| /* |
| * Copyright (c) 2018-2020 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #include "arm_compute/graph/backends/CL/CLFunctionFactory.h" |
| |
| #include "arm_compute/core/utils/misc/Cast.h" |
| #include "arm_compute/graph/Graph.h" |
| #include "arm_compute/graph/GraphContext.h" |
| #include "arm_compute/graph/backends/FunctionHelpers.h" |
| #include "arm_compute/runtime/CL/CLFunctions.h" |
| #include "arm_compute/runtime/CPP/CPPFunctions.h" |
| |
| using namespace arm_compute::utils::cast; |
| |
| namespace arm_compute |
| { |
| namespace graph |
| { |
| namespace backends |
| { |
| /** Target specific information structure used to pass information to the layer templates */ |
| struct CLTargetInfo |
| { |
| using TensorType = arm_compute::ICLTensor; |
| using SrcTensorType = const arm_compute::ICLTensor; |
| using TensorConcreteType = CLTensor; |
| static Target TargetType; |
| }; |
| |
| Target CLTargetInfo::TargetType = Target::CL; |
| |
| /** Collection of CL convolution functions */ |
| struct CLConvolutionLayerFunctions |
| { |
| using GenericConvolutionLayer = CLConvolutionLayer; |
| using GEMMConvolutionLayer = CLGEMMConvolutionLayer; |
| using DirectConvolutionLayer = CLDirectConvolutionLayer; |
| using WinogradConvolutionLayer = CLWinogradConvolutionLayer; |
| }; |
| |
| /** Collection of CL element-wise functions */ |
| struct CLEltwiseFunctions |
| { |
| using Addition = CLArithmeticAddition; |
| using Subtraction = CLArithmeticSubtraction; |
| using Multiplication = CLPixelWiseMultiplication; |
| using Maximum = CLElementwiseMax; |
| }; |
| |
| /** Collection of CL unary element-wise functions */ |
| struct CLUnaryEltwiseFunctions |
| { |
| using Exp = CLExpLayer; |
| }; |
| |
| /** Function and tensor types to be used inside a CL fused convolution/batch normalization layer */ |
| struct CLFusedLayerTypes |
| { |
| using ConvolutionLayer = CLConvolutionLayer; |
| using DepthwiseConvolutionLayer = CLDepthwiseConvolutionLayer; |
| using FuseBatchNormalization = CLFuseBatchNormalization; |
| }; |
| |
| // TODO (isagot01): Remove once we support heterogeneous scheduling at function level |
| /** Wrapper for the CPP Function in the OpenCL backend **/ |
| class CPPWrapperFunction : public IFunction |
| { |
| public: |
| /* Default constructor */ |
| CPPWrapperFunction() |
| : _tensors(), _func(nullptr) |
| { |
| } |
| |
| void run() override |
| { |
| for(auto &tensor : _tensors) |
| { |
| tensor->map(CLScheduler::get().queue()); |
| } |
| _func->run(); |
| |
| for(auto &tensor : _tensors) |
| { |
| tensor->unmap(CLScheduler::get().queue()); |
| } |
| } |
| |
| void register_tensor(ICLTensor *tensor) |
| { |
| _tensors.push_back(tensor); |
| } |
| |
| void register_function(std::unique_ptr<IFunction> function) |
| { |
| _func = std::move(function); |
| } |
| |
| private: |
| std::vector<arm_compute::ICLTensor *> _tensors; |
| std::unique_ptr<IFunction> _func; |
| }; |
| |
| namespace detail |
| { |
| // Specialized functions |
| template <> |
| std::unique_ptr<IFunction> create_detection_output_layer<CPPDetectionOutputLayer, CLTargetInfo>(DetectionOutputLayerNode &node) |
| { |
| validate_node<CLTargetInfo>(node, 3 /* expected inputs */, 1 /* expected outputs */); |
| |
| // Extract IO and info |
| CLTargetInfo::TensorType *input0 = get_backing_tensor<CLTargetInfo>(node.input(0)); |
| CLTargetInfo::TensorType *input1 = get_backing_tensor<CLTargetInfo>(node.input(1)); |
| CLTargetInfo::TensorType *input2 = get_backing_tensor<CLTargetInfo>(node.input(2)); |
| CLTargetInfo::TensorType *output = get_backing_tensor<CLTargetInfo>(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<CPPDetectionOutputLayer>(); |
| func->configure(input0, input1, input2, output, detect_info); |
| |
| // Log info |
| ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " |
| << node.name() |
| << " Type: " << node.type() |
| << " Target: " << CLTargetInfo::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); |
| |
| auto wrap_function = support::cpp14::make_unique<CPPWrapperFunction>(); |
| |
| wrap_function->register_function(std::move(func)); |
| wrap_function->register_tensor(input0); |
| wrap_function->register_tensor(input1); |
| wrap_function->register_tensor(input2); |
| wrap_function->register_tensor(output); |
| |
| return RETURN_UNIQUE_PTR(wrap_function); |
| } |
| template <> |
| std::unique_ptr<IFunction> create_detection_post_process_layer<CPPDetectionPostProcessLayer, CLTargetInfo>(DetectionPostProcessLayerNode &node) |
| { |
| validate_node<CLTargetInfo>(node, 3 /* expected inputs */, 4 /* expected outputs */); |
| |
| // Extract IO and info |
| CLTargetInfo::TensorType *input0 = get_backing_tensor<CLTargetInfo>(node.input(0)); |
| CLTargetInfo::TensorType *input1 = get_backing_tensor<CLTargetInfo>(node.input(1)); |
| CLTargetInfo::TensorType *input2 = get_backing_tensor<CLTargetInfo>(node.input(2)); |
| CLTargetInfo::TensorType *output0 = get_backing_tensor<CLTargetInfo>(node.output(0)); |
| CLTargetInfo::TensorType *output1 = get_backing_tensor<CLTargetInfo>(node.output(1)); |
| CLTargetInfo::TensorType *output2 = get_backing_tensor<CLTargetInfo>(node.output(2)); |
| CLTargetInfo::TensorType *output3 = get_backing_tensor<CLTargetInfo>(node.output(3)); |
| const DetectionPostProcessLayerInfo detect_info = node.detection_post_process_info(); |
| |
| ARM_COMPUTE_ERROR_ON(input0 == nullptr); |
| ARM_COMPUTE_ERROR_ON(input1 == nullptr); |
| ARM_COMPUTE_ERROR_ON(input2 == nullptr); |
| ARM_COMPUTE_ERROR_ON(output0 == nullptr); |
| ARM_COMPUTE_ERROR_ON(output1 == nullptr); |
| ARM_COMPUTE_ERROR_ON(output2 == nullptr); |
| ARM_COMPUTE_ERROR_ON(output3 == nullptr); |
| |
| // Create and configure function |
| auto func = support::cpp14::make_unique<CPPDetectionPostProcessLayer>(); |
| func->configure(input0, input1, input2, output0, output1, output2, output3, detect_info); |
| |
| // Log info |
| ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " |
| << node.name() |
| << " Type: " << node.type() |
| << " Target: " << CLTargetInfo::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() |
| << " Output0 shape: " << output0->info()->tensor_shape() |
| << " Output1 shape: " << output1->info()->tensor_shape() |
| << " Output2 shape: " << output2->info()->tensor_shape() |
| << " Output3 shape: " << output3->info()->tensor_shape() |
| << " DetectionPostProcessLayer info: " << detect_info |
| << std::endl); |
| |
| auto wrap_function = support::cpp14::make_unique<CPPWrapperFunction>(); |
| |
| wrap_function->register_function(std::move(func)); |
| wrap_function->register_tensor(input0); |
| wrap_function->register_tensor(input1); |
| wrap_function->register_tensor(input2); |
| wrap_function->register_tensor(output0); |
| wrap_function->register_tensor(output1); |
| wrap_function->register_tensor(output2); |
| wrap_function->register_tensor(output3); |
| |
| return RETURN_UNIQUE_PTR(wrap_function); |
| } |
| } // namespace detail |
| |
| std::unique_ptr<IFunction> CLFunctionFactory::create(INode *node, GraphContext &ctx) |
| { |
| if(node == nullptr) |
| { |
| return nullptr; |
| } |
| |
| NodeType type = node->type(); |
| switch(type) |
| { |
| case NodeType::ActivationLayer: |
| return detail::create_activation_layer<CLActivationLayer, CLTargetInfo>(*polymorphic_downcast<ActivationLayerNode *>(node)); |
| case NodeType::ArgMinMaxLayer: |
| return detail::create_arg_min_max_layer<CLArgMinMaxLayer, CLTargetInfo>(*polymorphic_downcast<ArgMinMaxLayerNode *>(node)); |
| case NodeType::BatchNormalizationLayer: |
| return detail::create_batch_normalization_layer<CLBatchNormalizationLayer, CLTargetInfo>(*polymorphic_downcast<BatchNormalizationLayerNode *>(node)); |
| case NodeType::BoundingBoxTransformLayer: |
| return detail::create_bounding_box_transform_layer<CLBoundingBoxTransform, CLTargetInfo>(*polymorphic_downcast<BoundingBoxTransformLayerNode *>(node)); |
| case NodeType::ChannelShuffleLayer: |
| return detail::create_channel_shuffle_layer<CLChannelShuffleLayer, CLTargetInfo>(*polymorphic_downcast<ChannelShuffleLayerNode *>(node)); |
| case NodeType::ConvolutionLayer: |
| return detail::create_convolution_layer<CLConvolutionLayerFunctions, CLTargetInfo>(*polymorphic_downcast<ConvolutionLayerNode *>(node), ctx); |
| case NodeType::DeconvolutionLayer: |
| return detail::create_deconvolution_layer<CLDeconvolutionLayer, CLTargetInfo>(*polymorphic_downcast<DeconvolutionLayerNode *>(node), ctx); |
| case NodeType::ConcatenateLayer: |
| return detail::create_concatenate_layer<CLConcatenateLayer, CLTargetInfo>(*polymorphic_downcast<ConcatenateLayerNode *>(node)); |
| case NodeType::DepthToSpaceLayer: |
| return detail::create_depth_to_space_layer<CLDepthToSpaceLayer, CLTargetInfo>(*polymorphic_downcast<DepthToSpaceLayerNode *>(node)); |
| case NodeType::DepthwiseConvolutionLayer: |
| return detail::create_depthwise_convolution_layer<CLDepthwiseConvolutionLayer, CLTargetInfo>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node)); |
| case NodeType::DequantizationLayer: |
| return detail::create_dequantization_layer<CLDequantizationLayer, CLTargetInfo>(*polymorphic_downcast<DequantizationLayerNode *>(node)); |
| case NodeType::DetectionOutputLayer: |
| return detail::create_detection_output_layer<CPPDetectionOutputLayer, CLTargetInfo>(*polymorphic_downcast<DetectionOutputLayerNode *>(node)); |
| case NodeType::DetectionPostProcessLayer: |
| return detail::create_detection_post_process_layer<CPPDetectionPostProcessLayer, CLTargetInfo>(*polymorphic_downcast<DetectionPostProcessLayerNode *>(node)); |
| case NodeType::EltwiseLayer: |
| return detail::create_eltwise_layer<CLEltwiseFunctions, CLTargetInfo>(*polymorphic_downcast<EltwiseLayerNode *>(node)); |
| case NodeType::UnaryEltwiseLayer: |
| return detail::create_unary_eltwise_layer<CLUnaryEltwiseFunctions, CLTargetInfo>(*polymorphic_downcast<UnaryEltwiseLayerNode *>(node)); |
| case NodeType::FlattenLayer: |
| return detail::create_flatten_layer<CLFlattenLayer, CLTargetInfo>(*polymorphic_downcast<FlattenLayerNode *>(node)); |
| case NodeType::FullyConnectedLayer: |
| return detail::create_fully_connected_layer<CLFullyConnectedLayer, CLTargetInfo>(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx); |
| case NodeType::FusedConvolutionBatchNormalizationLayer: |
| return detail::create_fused_convolution_batch_normalization_layer<CLFusedLayerTypes, CLTargetInfo>(*polymorphic_downcast<FusedConvolutionBatchNormalizationNode *>(node), ctx); |
| case NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer: |
| return detail::create_fused_depthwise_convolution_batch_normalization_layer<CLFusedLayerTypes, CLTargetInfo>(*polymorphic_downcast<FusedDepthwiseConvolutionBatchNormalizationNode *>(node), ctx); |
| case NodeType::GenerateProposalsLayer: |
| return detail::create_generate_proposals_layer<CLGenerateProposalsLayer, CLTargetInfo>(*polymorphic_downcast<GenerateProposalsLayerNode *>(node), ctx); |
| case NodeType::L2NormalizeLayer: |
| return detail::create_l2_normalize_layer<CLL2NormalizeLayer, CLTargetInfo>(*polymorphic_downcast<L2NormalizeLayerNode *>(node), ctx); |
| case NodeType::NormalizationLayer: |
| return detail::create_normalization_layer<CLNormalizationLayer, CLTargetInfo>(*polymorphic_downcast<NormalizationLayerNode *>(node), ctx); |
| case NodeType::NormalizePlanarYUVLayer: |
| return detail::create_normalize_planar_yuv_layer<CLNormalizePlanarYUVLayer, CLTargetInfo>(*polymorphic_downcast<NormalizePlanarYUVLayerNode *>(node)); |
| case NodeType::PadLayer: |
| return detail::create_pad_layer<CLPadLayer, CLTargetInfo>(*polymorphic_downcast<PadLayerNode *>(node)); |
| case NodeType::PermuteLayer: |
| return detail::create_permute_layer<CLPermute, CLTargetInfo>(*polymorphic_downcast<PermuteLayerNode *>(node)); |
| case NodeType::PoolingLayer: |
| return detail::create_pooling_layer<CLPoolingLayer, CLTargetInfo>(*polymorphic_downcast<PoolingLayerNode *>(node)); |
| case NodeType::PReluLayer: |
| return detail::create_prelu_layer<CLPReluLayer, CLTargetInfo>(*polymorphic_downcast<PReluLayerNode *>(node)); |
| case NodeType::PrintLayer: |
| return detail::create_print_layer<CLTargetInfo>(*polymorphic_downcast<PrintLayerNode *>(node)); |
| case NodeType::PriorBoxLayer: |
| return detail::create_priorbox_layer<CLPriorBoxLayer, CLTargetInfo>(*polymorphic_downcast<PriorBoxLayerNode *>(node)); |
| case NodeType::QuantizationLayer: |
| return detail::create_quantization_layer<CLQuantizationLayer, CLTargetInfo>(*polymorphic_downcast<QuantizationLayerNode *>(node)); |
| case NodeType::ReductionOperationLayer: |
| return detail::create_reduction_operation_layer<CLReductionOperation, CLTargetInfo>(*polymorphic_downcast<ReductionLayerNode *>(node), ctx); |
| case NodeType::ReorgLayer: |
| return detail::create_reorg_layer<CLReorgLayer, CLTargetInfo>(*polymorphic_downcast<ReorgLayerNode *>(node)); |
| case NodeType::ReshapeLayer: |
| return detail::create_reshape_layer<CLReshapeLayer, CLTargetInfo>(*polymorphic_downcast<ReshapeLayerNode *>(node)); |
| case NodeType::ResizeLayer: |
| return detail::create_resize_layer<CLScale, CLTargetInfo>(*polymorphic_downcast<ResizeLayerNode *>(node)); |
| case NodeType::ROIAlignLayer: |
| return detail::create_roi_align_layer<CLROIAlignLayer, CLTargetInfo>(*polymorphic_downcast<ROIAlignLayerNode *>(node)); |
| case NodeType::SliceLayer: |
| return detail::create_slice_layer<CLSlice, CLTargetInfo>(*polymorphic_downcast<SliceLayerNode *>(node)); |
| case NodeType::SoftmaxLayer: |
| return detail::create_softmax_layer<CLSoftmaxLayer, CLTargetInfo>(*polymorphic_downcast<SoftmaxLayerNode *>(node), ctx); |
| case NodeType::StackLayer: |
| return detail::create_stack_layer<CLStackLayer, CLTargetInfo>(*polymorphic_downcast<StackLayerNode *>(node)); |
| case NodeType::StridedSliceLayer: |
| return detail::create_strided_slice_layer<CLStridedSlice, CLTargetInfo>(*polymorphic_downcast<StridedSliceLayerNode *>(node)); |
| case NodeType::UpsampleLayer: |
| return detail::create_upsample_layer<CLUpsampleLayer, CLTargetInfo>(*polymorphic_downcast<UpsampleLayerNode *>(node), ctx); |
| case NodeType::YOLOLayer: |
| return detail::create_yolo_layer<CLYOLOLayer, CLTargetInfo>(*polymorphic_downcast<YOLOLayerNode *>(node), ctx); |
| default: |
| return nullptr; |
| } |
| } |
| } // namespace backends |
| } // namespace graph |
| } // namespace arm_compute |