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Diffstat (limited to 'src/armnn/backends/test/WorkloadDataValidation.cpp')
-rw-r--r--src/armnn/backends/test/WorkloadDataValidation.cpp71
1 files changed, 46 insertions, 25 deletions
diff --git a/src/armnn/backends/test/WorkloadDataValidation.cpp b/src/armnn/backends/test/WorkloadDataValidation.cpp
index c3a9d40116..bc3898b405 100644
--- a/src/armnn/backends/test/WorkloadDataValidation.cpp
+++ b/src/armnn/backends/test/WorkloadDataValidation.cpp
@@ -22,7 +22,7 @@ BOOST_AUTO_TEST_CASE(QueueDescriptor_Validate_WrongNumOfInputsOutputs)
{
InputQueueDescriptor invalidData;
WorkloadInfo invalidInfo;
- //invalid argument exception is expected, because no inputs and no outputs were defined
+ //Invalid argument exception is expected, because no inputs and no outputs were defined.
BOOST_CHECK_THROW(RefWorkloadFactory().CreateInput(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
@@ -31,7 +31,7 @@ BOOST_AUTO_TEST_CASE(RefPooling2dFloat32Workload_Validate_WrongDimTensor)
armnn::TensorInfo inputTensorInfo;
armnn::TensorInfo outputTensorInfo;
- unsigned int inputShape[] = {2, 3, 4}; // <- invalid - input tensor has to be 4D
+ unsigned int inputShape[] = {2, 3, 4}; // <- Invalid - input tensor has to be 4D.
unsigned int outputShape[] = {2, 3, 4, 5};
outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32);
@@ -43,7 +43,7 @@ BOOST_AUTO_TEST_CASE(RefPooling2dFloat32Workload_Validate_WrongDimTensor)
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
- // invalid argument exception is expected, input tensor has to be 4D
+ // Invalid argument exception is expected, input tensor has to be 4D.
BOOST_CHECK_THROW(RefPooling2dFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
@@ -55,7 +55,7 @@ BOOST_AUTO_TEST_CASE(SoftmaxQueueDescriptor_Validate_WrongInputHeight)
unsigned int inputNum = 2;
unsigned int outputChannels = inputChannels;
- unsigned int outputHeight = inputHeight + 1; //makes data invalid - Softmax expects height and width to be 1
+ unsigned int outputHeight = inputHeight + 1; //Makes data invalid - Softmax expects height and width to be 1.
unsigned int outputWidth = inputWidth;
unsigned int outputNum = inputNum;
@@ -74,7 +74,7 @@ BOOST_AUTO_TEST_CASE(SoftmaxQueueDescriptor_Validate_WrongInputHeight)
AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
- //invalid argument exception is expected, because height != 1
+ //Invalid argument exception is expected, because height != 1.
BOOST_CHECK_THROW(RefSoftmaxFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
@@ -90,7 +90,7 @@ BOOST_AUTO_TEST_CASE(FullyConnectedQueueDescriptor_Validate_RequiredDataMissing)
unsigned int outputChannels = 3;
unsigned int outputNum = 2;
- // Define the tensor descriptors
+ // Define the tensor descriptors.
armnn::TensorInfo inputTensorInfo;
armnn::TensorInfo outputTensorInfo;
armnn::TensorInfo weightsDesc;
@@ -120,8 +120,8 @@ BOOST_AUTO_TEST_CASE(FullyConnectedQueueDescriptor_Validate_RequiredDataMissing)
invalidData.m_Parameters.m_TransposeWeightMatrix = false;
- //invalid argument exception is expected, because not all required fields have been provided
- //in particular inputsData[0], outputsData[0] and weightsData can not be null
+ //Invalid argument exception is expected, because not all required fields have been provided.
+ //In particular inputsData[0], outputsData[0] and weightsData can not be null.
BOOST_CHECK_THROW(RefFullyConnectedFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
@@ -135,8 +135,8 @@ BOOST_AUTO_TEST_CASE(NormalizationQueueDescriptor_Validate_WrongInputHeight)
constexpr unsigned int outputNum = inputNum;
constexpr unsigned int outputChannels = inputChannels;
- constexpr unsigned int outputHeight = inputHeight + 1; //makes data invalid - normalization requires
- //input and output to have the same dimensions
+ constexpr unsigned int outputHeight = inputHeight + 1; //Makes data invalid - normalization requires.
+ //Input and output to have the same dimensions.
constexpr unsigned int outputWidth = inputWidth;
@@ -169,7 +169,7 @@ BOOST_AUTO_TEST_CASE(NormalizationQueueDescriptor_Validate_WrongInputHeight)
invalidData.m_Parameters.m_Beta = beta;
invalidData.m_Parameters.m_K = kappa;
- //invalid argument exception is expected, because input height != output height
+ //Invalid argument exception is expected, because input height != output height.
BOOST_CHECK_THROW(RefNormalizationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
@@ -201,7 +201,7 @@ BOOST_AUTO_TEST_CASE(SplitterQueueDescriptor_Validate_WrongWindow)
AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
- // invalid since it has only 3 dimensions while the input tensor is 4d
+ // Invalid, since it has only 3 dimensions while the input tensor is 4d.
std::vector<unsigned int> wOrigin = {0, 0, 0};
armnn::SplitterQueueDescriptor::ViewOrigin window(wOrigin);
invalidData.m_ViewOrigins.push_back(window);
@@ -210,7 +210,7 @@ BOOST_AUTO_TEST_CASE(SplitterQueueDescriptor_Validate_WrongWindow)
"match input.");
BOOST_CHECK_THROW(RefSplitterFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
- // invalid since window extends past the boundary of input tensor
+ // Invalid, since window extends past the boundary of input tensor.
std::vector<unsigned int> wOrigin3 = {0, 0, 15, 0};
armnn::SplitterQueueDescriptor::ViewOrigin window3(wOrigin3);
invalidData.m_ViewOrigins[0] = window3;
@@ -259,7 +259,7 @@ BOOST_AUTO_TEST_CASE(MergerQueueDescriptor_Validate_WrongWindow)
AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
- // invalid since it has only 3 dimensions while the input tensor is 4d
+ // Invalid, since it has only 3 dimensions while the input tensor is 4d.
std::vector<unsigned int> wOrigin = {0, 0, 0};
armnn::MergerQueueDescriptor::ViewOrigin window(wOrigin);
invalidData.m_ViewOrigins.push_back(window);
@@ -268,7 +268,7 @@ BOOST_AUTO_TEST_CASE(MergerQueueDescriptor_Validate_WrongWindow)
"match input.");
BOOST_CHECK_THROW(RefMergerFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
- // invalid since window extends past the boundary of output tensor
+ // Invalid, since window extends past the boundary of output tensor.
std::vector<unsigned int> wOrigin3 = {0, 0, 15, 0};
armnn::MergerQueueDescriptor::ViewOrigin window3(wOrigin3);
invalidData.m_ViewOrigins[0] = window3;
@@ -308,17 +308,17 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputNumbers)
AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
- // too few inputs
+ // Too few inputs.
BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr);
- // correct
+ // Correct.
BOOST_CHECK_NO_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo));
AddInputToWorkload(invalidData, invalidInfo, input3TensorInfo, nullptr);
- // too many inputs
+ // Too many inputs.
BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
@@ -331,7 +331,7 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes)
unsigned int shape1[] = {1, 1, 2, 1};
unsigned int shape2[] = {1, 1, 3, 2};
- // Incompatible shapes even with broadcasting
+ // Incompatible shapes even with broadcasting.
{
input1TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32);
input2TensorInfo = armnn::TensorInfo(4, shape2, armnn::DataType::Float32);
@@ -347,7 +347,7 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes)
BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
- // Output size not compatible with input sizes
+ // Output size not compatible with input sizes.
{
input1TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32);
input2TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32);
@@ -360,7 +360,7 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes)
AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
- // output differs
+ // Output differs.
BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
}
@@ -374,7 +374,7 @@ BOOST_AUTO_TEST_CASE(MultiplicationQueueDescriptor_Validate_InputTensorDimension
constexpr unsigned int input0Shape[] = { 2, 2, 4, 4 };
constexpr std::size_t dimensionCount = std::extent<decltype(input0Shape)>::value;
- // Check dimension consistency for input tensors
+ // Checks dimension consistency for input tensors.
for (unsigned int dimIndex = 0; dimIndex < dimensionCount; ++dimIndex)
{
unsigned int input1Shape[dimensionCount];
@@ -399,7 +399,7 @@ BOOST_AUTO_TEST_CASE(MultiplicationQueueDescriptor_Validate_InputTensorDimension
BOOST_CHECK_THROW(RefMultiplicationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
- // Check dimension consistency for input and output tensors
+ // Checks dimension consistency for input and output tensors.
for (unsigned int dimIndex = 0; dimIndex < dimensionCount; ++dimIndex)
{
unsigned int outputShape[dimensionCount];
@@ -430,7 +430,7 @@ BOOST_AUTO_TEST_CASE(ReshapeQueueDescriptor_Validate_MismatchingNumElements)
armnn::TensorInfo inputTensorInfo;
armnn::TensorInfo outputTensorInfo;
- // The input and output shapes should have the same number of elements, but these don't
+ // The input and output shapes should have the same number of elements, but these don't.
unsigned int inputShape[] = { 1, 1, 2, 3 };
unsigned int outputShape[] = { 1, 1, 1, 2 };
@@ -443,8 +443,29 @@ BOOST_AUTO_TEST_CASE(ReshapeQueueDescriptor_Validate_MismatchingNumElements)
AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
- // InvalidArgumentException is expected, because the number of elements don't match
+ // InvalidArgumentException is expected, because the number of elements don't match.
BOOST_CHECK_THROW(RefReshapeFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
+
+BOOST_AUTO_TEST_CASE(LstmQueueDescriptor_Validate)
+{
+ armnn::TensorInfo inputTensorInfo;
+ armnn::TensorInfo outputTensorInfo;
+
+ unsigned int inputShape[] = { 1, 2 };
+ unsigned int outputShape[] = { 1 };
+
+ inputTensorInfo = armnn::TensorInfo(2, inputShape, armnn::DataType::Float32);
+ outputTensorInfo = armnn::TensorInfo(1, outputShape, armnn::DataType::Float32);
+
+ LstmQueueDescriptor invalidData;
+ WorkloadInfo invalidInfo;
+
+ AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
+ AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
+
+ BOOST_CHECK_THROW(invalidData.Validate(invalidInfo), armnn::InvalidArgumentException);
+}
+
BOOST_AUTO_TEST_SUITE_END()
generated by cgit v1.2.1 (git 2.23.0) at 2024-07-04 13:40:40 +0000