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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2020-12-04 15:51:34 +0000 |
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committer | Michele Di Giorgio <michele.digiorgio@arm.com> | 2020-12-10 10:44:54 +0000 |
commit | 0b1c2db5c29ed80b7f4dd0c4fd6d4ed91b3d1538 (patch) | |
tree | 4d59e2627ad5d094ff80976488a5488982764d85 /arm_compute/graph/backends/FunctionHelpers.h | |
parent | ec2256b81e6d6f655dcfbc76683738fbfeb82bcc (diff) | |
download | ComputeLibrary-0b1c2db5c29ed80b7f4dd0c4fd6d4ed91b3d1538.tar.gz |
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>
Diffstat (limited to 'arm_compute/graph/backends/FunctionHelpers.h')
-rw-r--r-- | arm_compute/graph/backends/FunctionHelpers.h | 43 |
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 |