Remove (NE/CL)YoloLayer support

YOLO layer is too specialized and specific to a single model type. Can
be decomposed using split, activation and concatenate layers

Partially Resolves: COMPMID-3996

Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I3cde88f8d4cc7d8c70ce1bb3b32b00f8d09bdca2
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4678
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>

1 files changed, 0 insertions, 43 deletions

diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 05bd483cfd..18fdb9f3bb 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -1885,49 +1885,6 @@ std::unique_ptr<IFunction> create_upsample_layer(UpsampleLayerNode &node, GraphC
 
     return RETURN_UNIQUE_PTR(func);
 }
-/** Create a backend YOLO layer function
- *
- * @tparam YoloLayerFunction Backend YOLO function
- * @tparam TargetInfo        Target-specific information
- *
- * @param[in] node Node to create the backend function for
- * @param[in] ctx  Graph context
- *
- * @return Backend YOLO layer function
- */
-template <typename YOLOlayerFunction, typename TargetInfo>
-std::unique_ptr<IFunction> create_yolo_layer(YOLOLayerNode &node, GraphContext &ctx)
-{
-    ARM_COMPUTE_UNUSED(ctx);
-    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 ActivationLayerInfo        act_info    = node.activation_info();
-    const int32_t                    num_classes = node.num_classes();
-    ARM_COMPUTE_ERROR_ON(num_classes <= 0);
-    ARM_COMPUTE_ERROR_ON(input == nullptr);
-    ARM_COMPUTE_ERROR_ON(output == nullptr);
-
-    // Create and configure function
-    auto func = std::make_unique<YOLOlayerFunction>();
-    func->configure(input, output, act_info, num_classes);
-
-    // 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()
-                               << " Activation function: " << act_info.activation()
-                               << " Num classes: " << num_classes
-                               << std::endl);
-
-    return RETURN_UNIQUE_PTR(func);
-}
 } // namespace detail
 } // namespace backends
 } // namespace graph