From 988354de127528bdebb98fd25661fbf2f39f17dd Mon Sep 17 00:00:00 2001 From: Tianle Cheng Date: Wed, 28 Jun 2023 13:20:47 +0100 Subject: IVGCVSW-7831: Front end and Reference Implementation for REVERSE_V2 * Descriptors added for ReverseV2 * Layer definition added * Input validation added * Reference workload implementation for ReverseV2 added * Reference layer unit tests made for ReverseV2 * CompareTensors method updated to support comparison between empty tensors * CMake and other build files updated Signed-off-by: Tianle Cheng Change-Id: I805738454421309fda77c44218a8df171d68dc18 --- src/backends/backendsCommon/WorkloadData.cpp | 66 ++++++++++++++++++++++++++++ 1 file changed, 66 insertions(+) (limited to 'src/backends/backendsCommon/WorkloadData.cpp') diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp index d4ae08d874..6cde89c2e1 100644 --- a/src/backends/backendsCommon/WorkloadData.cpp +++ b/src/backends/backendsCommon/WorkloadData.cpp @@ -1640,6 +1640,72 @@ void ResizeQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const } } +void ReverseV2QueueDescriptor::Validate(const WorkloadInfo &workloadInfo) const { + const std::string descriptorName{"ReverseV2QueueDescriptor"}; + + ValidateNumInputs(workloadInfo, descriptorName, 1); + ValidateNumOutputs(workloadInfo, descriptorName, 1); + + const TensorInfo& inputTensorInfo = workloadInfo.m_InputTensorInfos[0]; + const TensorInfo& outputTensorInfo = workloadInfo.m_OutputTensorInfos[0]; + + auto inputTensorNumDimensions = inputTensorInfo.GetNumDimensions(); + if (inputTensorNumDimensions > m_Parameters.m_MaxDimension) + { + throw InvalidArgumentException(descriptorName + + ": Input tensors with rank greater than " + + std::to_string(m_Parameters.m_MaxDimension) + " are not supported."); + } + + std::vector supportedTypes = + { + DataType::BFloat16, + DataType::Float16, + DataType::Float32, + DataType::QAsymmS8, + DataType::QAsymmU8, + DataType::QSymmS16 + }; + + ValidateDataTypes(inputTensorInfo, supportedTypes, descriptorName); + ValidateTensorShapesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output"); + ValidateTensorDataTypesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output"); + + if (m_Parameters.m_Axis.size() > inputTensorNumDimensions) + { + throw InvalidArgumentException(descriptorName + ": More axes specified than is on the input tensor."); + } + if (m_Parameters.m_Axis.size() > m_Parameters.m_MaxDimension) + { + throw InvalidArgumentException(descriptorName + + ": More than " + std::to_string(m_Parameters.m_MaxDimension) + " axes cannot be specified."); + } + + if (! m_Parameters.m_Axis.empty()) + { + // First check that we have unique axis values + auto checkAxis = m_Parameters.m_Axis; + std::sort(checkAxis.begin(), checkAxis.end()); + auto lastUnique = std::unique(checkAxis.begin(), checkAxis.end()); + if (lastUnique != checkAxis.end()) + { + throw InvalidArgumentException(descriptorName + ": Axes values must be unique."); + } + + // Next check that the axes values are in range: [-rank, rank] + const auto minmax = + std::minmax_element(std::begin(m_Parameters.m_Axis), std::end(m_Parameters.m_Axis)); + if (((*minmax.first) < int32_t(-inputTensorNumDimensions)) || + ((*minmax.second) >= int32_t (inputTensorNumDimensions))) + { + throw InvalidArgumentException(descriptorName + + ": Axes values must in range [-" + std::to_string(inputTensorNumDimensions) + "," + + std::to_string(inputTensorNumDimensions) + "]."); + } + } +} + + void FakeQuantizationQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const { const std::string descriptorName{"FakeQuantizationQueueDescriptor"}; -- cgit v1.2.1