COMPMID-3791: Add support for all activation types in NodeFusionMutator

Change-Id: I9b548966201c00df8290fea7acf55c2173b0e0aa
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4011
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 10 insertions, 9 deletions

diff --git a/src/graph/mutators/NodeFusionMutator.cpp b/src/graph/mutators/NodeFusionMutator.cpp
index afc4452202..2a80825b36 100644
--- a/src/graph/mutators/NodeFusionMutator.cpp
+++ b/src/graph/mutators/NodeFusionMutator.cpp
@@ -300,10 +300,11 @@ IGraphMutator::MutationType NodeFusionMutator::type() const
 void NodeFusionMutator::mutate(Graph &g)
 {
     // Supported activations when fusing
-    const std::set<Activation> supported_fused_activations_conv    = { Activation::RELU, Activation::BOUNDED_RELU, Activation::LU_BOUNDED_RELU };
-    const std::set<Activation> supported_fused_activations_eltwise = { Activation::RELU, Activation::BOUNDED_RELU, Activation::LU_BOUNDED_RELU,
-                                                                       Activation::TANH, Activation::LOGISTIC
-                                                                     };
+    const std::set<Activation> supported_fused_activations    = { Activation::ABS, Activation::BOUNDED_RELU, Activation::ELU,
+                                                                  Activation::HARD_SWISH, Activation::IDENTITY, Activation::LEAKY_RELU,
+                                                                  Activation::LINEAR, Activation::LOGISTIC, Activation::LU_BOUNDED_RELU,
+                                                                  Activation::RELU, Activation::SOFT_RELU, Activation::SQRT,
+                                                                  Activation::SQUARE, Activation::TANH  };
 
     // Preconditions
     auto empty_prec = [](INode &)
@@ -328,11 +329,11 @@ void NodeFusionMutator::mutate(Graph &g)
     };
 
     // Fusion mutations
-    detail::fuse_layer<BatchNormalizationLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<BatchNormalizationLayerNode>, supported_fused_activations_conv);
-    detail::fuse_layer<ConvolutionLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<ConvolutionLayerNode>, supported_fused_activations_conv);
-    detail::fuse_layer<DepthwiseConvolutionLayerNode, ActivationLayerNode>(g, qs8_prec, detail::fuse_node_with_activation<DepthwiseConvolutionLayerNode>, supported_fused_activations_conv);
-    detail::fuse_layer<FullyConnectedLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<FullyConnectedLayerNode>, supported_fused_activations_conv);
-    detail::fuse_layer<EltwiseLayerNode, ActivationLayerNode>(g, cl_target_prec, detail::fuse_node_with_activation<EltwiseLayerNode>, supported_fused_activations_eltwise);
+    detail::fuse_layer<BatchNormalizationLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<BatchNormalizationLayerNode>, supported_fused_activations);
+    detail::fuse_layer<ConvolutionLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<ConvolutionLayerNode>, supported_fused_activations);
+    detail::fuse_layer<DepthwiseConvolutionLayerNode, ActivationLayerNode>(g, qs8_prec, detail::fuse_node_with_activation<DepthwiseConvolutionLayerNode>, supported_fused_activations);
+    detail::fuse_layer<FullyConnectedLayerNode, ActivationLayerNode>(g, empty_prec, detail::fuse_node_with_activation<FullyConnectedLayerNode>, supported_fused_activations);
+    detail::fuse_layer<EltwiseLayerNode, ActivationLayerNode>(g, cl_target_prec, detail::fuse_node_with_activation<EltwiseLayerNode>, supported_fused_activations);
     detail::fuse_layer<ConvolutionLayerNode, BatchNormalizationLayerNode>(g, empty_prec, detail::fuse_convolution_with_batch_normalization);
     detail::fuse_layer<DepthwiseConvolutionLayerNode, BatchNormalizationLayerNode>(g, empty_prec, detail::fuse_depthwise_convolution_with_batch_normalization);
 }