diff options
Diffstat (limited to 'arm_compute/graph/backends')
-rw-r--r-- | arm_compute/graph/backends/FunctionHelpers.h | 43 | ||||
-rw-r--r-- | arm_compute/graph/backends/ValidateHelpers.h | 22 |
2 files changed, 0 insertions, 65 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 diff --git a/arm_compute/graph/backends/ValidateHelpers.h b/arm_compute/graph/backends/ValidateHelpers.h index dd519fbd5e..df1c17697b 100644 --- a/arm_compute/graph/backends/ValidateHelpers.h +++ b/arm_compute/graph/backends/ValidateHelpers.h @@ -676,28 +676,6 @@ Status validate_upsample_layer(UpsampleLayerNode &node) // Validate function return UpsampleLayer::validate(input, output, node.info(), node.upsampling_policy()); } -/** Validates a YOLO layer node - * - * @tparam YOLOLayer YOLO layer type - * - * @param[in] node Node to validate - * - * @return Status - */ -template <typename YOLOLayer> -Status validate_yolo_layer(YOLOLayerNode &node) -{ - ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating YOLOLayer 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 input and output - 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 YOLOLayer::validate(input, output, node.activation_info(), node.num_classes()); -} /** Validates a element-wise layer node * * @param[in] node Node to validate |