IVGCVSW-7879 Change REVERSE_V2 from LayerWithParameters with 1 input, to Layer with 2 inputs

  * Changing ReverseV2 to use two inputs
  * This is required by the backends
  * The ReverseV2Descriptor was removed
  * Tests updated
  * Added a Run<> templatefor inputs with different data types

Signed-off-by: Tracy Narine <tracy.narine@arm.com>
Change-Id: I22f947de829b4b3da6bda3a74f4ffdef4052cc25

1 files changed, 27 insertions, 36 deletions

diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index a26aaf490b..bd3c7c2760 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -1617,18 +1617,35 @@ void ResizeQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
 void ReverseV2QueueDescriptor::Validate(const WorkloadInfo &workloadInfo) const {
     const std::string descriptorName{"ReverseV2QueueDescriptor"};
 
-    ValidateNumInputs(workloadInfo,  descriptorName, 1);
+    // Backend restriction
+    const unsigned int maxDimensions = 4;
+
+    ValidateNumInputs(workloadInfo,  descriptorName, 2);
     ValidateNumOutputs(workloadInfo, descriptorName, 1);
 
     const TensorInfo& inputTensorInfo  = workloadInfo.m_InputTensorInfos[0];
+    const TensorInfo& axisTensorInfo  = workloadInfo.m_InputTensorInfos[1];
     const TensorInfo& outputTensorInfo = workloadInfo.m_OutputTensorInfos[0];
 
-    auto inputTensorNumDimensions = inputTensorInfo.GetNumDimensions();
-    if (inputTensorNumDimensions > m_Parameters.m_MaxDimension)
+    const auto inputTensorNumDimensions = inputTensorInfo.GetNumDimensions();
+    if (inputTensorNumDimensions > maxDimensions)
     {
         throw InvalidArgumentException(descriptorName +
             ": Input tensors with rank greater than " +
-            std::to_string(m_Parameters.m_MaxDimension) + " are not supported.");
+            std::to_string(maxDimensions) + " are not supported.");
+    }
+
+    const auto axisTensorNumDimensions = axisTensorInfo.GetNumDimensions();
+    if (axisTensorNumDimensions > maxDimensions)
+    {
+        throw InvalidArgumentException(descriptorName +
+            ": More than " + std::to_string(maxDimensions) + " axes cannot be specified.");
+    }
+
+    if (axisTensorNumDimensions > inputTensorNumDimensions)
+    {
+        throw InvalidArgumentException(descriptorName +
+            ": More axes specified than the number of axes on the input tensor.");
     }
 
     std::vector<DataType> supportedTypes =
@@ -1642,44 +1659,18 @@ void ReverseV2QueueDescriptor::Validate(const WorkloadInfo &workloadInfo) const
     };
 
     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)
+    std::vector<DataType> axisSupportedTypes =
     {
-        throw InvalidArgumentException(descriptorName +
-            ": More than " + std::to_string(m_Parameters.m_MaxDimension) + " axes cannot be specified.");
-    }
+        DataType::Signed32,
+    };
 
-    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.");
-        }
+    ValidateDataTypes(axisTensorInfo, axisSupportedTypes, descriptorName);
 
-        // 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) + "].");
-        }
-    }
+    ValidateTensorShapesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output");
+    ValidateTensorDataTypesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output");
 }
 
-
 void FakeQuantizationQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
 {
     const std::string descriptorName{"FakeQuantizationQueueDescriptor"};