1 files changed, 16 insertions, 3 deletions
diff --git a/src/armnn/layers/ElementwiseBaseLayer.hpp b/src/armnn/layers/ElementwiseBaseLayer.hpp
index f0821ecfe9..5c2bbaa054 100644
--- a/src/armnn/layers/ElementwiseBaseLayer.hpp
+++ b/src/armnn/layers/ElementwiseBaseLayer.hpp
@@ -10,17 +10,30 @@
 namespace armnn
 {
 
-/// NOTE: this is an abstract class, it does not implement:
-///  std::unique_ptr<IWorkload> Layer::CreateWorkload(const Graph& graph, const IWorkloadFactory& factory) const = 0;
-///  Layer* Clone(Graph& graph) const = 0;
+/// NOTE: this is an abstract class to encapsulate the element wise operations, it does not implement:
+/// std::unique_ptr<IWorkload> Layer::CreateWorkload(const Graph& graph, const IWorkloadFactory& factory) const = 0;
+/// Layer* Clone(Graph& graph) const = 0;
 class ElementwiseBaseLayer : public Layer
 {
 public:
+    /// Check if the input tensor shape(s)
+    /// will lead to a valid configuration of the element wise operation.
     void ValidateTensorShapesFromInputs() override;
+
+    /// By default returns inputShapes if the number of inputs are equal to number of outputs,
+    /// otherwise infers the output shapes from given input shapes and layer properties.
+    /// @param [in] inputShapes The input shapes layer has.
+    /// @return A vector to the inferred output shape.
     std::vector<TensorShape> InferOutputShapes(const std::vector<TensorShape>& inputShapes) const override;
 
 protected:
+    /// @param numInputSlots The number of input slots for the layer.
+    /// @param numOutputSlots The number of output slots for the layer.
+    /// @param type The layer type.
+    /// @param name Optional name for the layer.
     ElementwiseBaseLayer(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char* name);
+
+    /// Default destructor
     ~ElementwiseBaseLayer() = default;
 };