IVGCVSW-3221 Refactor Mean ref workload and tests

 * Renamed RefMeanFloat32Workload and RefMeanUint8Workload
   to RefMeanWorkload, updated references to reflect this
   change.
 * Refactored RefFloorWorkload to use Decoders/Encoders,
   to support the use of multiple data types.
 * Deleted reference Unit8 Mean tests as they were
   duplicates of the Float32 tests. Refactored these tests
   to support multiple data types and updated references.
 * Adjusted the values used in the tests' input tensors so
   that they are more like floating point numbers
   e.g. change 1.0f to 1.5f.
 * Replace size_t with unsigned int in Mean ref workload,
   for better compatibility with the Encoder/Decoder,
   removed some unnecessary casts after this.
 * Added ValidateTensorDataTypesMatch() function to
   WorkloadData.cpp, added CreateIncorrectDimensionsErrorMsg
   function to RefLayerSupport.cpp.
 * Added passing and failing tests for ref IsMeanSupported.

Signed-off-by: James Conroy <james.conroy@arm.com>
Change-Id: Id3d44463d1385255c727a497d4026d21a49e7eb2

1 files changed, 34 insertions, 5 deletions

diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index a1d00c6945..1505078b77 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -271,6 +271,20 @@ void ValidateDataTypes(const TensorInfo& info,
     }
 }
 
+//---------------------------------------------------------------
+void ValidateTensorDataTypesMatch(const TensorInfo& first,
+                                  const TensorInfo& second,
+                                  std::string const& descName,
+                                  std::string const& firstName,
+                                  std::string const& secondName)
+{
+    if (first.GetDataType() != second.GetDataType())
+    {
+        throw InvalidArgumentException(descName + ": " + firstName + " & " + secondName +
+                                       " must have identical data types.");
+    }
+}
+
 } //namespace
 
 void QueueDescriptor::ValidateInputsOutputs(const std::string& descName,
@@ -1275,25 +1289,40 @@ void MaximumQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
 
 void MeanQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
 {
-    ValidateNumInputs(workloadInfo, "MeanQueueDescriptor", 1);
-    ValidateNumOutputs(workloadInfo, "MeanQueueDescriptor", 1);
+    const std::string meanQueueDescString = "MeanQueueDescriptor";
+
+    ValidateNumInputs(workloadInfo, meanQueueDescString, 1);
+    ValidateNumOutputs(workloadInfo, meanQueueDescString, 1);
+
+    std::vector<DataType> supportedTypes =
+    {
+        DataType::Float32,
+        DataType::Float16,
+        DataType::QuantisedAsymm8,
+        DataType::QuantisedSymm16
+    };
 
     const TensorInfo& input  = workloadInfo.m_InputTensorInfos[0];
     const TensorInfo& output = workloadInfo.m_OutputTensorInfos[0];
 
+    // First check if input tensor data type is supported, then
+    // check if this data type matches the output tensor data type
+    ValidateDataTypes(input,  supportedTypes, meanQueueDescString);
+    ValidateTensorDataTypesMatch(input, output, meanQueueDescString, "input", "output");
+
     if (m_Parameters.m_KeepDims)
     {
-        ValidateTensorNumDimensions(output, "MeanQueueDescriptor", input.GetNumDimensions(), "output");
+        ValidateTensorNumDimensions(output, meanQueueDescString, input.GetNumDimensions(), "output");
     }
     else if (m_Parameters.m_Axis.empty())
     {
-        ValidateTensorNumDimensions(output, "MeanQueueDescriptor", 1, "output");
+        ValidateTensorNumDimensions(output, meanQueueDescString, 1, "output");
     }
     else
     {
         auto outputDim = input.GetNumDimensions() - boost::numeric_cast<unsigned int>(m_Parameters.m_Axis.size());
         ValidateTensorNumDimensions(output,
-                                    "MeanQueueDescriptor",
+                                    meanQueueDescString,
                                     outputDim > 0 ? outputDim : 1,
                                     "output");
     }