IVGCVSW-3418 Add Arm NN front end support for the new Stack layer

 * Added new StackLayer class
 * Made necessary changes to Descriptors, ILayerSupport, ILayerVisitor, etc.
 * Added unit tests

Signed-off-by: Matthew Jackson <matthew.jackson@arm.com>
Change-Id: Ieb97a928a342ffe1901c6058eb895711c358fd3d

1 files changed, 85 insertions, 0 deletions

diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index 324c1debc0..878602391c 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -582,6 +582,91 @@ void ConcatQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
 }
 
 //---------------------------------------------------------------
+void StackQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
+{
+    ValidateNumOutputs(workloadInfo, "StackQueueDescriptor", 1);
+
+    if (m_Parameters.m_NumInputs != workloadInfo.m_InputTensorInfos.size())
+    {
+        throw InvalidArgumentException("StackQueueDescriptor: Must have the defined number of input tensors.");
+    }
+
+    // All inputs must have the same shape, which is defined in parameters
+    const TensorShape& inputShape = m_Parameters.m_InputShape;
+    for (unsigned int i = 0; i < workloadInfo.m_InputTensorInfos.size(); ++i)
+    {
+        if (workloadInfo.m_InputTensorInfos[i].GetShape() != inputShape)
+        {
+            throw InvalidArgumentException("StackQueueDescriptor: All input tensor shapes "
+                                           "must match the defined shape.");
+        }
+    }
+
+    // m_Axis is 0-based and may take values from 0 to the number of input dimensions (inclusive),
+    // since the output tensor has an additional dimension.
+    if (m_Parameters.m_Axis > inputShape.GetNumDimensions())
+    {
+        throw InvalidArgumentException("StackQueueDescriptor: Axis may not be greater "
+                                       "than the number of input dimensions.");
+    }
+
+    // Output shape must be as inferred from the input shape
+    const TensorShape& outputShape = workloadInfo.m_OutputTensorInfos[0].GetShape();
+    for (unsigned int i = 0; i < m_Parameters.m_Axis; ++i)
+    {
+        if (outputShape[i] != inputShape[i])
+        {
+            throw InvalidArgumentException("StackQueueDescriptor: Output tensor must "
+                                           "match shape inferred from input tensor.");
+        }
+    }
+
+    if (outputShape[m_Parameters.m_Axis] != m_Parameters.m_NumInputs)
+    {
+        throw InvalidArgumentException("StackQueueDescriptor: Output tensor must "
+                                       "match shape inferred from input tensor.");
+    }
+
+    for (unsigned int i = m_Parameters.m_Axis + 1; i < inputShape.GetNumDimensions() + 1; ++i)
+    {
+        if (outputShape[i] != inputShape[i-1])
+        {
+            throw InvalidArgumentException("StackQueueDescriptor: Output tensor must "
+                                           "match shape inferred from input tensor.");
+        }
+    }
+
+    // Check the supported data types
+    std::vector<DataType> supportedTypes =
+    {
+            DataType::Float32,
+            DataType::Float16,
+            DataType::Boolean,
+            DataType::Signed32,
+            DataType::QuantisedAsymm8,
+            DataType::QuantisedSymm16
+    };
+
+    ValidateDataTypes(workloadInfo.m_InputTensorInfos[0],
+                      supportedTypes,
+                      "StackQueueDescriptor");
+
+    for (unsigned int i = 1; i < workloadInfo.m_InputTensorInfos.size(); ++i)
+    {
+        ValidateTensorDataTypesMatch(workloadInfo.m_InputTensorInfos[0],
+                                     workloadInfo.m_InputTensorInfos[i],
+                                     "StackQueueDescriptor",
+                                     "InputTensor[0]",
+                                     "InputTensor[" + std::to_string(i) + "]");
+    }
+    ValidateTensorDataTypesMatch(workloadInfo.m_InputTensorInfos[0],
+                                 workloadInfo.m_OutputTensorInfos[0],
+                                 "StackQueueDescriptor",
+                                 "InputTensor[0]",
+                                 "OutputTensor[0]");
+}
+
+//---------------------------------------------------------------
 void FullyConnectedQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
 {
     ValidateNumInputs(workloadInfo, "FullyConnectedQueueDescriptor", 1);