xref: /aosp_15_r20/external/armnn/src/backends/reference/workloads/StridedSlice.cpp (revision 89c4ff92f2867872bb9e2354d150bf0c8c502810)
1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "StridedSlice.hpp"
7 
8 #include <ResolveType.hpp>
9 
10 #include <armnn/utility/Assert.hpp>
11 #include <armnn/utility/NumericCast.hpp>
12 
13 #include <cstring>
14 
15 namespace armnn
16 {
17 
18 namespace
19 {
20 
PadParams(StridedSliceDescriptor & p,unsigned int dimCount)21 void PadParams(StridedSliceDescriptor& p, unsigned int dimCount)
22 {
23     ARMNN_ASSERT_MSG(dimCount <= 4, "Expected input with at most 4 dimensions");
24 
25     const unsigned int beginIndicesCount =
26         armnn::numeric_cast<unsigned int>(p.m_Begin.size());
27 
28     ARMNN_ASSERT(dimCount >= beginIndicesCount);
29     const unsigned int padCount = dimCount - beginIndicesCount;
30 
31     p.m_Begin.resize(dimCount);
32     p.m_End.resize(dimCount);
33     p.m_Stride.resize(dimCount);
34 
35     for (unsigned int i = beginIndicesCount; i > 0; --i)
36     {
37         p.m_Stride[i + padCount - 1] = p.m_Stride[i - 1];
38         p.m_Begin[i + padCount - 1] = p.m_Begin[i - 1];
39         p.m_End[i + padCount - 1] = p.m_End[i - 1];
40     }
41 
42     for (unsigned int i = 0; i < padCount; ++i)
43     {
44         p.m_Stride[i] = 1;
45         p.m_Begin[i] = 0;
46         p.m_End[i] = 0;
47     }
48 
49     p.m_ShrinkAxisMask <<= padCount;
50     p.m_EllipsisMask <<= padCount;
51     p.m_NewAxisMask <<= padCount;
52     p.m_BeginMask <<= padCount;
53     p.m_EndMask <<= padCount;
54     p.m_BeginMask |= (1 << padCount) - 1;
55     p.m_EndMask |= (1 << padCount) - 1;
56 }
57 
LoopCondition(int index,int stop,int stride)58 bool LoopCondition(int index, int stop, int stride)
59 {
60     return stride > 0 ? index >= stop : index <= stop;
61 }
62 
ExtendShape(const TensorShape & inputShape,unsigned int newNumDimensions)63 TensorShape ExtendShape(const TensorShape& inputShape,
64                         unsigned int newNumDimensions)
65 {
66     if (inputShape.GetNumDimensions() >= newNumDimensions)
67     {
68         return inputShape;
69     }
70 
71     std::vector<unsigned int> newSizes(newNumDimensions, 0);
72 
73     unsigned int diff = newNumDimensions - inputShape.GetNumDimensions();
74 
75     for (unsigned int i = 0; i < diff; i++)
76     {
77         newSizes[i] = 1;
78     }
79 
80     for (unsigned int i = diff; i < newNumDimensions; i++)
81     {
82         newSizes[i] = inputShape[i - diff];
83     }
84 
85     return TensorShape(newNumDimensions, newSizes.data());
86 }
87 
88 } // Anonymous namespace
89 
StridedSlice(const TensorInfo & inputInfo,const StridedSliceDescriptor & params,const void * inputData,void * outputData,unsigned int dataTypeSize)90 void StridedSlice(const TensorInfo& inputInfo,
91                   const StridedSliceDescriptor& params,
92                   const void* inputData,
93                   void* outputData,
94                   unsigned int dataTypeSize)
95 {
96     const unsigned char* input = reinterpret_cast<const unsigned char*>(inputData);
97     unsigned char* output = reinterpret_cast<unsigned char*>(outputData);
98 
99     const TensorShape inputShape = ExtendShape(inputInfo.GetShape(), 4);
100 
101     StridedSliceDescriptor paddedParams = params;
102 
103     // Pad parameters to 4 dimensions
104     PadParams(paddedParams, 4);
105 
106     const int start0 = paddedParams.GetStartForAxis(inputShape, 0);
107     const int stop0  = paddedParams.GetStopForAxis (inputShape, 0, start0);
108 
109     const int start1 = paddedParams.GetStartForAxis(inputShape, 1);
110     const int stop1  = paddedParams.GetStopForAxis (inputShape, 1, start1);
111 
112     const int start2 = paddedParams.GetStartForAxis(inputShape, 2);
113     const int stop2  = paddedParams.GetStopForAxis (inputShape, 2, start2);
114 
115     const int start3 = paddedParams.GetStartForAxis(inputShape, 3);
116     const int stop3  = paddedParams.GetStopForAxis (inputShape, 3, start3);
117 
118     const int step = armnn::numeric_cast<int>(dataTypeSize);
119 
120     for (int in0 = start0;
121          !LoopCondition(in0, stop0, paddedParams.m_Stride[0]);
122          in0 += paddedParams.m_Stride[0])
123     {
124         for (int in1 = start1;
125              !LoopCondition(in1, stop1, paddedParams.m_Stride[1]);
126              in1 += paddedParams.m_Stride[1])
127         {
128             for (int in2 = start2;
129                  !LoopCondition(in2, stop2, paddedParams.m_Stride[2]);
130                  in2 += paddedParams.m_Stride[2])
131             {
132                 for (int in3 = start3;
133                      !LoopCondition(in3, stop3, paddedParams.m_Stride[3]);
134                      in3 += paddedParams.m_Stride[3])
135                 {
136                     int dim1 = armnn::numeric_cast<int>(inputShape[1]);
137                     int dim2 = armnn::numeric_cast<int>(inputShape[2]);
138                     int dim3 = armnn::numeric_cast<int>(inputShape[3]);
139 
140                     int inputOffset = (((in0 * dim1 + in1) * dim2 + in2) * dim3 + in3) * step;
141                     ::memcpy(output, input + inputOffset, dataTypeSize);
142                     output += step;
143                 }
144             }
145         }
146     }
147 }
148 
149 } // namespace armnn
150