diff options
Diffstat (limited to 'tests')
-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 | ||||
-rw-r--r-- | tests/validation/fixtures/ElementwiseOperationsFixture.h | 286 | ||||
-rw-r--r-- | tests/validation/reference/ElementwiseOperations.cpp | 187 | ||||
-rw-r--r-- | tests/validation/reference/ElementwiseOperations.h | 47 |
9 files changed, 1543 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 diff --git a/tests/validation/fixtures/ElementwiseOperationsFixture.h b/tests/validation/fixtures/ElementwiseOperationsFixture.h new file mode 100644 index 0000000000..b051c858c2 --- /dev/null +++ b/tests/validation/fixtures/ElementwiseOperationsFixture.h @@ -0,0 +1,286 @@ +/* + * 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. + */ +#ifndef ARM_COMPUTE_TEST_ELEMENTWISE_OPERATIONS_FIXTURE +#define ARM_COMPUTE_TEST_ELEMENTWISE_OPERATIONS_FIXTURE + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "tests/AssetsLibrary.h" +#include "tests/Globals.h" +#include "tests/IAccessor.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Fixture.h" +#include "tests/validation/Helpers.h" +#include "tests/validation/reference/ElementwiseOperations.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ArithmeticOperationsGenericFixture : public framework::Fixture +{ +public: + template <typename...> + void setup(ArithmeticOperation op, const TensorShape &shape0, const TensorShape &shape1, + DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + { + _op = op; + _target = compute_target(shape0, shape1, data_type0, data_type1, output_data_type, qinfo0, qinfo1, qinfo_out); + _reference = compute_reference(shape0, shape1, data_type0, data_type1, output_data_type, qinfo0, qinfo1, qinfo_out); + } + +protected: + template <typename U> + void fill(U &&tensor, int i) + { + library->fill_tensor_uniform(tensor, i); + } + + TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + { + // Create tensors + TensorType ref_src1 = create_tensor<TensorType>(shape0, data_type0, 1, qinfo0); + TensorType ref_src2 = create_tensor<TensorType>(shape1, data_type1, 1, qinfo1); + TensorType dst = create_tensor<TensorType>(TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, qinfo_out); + + // Create and configure function + FunctionType elem_op; + elem_op.configure(&ref_src1, &ref_src2, &dst); + + ARM_COMPUTE_EXPECT(ref_src1.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(ref_src2.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + ref_src1.allocator()->allocate(); + ref_src2.allocator()->allocate(); + dst.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!ref_src1.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!ref_src2.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(ref_src1), 0); + fill(AccessorType(ref_src2), 1); + + // Compute function + elem_op.run(); + + return dst; + } + + SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, + DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + { + // Create reference + SimpleTensor<T> ref_src1{ shape0, data_type0, 1, qinfo0 }; + SimpleTensor<T> ref_src2{ shape1, data_type1, 1, qinfo1 }; + SimpleTensor<T> ref_dst{ TensorShape::broadcast_shape(shape0, shape1), output_data_type, 1, qinfo_out }; + + // Fill reference + fill(ref_src1, 0); + fill(ref_src2, 1); + + return reference::arithmetic_operation<T>(_op, ref_src1, ref_src2, ref_dst); + } + + TensorType _target{}; + SimpleTensor<T> _reference{}; + ArithmeticOperation _op{ ArithmeticOperation::ADD }; +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ArithmeticDivisionBroadcastValidationFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::DIV, shape0, shape1, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ArithmeticDivisionValidationFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::DIV, shape, shape, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ArithmeticDivisionValidationQuantizedFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::DIV, shape, shape, + data_type0, data_type1, output_data_type, + qinfo0, qinfo1, qinfo_out); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseMaxBroadcastValidationFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::MAX, shape0, shape1, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseMaxValidationFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::MAX, shape, shape, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseMaxValidationQuantizedFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::MAX, shape, shape, + data_type0, data_type1, output_data_type, + qinfo0, qinfo1, qinfo_out); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseMinBroadcastValidationFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::MIN, shape0, shape1, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseMinValidationFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::MIN, shape, shape, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseMinValidationQuantizedFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::MIN, shape, shape, + data_type0, data_type1, output_data_type, + qinfo0, qinfo1, qinfo_out); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseSquaredDiffBroadcastValidationFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::SQUARED_DIFF, shape0, shape1, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseSquaredDiffValidationFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::SQUARED_DIFF, shape, shape, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ElementwiseSquaredDiffValidationQuantizedFixture : public ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type, + QuantizationInfo qinfo0, QuantizationInfo qinfo1, QuantizationInfo qinfo_out) + + { + ArithmeticOperationsGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(ArithmeticOperation::SQUARED_DIFF, shape, shape, + data_type0, data_type1, output_data_type, + qinfo0, qinfo1, qinfo_out); + } +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ARITHMETIC_OPERATIONS_FIXTURE */ diff --git a/tests/validation/reference/ElementwiseOperations.cpp b/tests/validation/reference/ElementwiseOperations.cpp new file mode 100644 index 0000000000..fe0467fe5e --- /dev/null +++ b/tests/validation/reference/ElementwiseOperations.cpp @@ -0,0 +1,187 @@ +/* + * 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 "ElementwiseOperations.h" + +#include "arm_compute/core/Types.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +namespace +{ +template <typename T> +T arithm_op(ArithmeticOperation op, T src1, T src2, ConvertPolicy convert_policy) +{ + using intermediate_type = typename common_promoted_signed_type<T>::intermediate_type; + + intermediate_type val; + + if(op == ArithmeticOperation::ADD) + { + val = static_cast<intermediate_type>(src1) + static_cast<intermediate_type>(src2); + } + else if(op == ArithmeticOperation::SUB) + { + val = static_cast<intermediate_type>(src1) - static_cast<intermediate_type>(src2); + } + else if(op == ArithmeticOperation::MIN) + { + val = std::min(static_cast<intermediate_type>(src1), static_cast<intermediate_type>(src2)); + } + else if(op == ArithmeticOperation::MAX) + { + val = std::max(static_cast<intermediate_type>(src1), static_cast<intermediate_type>(src2)); + } + else if(op == ArithmeticOperation::SQUARED_DIFF) + { + intermediate_type tmp = (static_cast<intermediate_type>(src1) - static_cast<intermediate_type>(src2)); + val = tmp * tmp; + } + else if(op == ArithmeticOperation::DIV) + { + val = (static_cast<intermediate_type>(src1) / static_cast<intermediate_type>(src2)); + } + else + { + ARM_COMPUTE_ERROR("Not handled"); + } + + T result; + if(op == ArithmeticOperation::ADD || op == ArithmeticOperation::SUB) + { + result = (convert_policy == ConvertPolicy::SATURATE) ? saturate_cast<T>(val) : static_cast<T>(val); + } + else + { + result = static_cast<T>(val); + } + return result; +} + +template <size_t dim> +struct BroadcastUnroll +{ + template <typename T> + static void unroll(ArithmeticOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst, + ConvertPolicy convert_policy, Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst) + { + const bool src1_is_broadcast = (src1.shape()[dim - 1] != dst.shape()[dim - 1]); + const bool src2_is_broadcast = (src2.shape()[dim - 1] != dst.shape()[dim - 1]); + + id_src1.set(dim - 1, 0); + id_src2.set(dim - 1, 0); + id_dst.set(dim - 1, 0); + + for(size_t i = 0; i < dst.shape()[dim - 1]; ++i, ++id_dst[dim - 1]) + { + BroadcastUnroll < dim - 1 >::unroll(op, src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); + + id_src1[dim - 1] += !src1_is_broadcast; + id_src2[dim - 1] += !src2_is_broadcast; + } + } +}; + +template <> +struct BroadcastUnroll<0> +{ + template <typename T> + static void unroll(ArithmeticOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst, + ConvertPolicy convert_policy, Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst) + { + dst[coord2index(dst.shape(), id_dst)] = arithm_op(op, src1[coord2index(src1.shape(), id_src1)], src2[coord2index(src2.shape(), id_src2)], convert_policy); + } +}; +} // namespace + +template <typename T> +SimpleTensor<T> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst, ConvertPolicy convert_policy) +{ + Coordinates id_src1, id_src2, id_dst; + + BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(op, src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); + + return dst; +} + +template <> +SimpleTensor<uint8_t> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<uint8_t> &src1, const SimpleTensor<uint8_t> &src2, SimpleTensor<uint8_t> &dst, ConvertPolicy convert_policy) +{ + if(dst.data_type() == DataType::QASYMM8) + { + SimpleTensor<float> src1_tmp = convert_from_asymmetric(src1); + SimpleTensor<float> src2_tmp = convert_from_asymmetric(src2); + SimpleTensor<float> dst_tmp(TensorShape::broadcast_shape(src1.shape(), src2.shape()), dst.data_type()); + + Coordinates id_src1, id_src2, id_dst; + + BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(op, src1_tmp, src2_tmp, dst_tmp, convert_policy, id_src1, id_src2, id_dst); + + dst = convert_to_asymmetric(dst_tmp, dst.quantization_info()); + return dst; + } + else + { + // DataType::U8 + Coordinates id_src1, id_src2, id_dst; + + BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(op, src1, src2, dst, convert_policy, id_src1, id_src2, id_dst); + + return dst; + } +} + +template SimpleTensor<int16_t> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<int16_t> &src1, const SimpleTensor<int16_t> &src2, SimpleTensor<int16_t> &dst, + ConvertPolicy convert_policy); +template SimpleTensor<int8_t> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<int8_t> &src1, const SimpleTensor<int8_t> &src2, SimpleTensor<int8_t> &dst, + ConvertPolicy convert_policy); +template SimpleTensor<half> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<half> &src1, const SimpleTensor<half> &src2, SimpleTensor<half> &dst, ConvertPolicy convert_policy); +template SimpleTensor<float> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<float> &src1, const SimpleTensor<float> &src2, SimpleTensor<float> &dst, ConvertPolicy convert_policy); + +template <typename T> +SimpleTensor<T> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, DataType dst_data_type, ConvertPolicy convert_policy) +{ + ARM_COMPUTE_ERROR_ON_MSG(dst_data_type == DataType::QASYMM8, "For QASYMM8, the quantized output tensor should be passed directly."); + + SimpleTensor<T> dst(TensorShape::broadcast_shape(src1.shape(), src2.shape()), dst_data_type); + arithmetic_operation<T>(op, src1, src2, dst, convert_policy); + return dst; +} + +template SimpleTensor<int16_t> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<int16_t> &src1, const SimpleTensor<int16_t> &src2, DataType dst_data_type, + ConvertPolicy convert_policy); +template SimpleTensor<int8_t> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<int8_t> &src1, const SimpleTensor<int8_t> &src2, DataType dst_data_type, ConvertPolicy convert_policy); +template SimpleTensor<half> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<half> &src1, const SimpleTensor<half> &src2, DataType dst_data_type, ConvertPolicy convert_policy); +template SimpleTensor<float> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<float> &src1, const SimpleTensor<float> &src2, DataType dst_data_type, ConvertPolicy convert_policy); + +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/reference/ElementwiseOperations.h b/tests/validation/reference/ElementwiseOperations.h new file mode 100644 index 0000000000..7518ec86d5 --- /dev/null +++ b/tests/validation/reference/ElementwiseOperations.h @@ -0,0 +1,47 @@ +/* + * 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. + */ +#ifndef __ARM_COMPUTE_TEST_ELEMENTWISE_OPERATIONS_H__ +#define __ARM_COMPUTE_TEST_ELEMENTWISE_OPERATIONS_H__ + +#include "tests/SimpleTensor.h" +#include "tests/validation/Helpers.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +template <typename T> +SimpleTensor<T> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst, ConvertPolicy convert_policy = ConvertPolicy::WRAP); + +template <typename T> +SimpleTensor<T> arithmetic_operation(ArithmeticOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, DataType dst_data_type, ConvertPolicy convert_policy = ConvertPolicy::WRAP); +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* __ARM_COMPUTE_TEST_ELEMENTWISE_OPERATIONS_H__ */ |