COMPMID-1808: Add Detection Output Layer to the GraphAPI

COMPMID-1710: Integrate Detection ouput in MobilenetSSD graph example

Change-Id: I384d1eb492ef14ece58f2023ad7bbc16f834450b
Reviewed-on: https://review.mlplatform.org/356
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

2 files changed, 69 insertions, 0 deletions

diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 3e71e3922a..96adffee46 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -489,6 +489,51 @@ std::unique_ptr<IFunction> create_depthwise_convolution_layer(DepthwiseConvoluti
     return func;
 }
 
+/** Create a backend detection output layer function
+ *
+ * @tparam DetectionOutputLayer Function Backend detection output function
+ * @tparam TargetInfo           Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend detection output layer function
+ */
+template <typename DetectionOutputLayerFunction, typename TargetInfo>
+std::unique_ptr<IFunction> create_detection_output_layer(DetectionOutputLayerNode &node)
+{
+    validate_node<TargetInfo>(node, 3 /* expected inputs */, 1 /* expected outputs */);
+
+    // Extract IO and info
+    typename TargetInfo::TensorType *input0      = get_backing_tensor<TargetInfo>(node.input(0));
+    typename TargetInfo::TensorType *input1      = get_backing_tensor<TargetInfo>(node.input(1));
+    typename TargetInfo::TensorType *input2      = get_backing_tensor<TargetInfo>(node.input(2));
+    typename TargetInfo::TensorType *output      = get_backing_tensor<TargetInfo>(node.output(0));
+    const DetectionOutputLayerInfo   detect_info = node.detection_output_info();
+
+    ARM_COMPUTE_ERROR_ON(input0 == nullptr);
+    ARM_COMPUTE_ERROR_ON(input1 == nullptr);
+    ARM_COMPUTE_ERROR_ON(input2 == nullptr);
+    ARM_COMPUTE_ERROR_ON(output == nullptr);
+
+    // Create and configure function
+    auto func = support::cpp14::make_unique<DetectionOutputLayerFunction>();
+    func->configure(input0, input1, input2, output, detect_info);
+
+    // Log info
+    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+                               << node.name()
+                               << " Type: " << node.type()
+                               << " Target: " << TargetInfo::TargetType
+                               << " Data Type: " << input0->info()->data_type()
+                               << " Input0 shape: " << input0->info()->tensor_shape()
+                               << " Input1 shape: " << input1->info()->tensor_shape()
+                               << " Input2 shape: " << input2->info()->tensor_shape()
+                               << " Output shape: " << output->info()->tensor_shape()
+                               << " DetectionOutputLayer info: " << detect_info
+                               << std::endl);
+
+    return std::move(func);
+}
 /** Create a backend element-wise operation layer function
  *
  * @tparam EltwiseFunctions Backend element-wise function
diff --git a/arm_compute/graph/backends/ValidateHelpers.h b/arm_compute/graph/backends/ValidateHelpers.h
index 75e2363f82..f1e53613ab 100644
--- a/arm_compute/graph/backends/ValidateHelpers.h
+++ b/arm_compute/graph/backends/ValidateHelpers.h
@@ -203,6 +203,30 @@ Status validate_depthwise_convolution_layer(DepthwiseConvolutionLayerNode &node)
 
     return status;
 }
+/** Validates a detection output layer node
+ *
+ * @tparam DetectionOutputLayer DetectionOutput layer type
+ *
+ * @param[in] node Node to validate
+ *
+ * @return Status
+ */
+template <typename DetectionOutputLayer>
+Status validate_detection_output_layer(DetectionOutputLayerNode &node)
+{
+    ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating DetectionOutputLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl);
+    ARM_COMPUTE_RETURN_ERROR_ON(node.num_inputs() != 3);
+    ARM_COMPUTE_RETURN_ERROR_ON(node.num_outputs() != 1);
+
+    // Extract IO and info
+    arm_compute::ITensorInfo      *input0      = get_backing_tensor_info(node.input(0));
+    arm_compute::ITensorInfo      *input1      = get_backing_tensor_info(node.input(1));
+    arm_compute::ITensorInfo      *input2      = get_backing_tensor_info(node.input(2));
+    arm_compute::ITensorInfo      *output      = get_backing_tensor_info(node.output(0));
+    const DetectionOutputLayerInfo detect_info = node.detection_output_info();
+
+    return DetectionOutputLayer::validate(input0, input1, input2, output, detect_info);
+}
 
 /** Validates a Generate Proposals layer node
  *