diff options
Diffstat (limited to 'arm_compute/graph/backends')
-rw-r--r-- | arm_compute/graph/backends/FunctionHelpers.h | 45 | ||||
-rw-r--r-- | arm_compute/graph/backends/ValidateHelpers.h | 24 |
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 * |