xref: /aosp_15_r20/external/ComputeLibrary/src/graph/backends/NEON/NEFunctionFactory.cpp (revision c217d954acce2dbc11938adb493fc0abd69584f3)
1 /*
2  * Copyright (c) 2018-2021 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
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6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
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10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
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13  * The above copyright notice and this permission notice shall be included in all
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17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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24 #include "arm_compute/graph/backends/NEON/NEFunctionFactory.h"
25 
26 #include "arm_compute/graph/Graph.h"
27 #include "arm_compute/graph/GraphContext.h"
28 #include "arm_compute/graph/Logger.h"
29 #include "arm_compute/graph/TypePrinter.h"
30 #include "arm_compute/graph/backends/FunctionHelpers.h"
31 #include "arm_compute/graph/backends/Utils.h"
32 #include "arm_compute/graph/nodes/Nodes.h"
33 #include "arm_compute/runtime/CPP/CPPFunctions.h"
34 #include "arm_compute/runtime/NEON/NEFunctions.h"
35 #include "support/Cast.h"
36 #include "support/ToolchainSupport.h"
37 
38 using namespace arm_compute::utils::cast;
39 
40 namespace arm_compute
41 {
42 namespace graph
43 {
44 namespace backends
45 {
46 /** Target specific information structure used to pass information to the layer templates */
47 struct NETargetInfo
48 {
49     using TensorType         = arm_compute::ITensor;
50     using SrcTensorType      = const arm_compute::ITensor;
51     using TensorConcreteType = arm_compute::Tensor;
52     static Target TargetType;
53 };
54 
55 Target NETargetInfo::TargetType = Target::NEON;
56 
57 /** Collection of CPU convolution functions */
58 struct NEConvolutionLayerFunctions
59 {
60     using GenericConvolutionLayer  = NEConvolutionLayer;
61     using GEMMConvolutionLayer     = NEGEMMConvolutionLayer;
62     using DirectConvolutionLayer   = NEDirectConvolutionLayer;
63     using WinogradConvolutionLayer = NEWinogradConvolutionLayer;
64 };
65 
66 /** Collection of CPU element-wise functions */
67 struct NEEltwiseFunctions
68 {
69     using Addition       = NEArithmeticAddition;
70     using Subtraction    = NEArithmeticSubtraction;
71     using Multiplication = NEPixelWiseMultiplication;
72     using Maximum        = NEElementwiseMax;
73     using Division       = NEElementwiseDivision;
74 };
75 
76 /** Collection of CPU unary element-wise functions */
77 struct NEUnaryEltwiseFunctions
78 {
79     using Exp = NEExpLayer;
80 };
81 
82 /** Function and tensor types to be used inside a fused convolution/batch normalization layer */
83 struct NEFusedLayerTypes
84 {
85     using ConvolutionLayer          = NEConvolutionLayer;
86     using DepthwiseConvolutionLayer = NEDepthwiseConvolutionLayer;
87     using FuseBatchNormalization    = NEFuseBatchNormalization;
88 };
89 
90 namespace detail
91 {
92 template <>
create_normalization_layer(NormalizationLayerNode & node,GraphContext & ctx)93 std::unique_ptr<IFunction> create_normalization_layer<NENormalizationLayer, NETargetInfo>(NormalizationLayerNode &node, GraphContext &ctx)
94 {
95     validate_node<NETargetInfo>(node, 1 /* expected inputs */, 1 /* expected outputs */);
96 
97     // Extract IO and info
98     NETargetInfo::TensorType    *input     = get_backing_tensor<NETargetInfo>(node.input(0));
99     NETargetInfo::TensorType    *output    = get_backing_tensor<NETargetInfo>(node.output(0));
100     const NormalizationLayerInfo norm_info = node.normalization_info();
101     ARM_COMPUTE_ERROR_ON(input == nullptr);
102     ARM_COMPUTE_ERROR_ON(output == nullptr);
103 
104     // Create and configure function
105     auto func = std::make_unique<NENormalizationLayer>(get_memory_manager(ctx, NETargetInfo::TargetType));
106     func->configure(input, output, norm_info);
107 
108     // Log info
109     ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated "
110                                << node.name()
111                                << " Type: " << node.type()
112                                << " Target: " << NETargetInfo::TargetType
113                                << " Data Type: " << input->info()->data_type()
114                                << " Input shape: " << input->info()->tensor_shape()
115                                << " Output shape: " << output->info()->tensor_shape()
116                                << " Normalization info: " << norm_info.type()
117                                << std::endl);
118 
119     return std::move(func);
120 }
121 } // namespace detail
122 
create(INode * node,GraphContext & ctx)123 std::unique_ptr<IFunction> NEFunctionFactory::create(INode *node, GraphContext &ctx)
124 {
125     if(node == nullptr)
126     {
127         return nullptr;
128     }
129 
130     NodeType type = node->type();
131     switch(type)
132     {
133         case NodeType::ActivationLayer:
134             return detail::create_activation_layer<NEActivationLayer, NETargetInfo>(*polymorphic_downcast<ActivationLayerNode *>(node));
135         case NodeType::ArgMinMaxLayer:
136             return detail::create_arg_min_max_layer<NEArgMinMaxLayer, NETargetInfo>(*polymorphic_downcast<ArgMinMaxLayerNode *>(node));
137         case NodeType::BatchNormalizationLayer:
138             return detail::create_batch_normalization_layer<NEBatchNormalizationLayer, NETargetInfo>(*polymorphic_downcast<BatchNormalizationLayerNode *>(node));
139         case NodeType::ChannelShuffleLayer:
140             return detail::create_channel_shuffle_layer<NEChannelShuffleLayer, NETargetInfo>(*polymorphic_downcast<ChannelShuffleLayerNode *>(node));
141         case NodeType::ConvolutionLayer:
142             return detail::create_convolution_layer<NEConvolutionLayerFunctions, NETargetInfo>(*polymorphic_downcast<ConvolutionLayerNode *>(node), ctx);
143         case NodeType::DepthToSpaceLayer:
144             return detail::create_depth_to_space_layer<NEDepthToSpaceLayer, NETargetInfo>(*polymorphic_downcast<DepthToSpaceLayerNode *>(node));
145         case NodeType::DeconvolutionLayer:
146             return detail::create_deconvolution_layer<NEDeconvolutionLayer, NETargetInfo>(*polymorphic_downcast<DeconvolutionLayerNode *>(node), ctx);
147         case NodeType::ConcatenateLayer:
148             return detail::create_concatenate_layer<NEConcatenateLayer, NETargetInfo>(*polymorphic_downcast<ConcatenateLayerNode *>(node));
149         case NodeType::DepthwiseConvolutionLayer:
150             return detail::create_depthwise_convolution_layer<NEDepthwiseConvolutionLayer, NETargetInfo>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
151         case NodeType::DequantizationLayer:
152             return detail::create_dequantization_layer<NEDequantizationLayer, NETargetInfo>(*polymorphic_downcast<DequantizationLayerNode *>(node));
153         case NodeType::DetectionOutputLayer:
154             return detail::create_detection_output_layer<CPPDetectionOutputLayer, NETargetInfo>(*polymorphic_downcast<DetectionOutputLayerNode *>(node));
155         case NodeType::DetectionPostProcessLayer:
156             return detail::create_detection_post_process_layer<NEDetectionPostProcessLayer, NETargetInfo>(*polymorphic_downcast<DetectionPostProcessLayerNode *>(node));
157         case NodeType::EltwiseLayer:
158             return detail::create_eltwise_layer<NEEltwiseFunctions, NETargetInfo>(*polymorphic_downcast<EltwiseLayerNode *>(node));
159         case NodeType::UnaryEltwiseLayer:
160             return detail::create_unary_eltwise_layer<NEUnaryEltwiseFunctions, NETargetInfo>(*polymorphic_downcast<UnaryEltwiseLayerNode *>(node));
161         case NodeType::FlattenLayer:
162             return detail::create_flatten_layer<NEFlattenLayer, NETargetInfo>(*polymorphic_downcast<FlattenLayerNode *>(node));
163         case NodeType::FullyConnectedLayer:
164             return detail::create_fully_connected_layer<NEFullyConnectedLayer, NETargetInfo>(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx);
165         case NodeType::FusedConvolutionBatchNormalizationLayer:
166             return detail::create_fused_convolution_batch_normalization_layer<NEFusedLayerTypes, NETargetInfo>(*polymorphic_downcast<FusedConvolutionBatchNormalizationNode *>(node), ctx);
167         case NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer:
168             return detail::create_fused_depthwise_convolution_batch_normalization_layer<NEFusedLayerTypes, NETargetInfo>(*polymorphic_downcast<FusedDepthwiseConvolutionBatchNormalizationNode *>(node), ctx);
169         case NodeType::L2NormalizeLayer:
170             return detail::create_l2_normalize_layer<NEL2NormalizeLayer, NETargetInfo>(*polymorphic_downcast<L2NormalizeLayerNode *>(node), ctx);
171         case NodeType::NormalizationLayer:
172             return detail::create_normalization_layer<NENormalizationLayer, NETargetInfo>(*polymorphic_downcast<NormalizationLayerNode *>(node), ctx);
173         case NodeType::PadLayer:
174             return detail::create_pad_layer<NEPadLayer, NETargetInfo>(*polymorphic_downcast<PadLayerNode *>(node));
175         case NodeType::PermuteLayer:
176             return detail::create_permute_layer<NEPermute, NETargetInfo>(*polymorphic_downcast<PermuteLayerNode *>(node));
177         case NodeType::PoolingLayer:
178             return detail::create_pooling_layer<NEPoolingLayer, NETargetInfo>(*polymorphic_downcast<PoolingLayerNode *>(node));
179         case NodeType::PReluLayer:
180             return detail::create_prelu_layer<NEPReluLayer, NETargetInfo>(*polymorphic_downcast<PReluLayerNode *>(node));
181         case NodeType::PrintLayer:
182             return detail::create_print_layer<NETargetInfo>(*polymorphic_downcast<PrintLayerNode *>(node));
183         case NodeType::PriorBoxLayer:
184             return detail::create_priorbox_layer<NEPriorBoxLayer, NETargetInfo>(*polymorphic_downcast<PriorBoxLayerNode *>(node));
185         case NodeType::QuantizationLayer:
186             return detail::create_quantization_layer<NEQuantizationLayer, NETargetInfo>(*polymorphic_downcast<QuantizationLayerNode *>(node));
187         case NodeType::ReductionOperationLayer:
188             return detail::create_reduction_operation_layer<NEReductionOperation, NETargetInfo>(*polymorphic_downcast<ReductionLayerNode *>(node), ctx);
189         case NodeType::ReorgLayer:
190             return detail::create_reorg_layer<NEReorgLayer, NETargetInfo>(*polymorphic_downcast<ReorgLayerNode *>(node));
191         case NodeType::ReshapeLayer:
192             return detail::create_reshape_layer<NEReshapeLayer, NETargetInfo>(*polymorphic_downcast<ReshapeLayerNode *>(node));
193         case NodeType::ResizeLayer:
194             return detail::create_resize_layer<NEScale, NETargetInfo>(*polymorphic_downcast<ResizeLayerNode *>(node));
195         case NodeType::SliceLayer:
196             return detail::create_slice_layer<NESlice, NETargetInfo>(*polymorphic_downcast<SliceLayerNode *>(node));
197         case NodeType::SoftmaxLayer:
198             return detail::create_softmax_layer<NESoftmaxLayer, NETargetInfo>(*polymorphic_downcast<SoftmaxLayerNode *>(node), ctx);
199         case NodeType::StackLayer:
200             return detail::create_stack_layer<NEStackLayer, NETargetInfo>(*polymorphic_downcast<StackLayerNode *>(node));
201         case NodeType::StridedSliceLayer:
202             return detail::create_strided_slice_layer<NEStridedSlice, NETargetInfo>(*polymorphic_downcast<StridedSliceLayerNode *>(node));
203         default:
204             return nullptr;
205     }
206 }
207 } // namespace backends
208 } // namespace graph
209 } // namespace arm_compute
210