diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index a1cadcb..1968ec3 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -397,8 +397,10 @@
         biases->info()->set_data_type(DataType::S32);
     }
 
-    const PadStrideInfo              conv_info     = node.convolution_info();
-    const DepthwiseConvolutionMethod dwc_algorithm = node.depthwise_convolution_method();
+    const PadStrideInfo              conv_info        = node.convolution_info();
+    const DepthwiseConvolutionMethod dwc_algorithm    = node.depthwise_convolution_method();
+    const unsigned int               depth_multiplier = 1;
+    const ActivationLayerInfo        fused_act        = node.fused_activation();
 
     // Create and configure function (we assume that functions have been validated before creation)
     std::unique_ptr<IFunction> func;
@@ -407,13 +409,13 @@
     {
         std::tie(func, func_name) = create_named_function<typename DepthwiseConvolutionLayerFunctions::DepthwiseConvolutionLayer3x3>(
                                         std::string("DepthwiseConvolutionLayer3x3"),
-                                        input, weights, biases, output, conv_info);
+                                        input, weights, biases, output, conv_info, depth_multiplier, fused_act);
     }
     else
     {
         std::tie(func, func_name) = create_named_function<typename DepthwiseConvolutionLayerFunctions::GenericDepthwiseConvolutionLayer>(
                                         std::string("DepthwiseConvolutionLayer"),
-                                        input, weights, biases, output, conv_info);
+                                        input, weights, biases, output, conv_info, depth_multiplier, fused_act);
     }
 
     // Log info
@@ -431,6 +433,7 @@
                                << " Input shape: " << input->info()->tensor_shape()
                                << " Weights shape: " << weights->info()->tensor_shape()
                                << " Output shape: " << output->info()->tensor_shape()
+                               << (fused_act.enabled() ? " " + to_string(fused_act.activation()) : "")
                                << std::endl);
     return func;
 }