COMPMID-3083: Add graph support for PRelu

Change-Id: I48492f8c48b818b563bba1e0b48831ac5cdf1420
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2685
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 38 insertions, 0 deletions

diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 65a3e15a66..9f352edb9a 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -1149,6 +1149,44 @@ std::unique_ptr<IFunction> create_pooling_layer(PoolingLayerNode &node)
     return std::move(func);
 }
 
+/** Create a backend PRelu layer function
+ *
+ * @tparam PReluFunction Backend PRelu function
+ * @tparam TargetInfo    Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend PRelu layer function
+ */
+template <typename PReluFunction, typename TargetInfo>
+std::unique_ptr<IFunction> create_prelu_layer(PReluLayerNode &node)
+{
+    validate_node<TargetInfo>(node, 2 /* expected inputs */, 1 /* expected outputs */);
+
+    // Extract IO and info
+    typename TargetInfo::TensorType *input  = get_backing_tensor<TargetInfo>(node.input(0));
+    typename TargetInfo::TensorType *alpha  = get_backing_tensor<TargetInfo>(node.input(1));
+    typename TargetInfo::TensorType *output = get_backing_tensor<TargetInfo>(node.output(0));
+    ARM_COMPUTE_ERROR_ON(input == nullptr || alpha == nullptr);
+    ARM_COMPUTE_ERROR_ON(output == nullptr);
+
+    // Create and configure function
+    auto func = support::cpp14::make_unique<PReluFunction>();
+    func->configure(input, alpha, output);
+
+    // Log info
+    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+                               << node.name()
+                               << " Type: " << node.type()
+                               << " Target: " << TargetInfo::TargetType
+                               << " Data Type: " << input->info()->data_type()
+                               << " Input shape: " << input->info()->tensor_shape()
+                               << " Output shape: " << output->info()->tensor_shape()
+                               << std::endl);
+
+    return std::move(func);
+}
+
 /** Create a backend print layer function
  *
  * @tparam TargetInfo Target-specific information