1 files changed, 48 insertions, 0 deletions
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 975e5fe55e..e21b8ed288 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -816,6 +816,54 @@ std::unique_ptr<IFunction> create_eltwise_layer(EltwiseLayerNode &node)
     return RETURN_UNIQUE_PTR(func);
 }
 
+/** Create a backend unary element-wise operation layer function
+ *
+ * @tparam UnaryEltwiseFunctions Backend unary element-wise function
+ * @tparam TargetInfo       Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend unary element-wise operation layer function
+ */
+template <typename UnaryEltwiseFunctions, typename TargetInfo>
+std::unique_ptr<IFunction> create_unary_eltwise_layer(UnaryEltwiseLayerNode &node)
+{
+    validate_node<TargetInfo>(node, 1 /* expected inputs */, 1 /* expected outputs */);
+
+    // Extract IO and info
+    typename TargetInfo::TensorType *input      = get_backing_tensor<TargetInfo>(node.input(0));
+    typename TargetInfo::TensorType *output     = get_backing_tensor<TargetInfo>(node.output(0));
+    const UnaryEltwiseOperation      eltwise_op = node.eltwise_descriptor().op;
+
+    ARM_COMPUTE_ERROR_ON(input == nullptr);
+    ARM_COMPUTE_ERROR_ON(output == nullptr);
+
+    std::unique_ptr<IFunction> func = nullptr;
+    std::string                func_name;
+    if(eltwise_op == UnaryEltwiseOperation::Exp)
+    {
+        std::tie(func, func_name) = create_named_function<typename UnaryEltwiseFunctions::Exp>(
+                                        std::string("Exp"),
+                                        input, output);
+    }
+    else
+    {
+        ARM_COMPUTE_ERROR("Unsupported unary element-wise operation!");
+    }
+
+    // Log info
+    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+                               << node.name()
+                               << " Type: " << node.type()
+                               << " Target: " << TargetInfo::TargetType
+                               << " Operation: " << func_name
+                               << " Data Type: " << input->info()->data_type()
+                               << " Shape: " << input->info()->tensor_shape()
+                               << std::endl);
+
+    return RETURN_UNIQUE_PTR(func);
+}
+
 /** Create a backend flatten layer function
  *
  * @tparam FlattenLayerFunction Backend flatten function