// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include #include #include using namespace armnn; TEST_SUITE("Tensor") { struct TensorInfoFixture { TensorInfoFixture() { unsigned int sizes[] = {6,7,8,9}; m_TensorInfo = TensorInfo(4, sizes, DataType::Float32); } ~TensorInfoFixture() {}; TensorInfo m_TensorInfo; }; TEST_CASE_FIXTURE(TensorInfoFixture, "ConstructShapeUsingListInitialization") { TensorShape listInitializedShape{ 6, 7, 8, 9 }; CHECK(listInitializedShape == m_TensorInfo.GetShape()); } TEST_CASE_FIXTURE(TensorInfoFixture, "ConstructTensorInfo") { CHECK(m_TensorInfo.GetNumDimensions() == 4); CHECK(m_TensorInfo.GetShape()[0] == 6); // <= Outer most CHECK(m_TensorInfo.GetShape()[1] == 7); CHECK(m_TensorInfo.GetShape()[2] == 8); CHECK(m_TensorInfo.GetShape()[3] == 9); // <= Inner most } TEST_CASE_FIXTURE(TensorInfoFixture, "CopyConstructTensorInfo") { TensorInfo copyConstructed(m_TensorInfo); CHECK(copyConstructed.GetNumDimensions() == 4); CHECK(copyConstructed.GetShape()[0] == 6); CHECK(copyConstructed.GetShape()[1] == 7); CHECK(copyConstructed.GetShape()[2] == 8); CHECK(copyConstructed.GetShape()[3] == 9); } TEST_CASE_FIXTURE(TensorInfoFixture, "TensorInfoEquality") { TensorInfo copyConstructed(m_TensorInfo); CHECK(copyConstructed == m_TensorInfo); } TEST_CASE_FIXTURE(TensorInfoFixture, "TensorInfoInequality") { TensorInfo other; unsigned int sizes[] = {2,3,4,5}; other = TensorInfo(4, sizes, DataType::Float32); CHECK(other != m_TensorInfo); } TEST_CASE_FIXTURE(TensorInfoFixture, "TensorInfoAssignmentOperator") { TensorInfo copy; copy = m_TensorInfo; CHECK(copy == m_TensorInfo); } TEST_CASE("CopyNoQuantizationTensorInfo") { TensorInfo infoA; infoA.SetShape({ 5, 6, 7, 8 }); infoA.SetDataType(DataType::QAsymmU8); TensorInfo infoB; infoB.SetShape({ 5, 6, 7, 8 }); infoB.SetDataType(DataType::QAsymmU8); infoB.SetQuantizationScale(10.0f); infoB.SetQuantizationOffset(5); infoB.SetQuantizationDim(Optional(1)); CHECK((infoA.GetShape() == TensorShape({ 5, 6, 7, 8 }))); CHECK((infoA.GetDataType() == DataType::QAsymmU8)); CHECK(infoA.GetQuantizationScale() == 1); CHECK(infoA.GetQuantizationOffset() == 0); CHECK(!infoA.GetQuantizationDim().has_value()); CHECK(infoA != infoB); infoA = infoB; CHECK(infoA == infoB); CHECK((infoA.GetShape() == TensorShape({ 5, 6, 7, 8 }))); CHECK((infoA.GetDataType() == DataType::QAsymmU8)); CHECK(infoA.GetQuantizationScale() == 10.0f); CHECK(infoA.GetQuantizationOffset() == 5); CHECK(infoA.GetQuantizationDim().value() == 1); } TEST_CASE("CopyDifferentQuantizationTensorInfo") { TensorInfo infoA; infoA.SetShape({ 5, 6, 7, 8 }); infoA.SetDataType(DataType::QAsymmU8); infoA.SetQuantizationScale(10.0f); infoA.SetQuantizationOffset(5); infoA.SetQuantizationDim(Optional(1)); TensorInfo infoB; infoB.SetShape({ 5, 6, 7, 8 }); infoB.SetDataType(DataType::QAsymmU8); infoB.SetQuantizationScale(11.0f); infoB.SetQuantizationOffset(6); infoB.SetQuantizationDim(Optional(2)); CHECK((infoA.GetShape() == TensorShape({ 5, 6, 7, 8 }))); CHECK((infoA.GetDataType() == DataType::QAsymmU8)); CHECK(infoA.GetQuantizationScale() == 10.0f); CHECK(infoA.GetQuantizationOffset() == 5); CHECK(infoA.GetQuantizationDim().value() == 1); CHECK(infoA != infoB); infoA = infoB; CHECK(infoA == infoB); CHECK((infoA.GetShape() == TensorShape({ 5, 6, 7, 8 }))); CHECK((infoA.GetDataType() == DataType::QAsymmU8)); CHECK(infoA.GetQuantizationScale() == 11.0f); CHECK(infoA.GetQuantizationOffset() == 6); CHECK(infoA.GetQuantizationDim().value() == 2); } void CheckTensor(const ConstTensor& t) { t.GetInfo(); } TEST_CASE("TensorVsConstTensor") { int mutableDatum = 2; const int immutableDatum = 3; armnn::Tensor uninitializedTensor; uninitializedTensor.GetInfo().SetConstant(true); armnn::ConstTensor uninitializedTensor2; uninitializedTensor2 = uninitializedTensor; armnn::TensorInfo emptyTensorInfo; emptyTensorInfo.SetConstant(true); armnn::Tensor t(emptyTensorInfo, &mutableDatum); armnn::ConstTensor ct(emptyTensorInfo, &immutableDatum); // Checks that both Tensor and ConstTensor can be passed as a ConstTensor. CheckTensor(t); CheckTensor(ct); } TEST_CASE("ConstTensor_EmptyConstructorTensorInfoSet") { armnn::ConstTensor t; CHECK(t.GetInfo().IsConstant() == true); } TEST_CASE("ConstTensor_TensorInfoNotConstantError") { armnn::TensorInfo tensorInfo ({ 1 }, armnn::DataType::Float32); std::vector tensorData = { 1.0f }; try { armnn::ConstTensor ct(tensorInfo, tensorData); FAIL("InvalidArgumentException should have been thrown"); } catch(const InvalidArgumentException& exc) { CHECK(strcmp(exc.what(), "Invalid attempt to construct ConstTensor from non-constant TensorInfo.") == 0); } } TEST_CASE("PassTensorToConstTensor_TensorInfoNotConstantError") { try { armnn::ConstTensor t = ConstTensor(Tensor()); FAIL("InvalidArgumentException should have been thrown"); } catch(const InvalidArgumentException& exc) { CHECK(strcmp(exc.what(), "Invalid attempt to construct ConstTensor from " "Tensor due to non-constant TensorInfo") == 0); } } TEST_CASE("ModifyTensorInfo") { TensorInfo info; info.SetShape({ 5, 6, 7, 8 }); CHECK((info.GetShape() == TensorShape({ 5, 6, 7, 8 }))); info.SetDataType(DataType::QAsymmU8); CHECK((info.GetDataType() == DataType::QAsymmU8)); info.SetQuantizationScale(10.0f); CHECK(info.GetQuantizationScale() == 10.0f); info.SetQuantizationOffset(5); CHECK(info.GetQuantizationOffset() == 5); } TEST_CASE("TensorShapeOperatorBrackets") { const TensorShape constShape({0,1,2,3}); TensorShape shape({0,1,2,3}); // Checks version of operator[] which returns an unsigned int. CHECK(shape[2] == 2); shape[2] = 20; CHECK(shape[2] == 20); // Checks the version of operator[] which returns a reference. CHECK(constShape[2] == 2); } TEST_CASE("TensorInfoPerAxisQuantization") { // Old constructor TensorInfo tensorInfo0({ 1, 1 }, DataType::Float32, 2.0f, 1); CHECK(!tensorInfo0.HasMultipleQuantizationScales()); CHECK(tensorInfo0.GetQuantizationScale() == 2.0f); CHECK(tensorInfo0.GetQuantizationOffset() == 1); CHECK(tensorInfo0.GetQuantizationScales()[0] == 2.0f); CHECK(!tensorInfo0.GetQuantizationDim().has_value()); // Set per-axis quantization scales std::vector perAxisScales{ 3.0f, 4.0f }; tensorInfo0.SetQuantizationScales(perAxisScales); CHECK(tensorInfo0.HasMultipleQuantizationScales()); CHECK(tensorInfo0.GetQuantizationScales() == perAxisScales); // Set per-tensor quantization scale tensorInfo0.SetQuantizationScale(5.0f); CHECK(!tensorInfo0.HasMultipleQuantizationScales()); CHECK(tensorInfo0.GetQuantizationScales()[0] == 5.0f); // Set quantization offset tensorInfo0.SetQuantizationDim(Optional(1)); CHECK(tensorInfo0.GetQuantizationDim().value() == 1); // New constructor perAxisScales = { 6.0f, 7.0f }; TensorInfo tensorInfo1({ 1, 1 }, DataType::Float32, perAxisScales, 1); CHECK(tensorInfo1.HasMultipleQuantizationScales()); CHECK(tensorInfo1.GetQuantizationOffset() == 0); CHECK(tensorInfo1.GetQuantizationScales() == perAxisScales); CHECK(tensorInfo1.GetQuantizationDim().value() == 1); } TEST_CASE("TensorShape_scalar") { float mutableDatum = 3.1416f; const armnn::TensorShape shape (armnn::Dimensionality::Scalar ); armnn::TensorInfo info ( shape, DataType::Float32 ); const armnn::Tensor tensor ( info, &mutableDatum ); CHECK(armnn::Dimensionality::Scalar == shape.GetDimensionality()); float scalarValue = *reinterpret_cast(tensor.GetMemoryArea()); CHECK_MESSAGE(mutableDatum == scalarValue, "Scalar value is " << scalarValue); armnn::TensorShape shape_equal; armnn::TensorShape shape_different; shape_equal = shape; CHECK(shape_equal == shape); CHECK(shape_different != shape); CHECK_MESSAGE(1 == shape.GetNumElements(), "Number of elements is " << shape.GetNumElements()); CHECK_MESSAGE(1 == shape.GetNumDimensions(), "Number of dimensions is " << shape.GetNumDimensions()); CHECK(true == shape.GetDimensionSpecificity(0)); CHECK(shape.AreAllDimensionsSpecified()); CHECK(shape.IsAtLeastOneDimensionSpecified()); CHECK(1 == shape[0]); CHECK(1 == tensor.GetShape()[0]); CHECK(1 == tensor.GetInfo().GetShape()[0]); CHECK_THROWS_AS( shape[1], InvalidArgumentException ); float newMutableDatum = 42.f; std::memcpy(tensor.GetMemoryArea(), &newMutableDatum, sizeof(float)); scalarValue = *reinterpret_cast(tensor.GetMemoryArea()); CHECK_MESSAGE(newMutableDatum == scalarValue, "Scalar value is " << scalarValue); } TEST_CASE("TensorShape_DynamicTensorType1_unknownNumberDimensions") { float mutableDatum = 3.1416f; armnn::TensorShape shape (armnn::Dimensionality::NotSpecified ); armnn::TensorInfo info ( shape, DataType::Float32 ); armnn::Tensor tensor ( info, &mutableDatum ); CHECK(armnn::Dimensionality::NotSpecified == shape.GetDimensionality()); CHECK_THROWS_AS( shape[0], InvalidArgumentException ); CHECK_THROWS_AS( shape.GetNumElements(), InvalidArgumentException ); CHECK_THROWS_AS( shape.GetNumDimensions(), InvalidArgumentException ); armnn::TensorShape shape_equal; armnn::TensorShape shape_different; shape_equal = shape; CHECK(shape_equal == shape); CHECK(shape_different != shape); } TEST_CASE("TensorShape_DynamicTensorType1_unknownAllDimensionsSizes") { float mutableDatum = 3.1416f; armnn::TensorShape shape ( 3, false ); armnn::TensorInfo info ( shape, DataType::Float32 ); armnn::Tensor tensor ( info, &mutableDatum ); CHECK(armnn::Dimensionality::Specified == shape.GetDimensionality()); CHECK_MESSAGE(0 == shape.GetNumElements(), "Number of elements is " << shape.GetNumElements()); CHECK_MESSAGE(3 == shape.GetNumDimensions(), "Number of dimensions is " << shape.GetNumDimensions()); CHECK(false == shape.GetDimensionSpecificity(0)); CHECK(false == shape.GetDimensionSpecificity(1)); CHECK(false == shape.GetDimensionSpecificity(2)); CHECK(!shape.AreAllDimensionsSpecified()); CHECK(!shape.IsAtLeastOneDimensionSpecified()); armnn::TensorShape shape_equal; armnn::TensorShape shape_different; shape_equal = shape; CHECK(shape_equal == shape); CHECK(shape_different != shape); } TEST_CASE("TensorShape_DynamicTensorType1_unknownSomeDimensionsSizes") { std::vector mutableDatum { 42.f, 42.f, 42.f, 0.0f, 0.1f, 0.2f }; armnn::TensorShape shape ( {2, 0, 3}, {true, false, true} ); armnn::TensorInfo info ( shape, DataType::Float32 ); armnn::Tensor tensor ( info, &mutableDatum ); CHECK(armnn::Dimensionality::Specified == shape.GetDimensionality()); CHECK_MESSAGE(6 == shape.GetNumElements(), "Number of elements is " << shape.GetNumElements()); CHECK_MESSAGE(3 == shape.GetNumDimensions(), "Number of dimensions is " << shape.GetNumDimensions()); CHECK(true == shape.GetDimensionSpecificity(0)); CHECK(false == shape.GetDimensionSpecificity(1)); CHECK(true == shape.GetDimensionSpecificity(2)); CHECK(!shape.AreAllDimensionsSpecified()); CHECK(shape.IsAtLeastOneDimensionSpecified()); CHECK_THROWS_AS(shape[1], InvalidArgumentException); CHECK_THROWS_AS(tensor.GetShape()[1], InvalidArgumentException); CHECK_THROWS_AS(tensor.GetInfo().GetShape()[1], InvalidArgumentException); CHECK(2 == shape[0]); CHECK(2 == tensor.GetShape()[0]); CHECK(2 == tensor.GetInfo().GetShape()[0]); CHECK_THROWS_AS( shape[1], InvalidArgumentException ); CHECK(3 == shape[2]); CHECK(3 == tensor.GetShape()[2]); CHECK(3 == tensor.GetInfo().GetShape()[2]); armnn::TensorShape shape_equal; armnn::TensorShape shape_different; shape_equal = shape; CHECK(shape_equal == shape); CHECK(shape_different != shape); } TEST_CASE("TensorShape_DynamicTensorType1_transitionFromUnknownToKnownDimensionsSizes") { std::vector mutableDatum { 42.f, 42.f, 42.f, 0.0f, 0.1f, 0.2f }; armnn::TensorShape shape (armnn::Dimensionality::NotSpecified ); armnn::TensorInfo info ( shape, DataType::Float32 ); armnn::Tensor tensor ( info, &mutableDatum ); // Specify the number of dimensions shape.SetNumDimensions(3); CHECK(armnn::Dimensionality::Specified == shape.GetDimensionality()); CHECK_MESSAGE(3 == shape.GetNumDimensions(), "Number of dimensions is " << shape.GetNumDimensions()); CHECK(false == shape.GetDimensionSpecificity(0)); CHECK(false == shape.GetDimensionSpecificity(1)); CHECK(false == shape.GetDimensionSpecificity(2)); CHECK(!shape.AreAllDimensionsSpecified()); CHECK(!shape.IsAtLeastOneDimensionSpecified()); // Specify dimension 0 and 2. shape.SetDimensionSize(0, 2); shape.SetDimensionSize(2, 3); CHECK_MESSAGE(3 == shape.GetNumDimensions(), "Number of dimensions is " << shape.GetNumDimensions()); CHECK_MESSAGE(6 == shape.GetNumElements(), "Number of elements is " << shape.GetNumElements()); CHECK(true == shape.GetDimensionSpecificity(0)); CHECK(false == shape.GetDimensionSpecificity(1)); CHECK(true == shape.GetDimensionSpecificity(2)); CHECK(!shape.AreAllDimensionsSpecified()); CHECK(shape.IsAtLeastOneDimensionSpecified()); info.SetShape(shape); armnn::Tensor tensor2( info, &mutableDatum ); CHECK(2 == shape[0]); CHECK(2 == tensor2.GetShape()[0]); CHECK(2 == tensor2.GetInfo().GetShape()[0]); CHECK_THROWS_AS(shape[1], InvalidArgumentException); CHECK_THROWS_AS(tensor.GetShape()[1], InvalidArgumentException); CHECK_THROWS_AS(tensor.GetInfo().GetShape()[1], InvalidArgumentException); CHECK(3 == shape[2]); CHECK(3 == tensor2.GetShape()[2]); CHECK(3 == tensor2.GetInfo().GetShape()[2]); armnn::TensorShape shape_equal; armnn::TensorShape shape_different; shape_equal = shape; CHECK(shape_equal == shape); CHECK(shape_different != shape); // Specify dimension 1. shape.SetDimensionSize(1, 5); CHECK_MESSAGE(3 == shape.GetNumDimensions(), "Number of dimensions is " << shape.GetNumDimensions()); CHECK_MESSAGE(30 == shape.GetNumElements(), "Number of elements is " << shape.GetNumElements()); CHECK(true == shape.GetDimensionSpecificity(0)); CHECK(true == shape.GetDimensionSpecificity(1)); CHECK(true == shape.GetDimensionSpecificity(2)); CHECK(shape.AreAllDimensionsSpecified()); CHECK(shape.IsAtLeastOneDimensionSpecified()); } TEST_CASE("Tensor_emptyConstructors") { auto shape = armnn::TensorShape(); CHECK_MESSAGE( 0 == shape.GetNumDimensions(), "Number of dimensions is " << shape.GetNumDimensions()); CHECK_MESSAGE( 0 == shape.GetNumElements(), "Number of elements is " << shape.GetNumElements()); CHECK( armnn::Dimensionality::Specified == shape.GetDimensionality()); CHECK( shape.AreAllDimensionsSpecified()); CHECK_THROWS_AS( shape[0], InvalidArgumentException ); auto tensor = armnn::Tensor(); CHECK_MESSAGE( 0 == tensor.GetNumDimensions(), "Number of dimensions is " << tensor.GetNumDimensions()); CHECK_MESSAGE( 0 == tensor.GetNumElements(), "Number of elements is " << tensor.GetNumElements()); CHECK_MESSAGE( 0 == tensor.GetShape().GetNumDimensions(), "Number of dimensions is " << tensor.GetShape().GetNumDimensions()); CHECK_MESSAGE( 0 == tensor.GetShape().GetNumElements(), "Number of dimensions is " << tensor.GetShape().GetNumElements()); CHECK( armnn::Dimensionality::Specified == tensor.GetShape().GetDimensionality()); CHECK( tensor.GetShape().AreAllDimensionsSpecified()); CHECK_THROWS_AS( tensor.GetShape()[0], InvalidArgumentException ); } }