Add ArgMinMax layer node to Graph API

Change-Id: I2ccb2c65edd2932b76e905af3d747324b65c2f7f
Signed-off-by: thecha01 <theo.charalambous@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3910
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

2 files changed, 60 insertions, 0 deletions

diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 5b0e7d174c..05695fb797 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -131,6 +131,43 @@ std::unique_ptr<IFunction> create_activation_layer(ActivationLayerNode &node)
     return RETURN_UNIQUE_PTR(func);
 }
 
+/** Creates a backend argminmax layer function
+ *
+ * @tparam ArgMinMaxLayerFunction Backend activation function
+ * @tparam TargetInfo             Target-specific information
+ *
+ * @param[in] node Node to create the backend function for
+ *
+ * @return Backend argminmax layer function
+ */
+template <typename ArgMinMaxLayerFunction, typename TargetInfo>
+std::unique_ptr<IFunction> create_arg_min_max_layer(ArgMinMaxLayerNode &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 ReductionOperation         op     = node.reduction_operation();
+    unsigned int                     axis   = node.axis();
+
+    // Create function
+    auto func = support::cpp14::make_unique<ArgMinMaxLayerFunction>();
+    func->configure(input, axis, output, op);
+
+    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
+                               << node.name()
+                               << " Type: " << node.type()
+                               << " Target: " << TargetInfo::TargetType
+                               << " Data Type: " << input->info()->data_type()
+                               << " Shape: " << input->info()->tensor_shape()
+                               << " Reduction Operation: " << op
+                               << " axis: " << axis
+                               << std::endl);
+
+    return RETURN_UNIQUE_PTR(func);
+}
+
 /** Create a backend batch normalization layer function
  *
  * @tparam BatchNormalizationLayerFunction Backend batch normalization function
diff --git a/arm_compute/graph/backends/ValidateHelpers.h b/arm_compute/graph/backends/ValidateHelpers.h
index fcebc5c418..23f6cc5627 100644
--- a/arm_compute/graph/backends/ValidateHelpers.h
+++ b/arm_compute/graph/backends/ValidateHelpers.h
@@ -52,6 +52,29 @@ inline arm_compute::ITensorInfo *get_backing_tensor_info(arm_compute::graph::Ten
     return ((tensor == nullptr) || (tensor->handle() == nullptr)) ? nullptr : tensor->handle()->tensor().info();
 }
 
+/** Validates a ArgMinMax layer node
+ *
+ * @tparam ArgMinMax layer function type
+ *
+ * @param[in] node Node to validate
+ *
+ * @return Status
+ */
+template <typename ArgMinMaxLayer>
+Status validate_arg_min_max_layer(ArgMinMaxLayerNode &node)
+{
+    ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating ArgMinMaxLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl);
+    ARM_COMPUTE_RETURN_ERROR_ON(node.num_inputs() != 1);
+    ARM_COMPUTE_RETURN_ERROR_ON(node.num_outputs() != 1);
+
+    // Extract IO and info
+    arm_compute::ITensorInfo *input  = detail::get_backing_tensor_info(node.input(0));
+    arm_compute::ITensorInfo *output = get_backing_tensor_info(node.output(0));
+
+    // Validate function
+    return ArgMinMaxLayer::validate(input, node.axis(), output, node.reduction_operation());
+}
+
 /** Validates a Bounding Box Transform layer node
  *
  * @tparam BoundingBoxTransformLayer  Bounding Box Transform layer function type