | tests/validation/CL/ArithmeticAddition.cpp | 4 | ||||
-rw-r--r-- | tests/validation/CL/ArithmeticDivision.cpp | 169 | ||||
-rw-r--r-- | tests/validation/CL/ArithmeticSubtraction.cpp | 83 | ||||
-rw-r--r-- | tests/validation/CL/ElementwiseMax.cpp | 277 | ||||
-rw-r--r-- | tests/validation/CL/ElementwiseMin.cpp | 277 | ||||
-rw-r--r-- | tests/validation/CL/ElementwiseSquaredDiff.cpp | 278 |
6 files changed, 1023 insertions, 65 deletions
diff --git a/tests/validation/CL/ArithmeticAddition.cpp b/tests/validation/CL/ArithmeticAddition.cpp index 09f1b7c5a9..6f7aa94521 100644 --- a/tests/validation/CL/ArithmeticAddition.cpp +++ b/tests/validation/CL/ArithmeticAddition.cpp @@ -24,7 +24,7 @@ #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/CLArithmeticAddition.h" +#include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/ConvertPolicyDataset.h" @@ -43,7 +43,7 @@ namespace validation { namespace { -constexpr unsigned int num_elems_processed_per_iteration = 8; +constexpr unsigned int num_elems_processed_per_iteration = 16; /** Input data sets **/ const auto ArithmeticAdditionU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), framework::dataset::make("DataType", DataType::U8)); diff --git a/tests/validation/CL/ArithmeticDivision.cpp b/tests/validation/CL/ArithmeticDivision.cpp index 5d4fa1fd5e..87039d775f 100644 --- a/tests/validation/CL/ArithmeticDivision.cpp +++ b/tests/validation/CL/ArithmeticDivision.cpp @@ -24,7 +24,7 @@ #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/CLArithmeticDivision.h" +#include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/ConvertPolicyDataset.h" @@ -33,7 +33,7 @@ #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" -#include "tests/validation/fixtures/ArithmeticDivisionFixture.h" +#include "tests/validation/fixtures/ElementwiseOperationsFixture.h" namespace arm_compute { @@ -45,6 +45,20 @@ namespace { RelativeTolerance<float> tolerance_fp32(0.000001f); RelativeTolerance<float> tolerance_fp16(0.001f); + +constexpr unsigned int num_elems_processed_per_iteration = 16; +/** Input data sets **/ +const auto ArithmeticDivisionU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), framework::dataset::make("DataType", + DataType::U8)); +const auto ArithmeticDivisionQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataType", + DataType::QASYMM8)); +const auto ArithmeticDivisionS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::U8, DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), + framework::dataset::make("DataType", DataType::S16)); +const auto ArithmeticDivisionFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataType", DataType::F16)); +const auto ArithmeticDivisionFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("DataType", DataType::F32)); } // namespace TEST_SUITE(CL) @@ -53,25 +67,25 @@ TEST_SUITE(ArithmeticDivision) // *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::U8), // Wrong data type + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // Invalid data type combination TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), }), framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S16), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), })), - framework::dataset::make("Expected", { false, false, false, false, true })), + framework::dataset::make("Expected", { true, true, false, false, false})), input1_info, input2_info, output_info, expected) { ARM_COMPUTE_EXPECT(bool(CLArithmeticDivision::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); @@ -82,17 +96,128 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( template <typename T> using CLArithmeticDivisionFixture = ArithmeticDivisionValidationFixture<CLTensor, CLAccessor, CLArithmeticDivision, T>; +TEST_SUITE(U8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::U8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::U8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8); + + // Create and Configure function + CLArithmeticDivision 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticDivisionFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ArithmeticDivisionU8Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() + +template <typename T> +using CLArithmeticDivisionQuantizedFixture = ArithmeticDivisionValidationQuantizedFixture<CLTensor, CLAccessor, CLArithmeticDivision, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::QASYMM8); + + // Create and Configure function + CLArithmeticDivision 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticDivisionQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), + ArithmeticDivisionQASYMM8Dataset), + 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(CLAccessor(_target), _reference, tolerance_fp32, 0.01); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE(S16) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), + shape, data_type) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, data_type); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::S16); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::S16); + + // Create and Configure function + CLArithmeticDivision 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticDivisionFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ArithmeticDivisionS16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLArithmeticDivisionFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ArithmeticDivisionS16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() + TEST_SUITE(Float) TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticDivisionFixture<half>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16))) +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticDivisionFixture<half>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ArithmeticDivisionFP16Dataset)) { // Validate output - validate(CLAccessor(_target), _reference, tolerance_fp16); + validate(CLAccessor(_target), _reference, tolerance_fp16, 0.01); } -TEST_SUITE_END() // FP16 +TEST_SUITE_END() TEST_SUITE(FP32) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, concat(datasets::SmallShapes(), datasets::LargeShapes()), shape) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) { // Create tensors CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::F32); @@ -100,27 +225,27 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, concat(datasets::Smal CLTensor dst = create_tensor<CLTensor>(shape, DataType::F32); // Create and Configure function - CLArithmeticDivision div; - div.configure(&ref_src1, &ref_src2, &dst); + CLArithmeticDivision 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); // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); validate(ref_src1.info()->padding(), padding); validate(ref_src2.info()->padding(), padding); validate(dst.info()->padding(), padding); } -FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticDivisionFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticDivisionFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ArithmeticDivisionFP32Dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp32); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLArithmeticDivisionFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(RunLarge, CLArithmeticDivisionFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ArithmeticDivisionFP32Dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp32); @@ -130,23 +255,23 @@ template <typename T> using CLArithmeticDivisionBroadcastFixture = ArithmeticDivisionBroadcastValidationFixture<CLTensor, CLAccessor, CLArithmeticDivision, T>; FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, CLArithmeticDivisionBroadcastFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(), - framework::dataset::make("DataType", DataType::F32))) + ArithmeticDivisionFP32Dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp32); } FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, CLArithmeticDivisionBroadcastFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(), - framework::dataset::make("DataType", DataType::F32))) + ArithmeticDivisionFP32Dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp32); } -TEST_SUITE_END() // FP32 -TEST_SUITE_END() // Float +TEST_SUITE_END() +TEST_SUITE_END() -TEST_SUITE_END() // ArithmeticDivision -TEST_SUITE_END() // CL +TEST_SUITE_END() +TEST_SUITE_END() } // namespace validation } // namespace test } // namespace arm_compute diff --git a/tests/validation/CL/ArithmeticSubtraction.cpp b/tests/validation/CL/ArithmeticSubtraction.cpp index cd13f42ec4..2cf410f373 100644 --- a/tests/validation/CL/ArithmeticSubtraction.cpp +++ b/tests/validation/CL/ArithmeticSubtraction.cpp @@ -24,7 +24,7 @@ #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/CLArithmeticSubtraction.h" +#include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/ConvertPolicyDataset.h" @@ -43,6 +43,7 @@ namespace validation { namespace { +constexpr unsigned int num_elems_processed_per_iteration = 16; /** Input data sets **/ const auto ArithmeticSubtractionU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), framework::dataset::make("DataType", @@ -64,26 +65,26 @@ TEST_SUITE(ArithmeticSubtraction) // *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::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // 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::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), - 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::S16), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), - TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), - })), - framework::dataset::make("Expected", { true, true, false, false, false})), - input1_info, input2_info, output_info, expected) + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // 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::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + 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::S16), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, false, false, false})), + input1_info, input2_info, output_info, expected) { ARM_COMPUTE_EXPECT(bool(CLArithmeticSubtraction::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), ConvertPolicy::WRAP)) == expected, framework::LogLevel::ERRORS); } @@ -103,15 +104,15 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8); // Create and Configure function - CLArithmeticSubtraction sub; - sub.configure(&ref_src1, &ref_src2, &dst, policy); + CLArithmeticSubtraction add; + add.configure(&ref_src1, &ref_src2, &dst, policy); // Validate valid region const ValidRegion valid_region = shape_to_valid_region(shape); validate(dst.info()->valid_region(), valid_region); // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); validate(ref_src1.info()->padding(), padding); validate(ref_src2.info()->padding(), padding); validate(dst.info()->padding(), padding); @@ -123,7 +124,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionFixture<uint8_t>, framew // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() // U8 +TEST_SUITE_END() template <typename T> using CLArithmeticSubtractionQuantizedFixture = ArithmeticSubtractionValidationQuantizedFixture<CLTensor, CLAccessor, CLArithmeticSubtraction, T>; @@ -147,7 +148,7 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da validate(dst.info()->valid_region(), valid_region); // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); validate(ref_src1.info()->padding(), padding); validate(ref_src2.info()->padding(), padding); validate(dst.info()->padding(), padding); @@ -165,8 +166,8 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionQuantizedFixture<uint8_t // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() // QASYMM8 -TEST_SUITE_END() // Quantized +TEST_SUITE_END() +TEST_SUITE_END() TEST_SUITE(S16) DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), @@ -179,15 +180,15 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(frame CLTensor dst = create_tensor<CLTensor>(shape, DataType::S16); // Create and Configure function - CLArithmeticSubtraction sub; - sub.configure(&ref_src1, &ref_src2, &dst, policy); + CLArithmeticSubtraction add; + add.configure(&ref_src1, &ref_src2, &dst, policy); // Validate valid region const ValidRegion valid_region = shape_to_valid_region(shape); validate(dst.info()->valid_region(), valid_region); // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); validate(ref_src1.info()->padding(), padding); validate(ref_src2.info()->padding(), padding); validate(dst.info()->padding(), padding); @@ -206,7 +207,7 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLArithmeticSubtractionFixture<int16_t>, framew // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() // S16 +TEST_SUITE_END() TEST_SUITE(Float) TEST_SUITE(FP16) @@ -216,7 +217,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLArithmeticSubtractionFixture<half>, framework // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() // FP16 +TEST_SUITE_END() TEST_SUITE(FP32) DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE, ConvertPolicy::WRAP })), @@ -228,15 +229,15 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da CLTensor dst = create_tensor<CLTensor>(shape, DataType::F32); // Create and Configure function - CLArithmeticSubtraction sub; - sub.configure(&ref_src1, &ref_src2, &dst, policy); + CLArithmeticSubtraction add; + add.configure(&ref_src1, &ref_src2, &dst, policy); // Validate valid region const ValidRegion valid_region = shape_to_valid_region(shape); validate(dst.info()->valid_region(), valid_region); // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding(); + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); validate(ref_src1.info()->padding(), padding); validate(ref_src2.info()->padding(), padding); validate(dst.info()->padding(), padding); @@ -274,11 +275,11 @@ FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, CLArithmeticSubtractionBroadcastFixtur // Validate output validate(CLAccessor(_target), _reference); } -TEST_SUITE_END() // FP32 -TEST_SUITE_END() // Float +TEST_SUITE_END() +TEST_SUITE_END() -TEST_SUITE_END() // ArithmeticSubtraction -TEST_SUITE_END() // CL +TEST_SUITE_END() +TEST_SUITE_END() } // namespace validation } // namespace test -} // namespace arm_compute
\ No newline at end of file +} // namespace arm_compute diff --git a/tests/validation/CL/ElementwiseMax.cpp b/tests/validation/CL/ElementwiseMax.cpp new file mode 100644 index 0000000000..894688fe2c --- /dev/null +++ b/tests/validation/CL/ElementwiseMax.cpp @@ -0,0 +1,277 @@ +/* + * 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 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/CLElementwiseOperations.h" +#include "tests/CL/CLAccessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/ConvertPolicyDataset.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<float> tolerance_fp32(0.000001f); +RelativeTolerance<float> tolerance_fp16(0.001f); + +constexpr unsigned int num_elems_processed_per_iteration = 16; +/** Input data sets **/ +const auto ElementwiseMaxU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), framework::dataset::make("DataType", + DataType::U8)); +const auto ElementwiseMaxQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataType", + DataType::QASYMM8)); +const auto ElementwiseMaxS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::U8, DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), + framework::dataset::make("DataType", DataType::S16)); +const auto ElementwiseMaxFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataType", DataType::F16)); +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(CL) +TEST_SUITE(ElementwiseMax) + +// *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::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // 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::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + 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::S16), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, false, false, false})), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(CLElementwiseMax::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* + +template <typename T> +using CLElementwiseMaxFixture = ElementwiseMaxValidationFixture<CLTensor, CLAccessor, CLElementwiseMax, T>; + +TEST_SUITE(U8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::U8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::U8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8); + + // Create and Configure function + CLElementwiseMax 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMaxFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxU8Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() + +template <typename T> +using CLElementwiseMaxQuantizedFixture = ElementwiseMaxValidationQuantizedFixture<CLTensor, CLAccessor, CLElementwiseMax, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::QASYMM8); + + // Create and Configure function + CLElementwiseMax 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMaxQuantizedFixture<uint8_t>, 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(CLAccessor(_target), _reference, tolerance_fp32, 0.01); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE(S16) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), + shape, data_type) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, data_type); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::S16); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::S16); + + // Create and Configure function + CLElementwiseMax 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMaxFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxS16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLElementwiseMaxFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMaxS16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() + +TEST_SUITE(Float) +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMaxFixture<half>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseMaxFP16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp16, 0.01); +} +TEST_SUITE_END() + +TEST_SUITE(FP32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::F32); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::F32); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::F32); + + // Create and Configure function + CLElementwiseMax 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMaxFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMaxFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLElementwiseMaxFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMaxFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +template <typename T> +using CLElementwiseMaxBroadcastFixture = ElementwiseMaxBroadcastValidationFixture<CLTensor, CLAccessor, CLElementwiseMax, T>; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, CLElementwiseMaxBroadcastFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(), + ElementwiseMaxFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, CLElementwiseMaxBroadcastFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(), + ElementwiseMaxFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/CL/ElementwiseMin.cpp b/tests/validation/CL/ElementwiseMin.cpp new file mode 100644 index 0000000000..05abfc853f --- /dev/null +++ b/tests/validation/CL/ElementwiseMin.cpp @@ -0,0 +1,277 @@ +/* + * 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 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/CLElementwiseOperations.h" +#include "tests/CL/CLAccessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/ConvertPolicyDataset.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<float> tolerance_fp32(0.000001f); +RelativeTolerance<float> tolerance_fp16(0.001f); + +constexpr unsigned int num_elems_processed_per_iteration = 16; +/** Input data sets **/ +const auto ElementwiseMinU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), framework::dataset::make("DataType", + DataType::U8)); +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 ElementwiseMinS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::U8, DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), + framework::dataset::make("DataType", DataType::S16)); +const auto ElementwiseMinFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataType", DataType::F16)); +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(CL) +TEST_SUITE(ElementwiseMin) + +// *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::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // 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::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + 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::S16), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, false, false, false})), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(CLElementwiseMin::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* + +template <typename T> +using CLElementwiseMinFixture = ElementwiseMinValidationFixture<CLTensor, CLAccessor, CLElementwiseMin, T>; + +TEST_SUITE(U8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::U8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::U8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8); + + // Create and Configure function + CLElementwiseMin 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMinFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMinU8Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() + +template <typename T> +using CLElementwiseMinQuantizedFixture = ElementwiseMinValidationQuantizedFixture<CLTensor, CLAccessor, CLElementwiseMin, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::QASYMM8); + + // Create and Configure function + CLElementwiseMin 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMinQuantizedFixture<uint8_t>, 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(CLAccessor(_target), _reference, tolerance_fp32, 0.01); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE(S16) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), + shape, data_type) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, data_type); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::S16); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::S16); + + // Create and Configure function + CLElementwiseMin 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMinFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMinS16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLElementwiseMinFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMinS16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() + +TEST_SUITE(Float) +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMinFixture<half>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseMinFP16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp16, 0.01); +} +TEST_SUITE_END() + +TEST_SUITE(FP32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::F32); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::F32); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::F32); + + // Create and Configure function + CLElementwiseMin 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseMinFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseMinFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLElementwiseMinFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseMinFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +template <typename T> +using CLElementwiseMinBroadcastFixture = ElementwiseMinBroadcastValidationFixture<CLTensor, CLAccessor, CLElementwiseMin, T>; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, CLElementwiseMinBroadcastFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(), + ElementwiseMinFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, CLElementwiseMinBroadcastFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(), + ElementwiseMinFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/CL/ElementwiseSquaredDiff.cpp b/tests/validation/CL/ElementwiseSquaredDiff.cpp new file mode 100644 index 0000000000..c00f95b885 --- /dev/null +++ b/tests/validation/CL/ElementwiseSquaredDiff.cpp @@ -0,0 +1,278 @@ +/* + * 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 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/CLElementwiseOperations.h" +#include "tests/CL/CLAccessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/ConvertPolicyDataset.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<float> tolerance_fp32(0.000001f); +RelativeTolerance<float> tolerance_fp16(0.001f); + +constexpr unsigned int num_elems_processed_per_iteration = 16; +/** Input data sets **/ +const auto ElementwiseSquaredDiffU8Dataset = combine(combine(framework::dataset::make("DataType", DataType::U8), framework::dataset::make("DataType", DataType::U8)), + framework::dataset::make("DataType", + DataType::U8)); +const auto ElementwiseSquaredDiffQASYMM8Dataset = combine(combine(framework::dataset::make("DataType", DataType::QASYMM8), framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("DataType", + DataType::QASYMM8)); +const auto ElementwiseSquaredDiffS16Dataset = combine(combine(framework::dataset::make("DataType", { DataType::U8, DataType::S16 }), framework::dataset::make("DataType", DataType::S16)), + framework::dataset::make("DataType", DataType::S16)); +const auto ElementwiseSquaredDiffFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataType", DataType::F16)); +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(CL) +TEST_SUITE(ElementwiseSquaredDiff) + +// *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::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), // Window shrink + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), // 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::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + 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::S16), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::U8), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, false, false, false})), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(CLElementwiseSquaredDiff::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* + +template <typename T> +using CLElementwiseSquaredDiffFixture = ElementwiseSquaredDiffValidationFixture<CLTensor, CLAccessor, CLElementwiseSquaredDiff, T>; + +TEST_SUITE(U8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::U8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::U8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8); + + // Create and Configure function + CLElementwiseSquaredDiff 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseSquaredDiffFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseSquaredDiffU8Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() + +template <typename T> +using CLElementwiseSquaredDiffQuantizedFixture = ElementwiseSquaredDiffValidationQuantizedFixture<CLTensor, CLAccessor, CLElementwiseSquaredDiff, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::QASYMM8); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::QASYMM8); + + // Create and Configure function + CLElementwiseSquaredDiff 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseSquaredDiffQuantizedFixture<uint8_t>, 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(CLAccessor(_target), _reference, tolerance_fp32, 0.01); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE(S16) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make("DataType", { DataType::U8, DataType::S16 })), + shape, data_type) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, data_type); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::S16); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::S16); + + // Create and Configure function + CLElementwiseSquaredDiff 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseSquaredDiffFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseSquaredDiffS16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLElementwiseSquaredDiffFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseSquaredDiffS16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() + +TEST_SUITE(Float) +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseSquaredDiffFixture<half>, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwiseSquaredDiffFP16Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp16, 0.01); +} +TEST_SUITE_END() + +TEST_SUITE(FP32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + CLTensor ref_src1 = create_tensor<CLTensor>(shape, DataType::F32); + CLTensor ref_src2 = create_tensor<CLTensor>(shape, DataType::F32); + CLTensor dst = create_tensor<CLTensor>(shape, DataType::F32); + + // Create and Configure function + CLElementwiseSquaredDiff 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); + + // Validate padding + const PaddingSize padding = PaddingCalculator(shape.x(), num_elems_processed_per_iteration).required_padding(); + validate(ref_src1.info()->padding(), padding); + validate(ref_src2.info()->padding(), padding); + validate(dst.info()->padding(), padding); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, CLElementwiseSquaredDiffFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), ElementwiseSquaredDiffFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLElementwiseSquaredDiffFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwiseSquaredDiffFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +template <typename T> +using CLElementwiseSquaredDiffBroadcastFixture = ElementwiseSquaredDiffBroadcastValidationFixture<CLTensor, CLAccessor, CLElementwiseSquaredDiff, T>; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, CLElementwiseSquaredDiffBroadcastFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapesBroadcast(), + ElementwiseSquaredDiffFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, CLElementwiseSquaredDiffBroadcastFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(), + ElementwiseSquaredDiffFP32Dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute |