Use X macro for the enum class LayerType

In order to improve the maintability of the LayerType enum,
it is easier to use the X macro technique https://en.wikipedia.org/wiki/X_Macro
Thanks to that, the pre-processor can generate some code based on the
list provided by the LIST_OF_LAYER_TYPE macro

Signed-off-by: Laurent Carlier <laurent.carlier@arm.com>
Change-Id: I3a6049abfb1e964fe0bf32aa4e26bec4e29a77de

2 files changed, 75 insertions, 123 deletions

diff --git a/src/armnn/InternalTypes.cpp b/src/armnn/InternalTypes.cpp
index a9435b29f5..aebc721be3 100644
--- a/src/armnn/InternalTypes.cpp
+++ b/src/armnn/InternalTypes.cpp
@@ -14,66 +14,9 @@ char const* GetLayerTypeAsCString(LayerType type)
 {
     switch (type)
     {
-        case LayerType::Activation: return "Activation";
-        case LayerType::Addition: return "Addition";
-        case LayerType::ArgMinMax: return "ArgMinMax";
-        case LayerType::BatchNormalization: return "BatchNormalization";
-        case LayerType::BatchToSpaceNd: return "BatchToSpaceNd";
-        case LayerType::Comparison: return "Comparison";
-        case LayerType::Concat: return "Concat";
-        case LayerType::Constant: return "Constant";
-        case LayerType::ConvertBf16ToFp32: return "ConvertBf16ToFp32";
-        case LayerType::ConvertFp16ToFp32: return "ConvertFp16ToFp32";
-        case LayerType::ConvertFp32ToBf16: return "ConvertFp32ToBf16";
-        case LayerType::ConvertFp32ToFp16: return "ConvertFp32ToFp16";
-        case LayerType::Convolution2d: return "Convolution2d";
-        case LayerType::Debug: return "Debug";
-        case LayerType::DepthToSpace: return "DepthToSpace";
-        case LayerType::DepthwiseConvolution2d: return "DepthwiseConvolution2d";
-        case LayerType::Dequantize: return "Dequantize";
-        case LayerType::DetectionPostProcess: return "DetectionPostProcess";
-        case LayerType::Division: return "Division";
-        case LayerType::ElementwiseUnary: return "ElementwiseUnary";
-        case LayerType::FakeQuantization: return "FakeQuantization";
-        case LayerType::Floor: return "Floor";
-        case LayerType::FullyConnected: return "FullyConnected";
-        case LayerType::Gather: return "Gather";
-        case LayerType::Input: return "Input";
-        case LayerType::InstanceNormalization: return "InstanceNormalization";
-        case LayerType::L2Normalization: return "L2Normalization";
-        case LayerType::LogSoftmax: return "LogSoftmax";
-        case LayerType::Lstm: return "Lstm";
-        case LayerType::Maximum: return "Maximum";
-        case LayerType::Mean: return "Mean";
-        case LayerType::MemCopy: return "MemCopy";
-        case LayerType::MemImport: return "MemImport";
-        case LayerType::Merge: return "Merge";
-        case LayerType::Minimum: return "Minimum";
-        case LayerType::Multiplication: return "Multiplication";
-        case LayerType::Normalization: return "Normalization";
-        case LayerType::Output: return "Output";
-        case LayerType::Pad: return "Pad";
-        case LayerType::Permute: return "Permute";
-        case LayerType::Pooling2d: return "Pooling2d";
-        case LayerType::PreCompiled: return "PreCompiled";
-        case LayerType::Prelu: return "Prelu";
-        case LayerType::Quantize:  return "Quantize";
-        case LayerType::QLstm: return "QLstm";
-        case LayerType::QuantizedLstm: return "QuantizedLstm";
-        case LayerType::Reshape: return "Reshape";
-        case LayerType::Resize: return "Resize";
-        case LayerType::Slice: return "Slice";
-        case LayerType::Softmax: return "Softmax";
-        case LayerType::SpaceToBatchNd: return "SpaceToBatchNd";
-        case LayerType::SpaceToDepth: return "SpaceToDepth";
-        case LayerType::Splitter: return "Splitter";
-        case LayerType::Stack: return "Stack";
-        case LayerType::StandIn: return "StandIn";
-        case LayerType::StridedSlice: return "StridedSlice";
-        case LayerType::Subtraction: return "Subtraction";
-        case LayerType::Switch: return "Switch";
-        case LayerType::TransposeConvolution2d: return "TransposeConvolution2d";
-        case LayerType::Transpose: return "Transpose";
+#define X(name) case LayerType::name: return #name;
+      LIST_OF_LAYER_TYPE
+#undef X
         default:
             ARMNN_ASSERT_MSG(false, "Unknown layer type");
             return "Unknown";
diff --git a/src/armnn/InternalTypes.hpp b/src/armnn/InternalTypes.hpp
index ee4a710d14..455cb60d5d 100644
--- a/src/armnn/InternalTypes.hpp
+++ b/src/armnn/InternalTypes.hpp
@@ -8,74 +8,83 @@
 
 #include <array>
 
+
+/// This list uses X macro technique.
+/// See https://en.wikipedia.org/wiki/X_Macro for more info
+#define LIST_OF_LAYER_TYPE \
+    X(Activation) \
+    X(Addition) \
+    X(ArgMinMax) \
+    X(BatchNormalization) \
+    X(BatchToSpaceNd) \
+    X(Comparison) \
+    X(Concat) \
+    X(Constant) \
+    X(ConvertBf16ToFp32) \
+    X(ConvertFp16ToFp32) \
+    X(ConvertFp32ToBf16) \
+    X(ConvertFp32ToFp16) \
+    X(Convolution2d) \
+    X(Debug) \
+    X(DepthToSpace) \
+    X(DepthwiseConvolution2d) \
+    X(Dequantize) \
+    X(DetectionPostProcess) \
+    X(Division) \
+    X(ElementwiseUnary) \
+    X(FakeQuantization) \
+    X(Floor) \
+    X(FullyConnected) \
+    X(Gather) \
+    X(Input) \
+    X(InstanceNormalization) \
+    X(L2Normalization) \
+    X(LogSoftmax) \
+    X(Lstm) \
+    X(QLstm) \
+    X(Maximum) \
+    X(Mean) \
+    X(MemCopy) \
+    X(MemImport) \
+    X(Merge) \
+    X(Minimum) \
+    X(Multiplication) \
+    X(Normalization) \
+    X(Output) \
+    X(Pad) \
+    X(Permute) \
+    X(Pooling2d) \
+    X(PreCompiled) \
+    X(Prelu) \
+    X(Quantize) \
+    X(QuantizedLstm) \
+    X(Reshape) \
+    X(Resize) \
+    X(Slice) \
+    X(Softmax) \
+    X(SpaceToBatchNd) \
+    X(SpaceToDepth) \
+    X(Splitter) \
+    X(Stack) \
+    X(StandIn) \
+    X(StridedSlice) \
+    X(Subtraction) \
+    X(Switch) \
+    X(Transpose) \
+    X(TransposeConvolution2d)
+
+/// When adding a new layer, adapt also the LastLayer enum value in the
+/// enum class LayerType below
 namespace armnn
 {
 
 enum class LayerType
 {
-    FirstLayer,
-    Activation = FirstLayer,
-    Addition,
-    ArgMinMax,
-    BatchNormalization,
-    BatchToSpaceNd,
-    Comparison,
-    Concat,
-    Constant,
-    ConvertBf16ToFp32,
-    ConvertFp16ToFp32,
-    ConvertFp32ToBf16,
-    ConvertFp32ToFp16,
-    Convolution2d,
-    Debug,
-    DepthToSpace,
-    DepthwiseConvolution2d,
-    Dequantize,
-    DetectionPostProcess,
-    Division,
-    ElementwiseUnary,
-    FakeQuantization,
-    Floor,
-    FullyConnected,
-    Gather,
-    Input,
-    InstanceNormalization,
-    L2Normalization,
-    LogSoftmax,
-    Lstm,
-    Maximum,
-    Mean,
-    MemCopy,
-    MemImport,
-    Merge,
-    Minimum,
-    Multiplication,
-    Normalization,
-    Output,
-    Pad,
-    Permute,
-    Pooling2d,
-    PreCompiled,
-    Prelu,
-    Quantize,
-    QLstm,
-    QuantizedLstm,
-    Reshape,
-    Resize,
-    Slice,
-    Softmax,
-    SpaceToBatchNd,
-    SpaceToDepth,
-    Splitter,
-    Stack,
-    StandIn,
-    StridedSlice,
-    Subtraction,
-    Switch,
-    TransposeConvolution2d,
-    // Last layer goes here.
-    LastLayer,
-    Transpose = LastLayer
+#define X(name) name,
+  LIST_OF_LAYER_TYPE
+#undef X
+  FirstLayer = Activation,
+  LastLayer = TransposeConvolution2d
 };
 
 const char* GetLayerTypeAsCString(LayerType type);