1 //
2 // Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #include "Reduce.hpp"
7
8 #include <armnn/utility/NumericCast.hpp>
9
10 #include <armnn/backends/WorkloadData.hpp>
11
12 #include <cstddef>
13 #include <functional>
14 #include <limits>
15
16 namespace armnn
17 {
18
NextIndex(const unsigned int numDims,const armnn::TensorShape & dims,std::vector<unsigned int> & current)19 bool NextIndex(const unsigned int numDims, const armnn::TensorShape& dims, std::vector<unsigned int>& current)
20 {
21 unsigned int carry = 1;
22
23 for (unsigned int idx = numDims; idx-- > 0; )
24 {
25 unsigned int current_val = current[idx] + carry;
26 if (dims[idx] == current_val)
27 {
28 current[idx] = 0;
29 }
30 else
31 {
32 current[idx] = current_val;
33 carry = 0;
34 break;
35 }
36 }
37 return (carry == 0);
38 }
39
ReducedOutputOffset(const unsigned int numDims,const armnn::TensorShape & dims,std::vector<unsigned int> & index,const unsigned int numAxis,const std::vector<unsigned int> & axis)40 unsigned int ReducedOutputOffset(const unsigned int numDims,
41 const armnn::TensorShape& dims,
42 std::vector<unsigned int>& index,
43 const unsigned int numAxis,
44 const std::vector<unsigned int>& axis)
45 {
46 unsigned int offset = 0;
47 for (unsigned int idx = 0; idx < numDims; ++idx)
48 {
49 bool isAxis = false;
50 if (!axis.empty())
51 {
52 for (unsigned int axisIdx = 0; axisIdx < numAxis; ++axisIdx)
53 {
54 if (idx == axis[axisIdx])
55 {
56 isAxis = true;
57 break;
58 }
59 }
60 }
61 if (!isAxis)
62 {
63 offset = offset * dims[idx] + index[idx];
64 }
65 }
66 return offset;
67 }
68
69
Reduce(const TensorInfo & inputInfo,const TensorInfo & outputInfo,Decoder<float> & input,Encoder<float> & output,const std::vector<uint32_t> axis,const ReduceOperation reduceOperation)70 void Reduce(const TensorInfo& inputInfo,
71 const TensorInfo& outputInfo,
72 Decoder<float>& input,
73 Encoder<float>& output,
74 const std::vector<uint32_t> axis,
75 const ReduceOperation reduceOperation)
76 {
77 armnn::TensorShape inputDims = inputInfo.GetShape();
78 unsigned int inputNumDims = inputInfo.GetNumDimensions();
79 unsigned int numOutputs = outputInfo.GetNumElements();
80
81 // Initialise temp output
82 std::vector<float> tempOut(numOutputs);
83 switch(reduceOperation)
84 {
85 case ReduceOperation::Mean:
86 case ReduceOperation::Sum:
87 std::fill(tempOut.begin(), tempOut.end(), 0.0f);
88 break;
89 case ReduceOperation::Prod:
90 std::fill(tempOut.begin(), tempOut.end(), 1.0f);
91 break;
92 case ReduceOperation::Max:
93 std::fill(tempOut.begin(), tempOut.end(), -1 * std::numeric_limits<float>::max());
94 break;
95 case ReduceOperation::Min:
96 std::fill(tempOut.begin(), tempOut.end(), std::numeric_limits<float>::max());
97 break;
98 default:
99 throw armnn::InvalidArgumentException("Unknown reduce method: " +
100 std::to_string(static_cast<int>(reduceOperation)));
101 }
102
103 // Initialise temp index
104 std::vector<unsigned int> tempIndex(inputNumDims, 0);
105
106 std::vector<unsigned int> resolvedAxis = axis;
107 if (resolvedAxis.empty())
108 {
109 for (unsigned int idx = 0; idx < inputNumDims; ++idx)
110 {
111 resolvedAxis.push_back(idx);
112 }
113 }
114 auto numResolvedAxis = armnn::numeric_cast<unsigned int>(resolvedAxis.size());
115
116 // Iterates through input_data and operates over the reduced axis
117 for (bool hasNext = true; hasNext; hasNext = NextIndex(inputNumDims, inputDims, tempIndex))
118 {
119 unsigned int inputOffset = ReducedOutputOffset(inputNumDims, inputDims, tempIndex, 0, {});
120 unsigned int outputOffset = ReducedOutputOffset(inputNumDims, inputDims, tempIndex,
121 numResolvedAxis, resolvedAxis);
122 input[inputOffset];
123 auto inputValue = input.Get();
124 switch(reduceOperation)
125 {
126 case ReduceOperation::Mean:
127 case ReduceOperation::Sum:
128 tempOut[outputOffset] += inputValue;
129 break;
130 case ReduceOperation::Prod:
131 tempOut[outputOffset] *= inputValue;
132 break;
133 case ReduceOperation::Max:
134 if (inputValue > tempOut[outputOffset])
135 {
136 tempOut[outputOffset] = inputValue;
137 }
138 break;
139 case ReduceOperation::Min:
140 if (inputValue < tempOut[outputOffset])
141 {
142 tempOut[outputOffset] = inputValue;
143 }
144 break;
145 default:
146 throw armnn::InvalidArgumentException("Unknown reduce method: " +
147 std::to_string(static_cast<int>(reduceOperation)));
148 }
149 }
150
151 // Takes average by num of elements added to get MEAN
152 size_t numElementsInAxis = 1;
153 for (unsigned int idx = 0; idx < numResolvedAxis; ++idx)
154 {
155 unsigned int current = inputDims[resolvedAxis[idx]];
156 ARMNN_ASSERT(armnn::numeric_cast<float>(current) <
157 (std::numeric_limits<float>::max() / armnn::numeric_cast<float>(numElementsInAxis)));
158 numElementsInAxis *= current;
159 }
160
161 for (unsigned int idx = 0; idx < numOutputs; ++idx)
162 {
163 output[idx];
164 if (reduceOperation == ReduceOperation::Mean)
165 {
166 if (numElementsInAxis > 0)
167 {
168 output.Set(tempOut[idx] / armnn::numeric_cast<float>(numElementsInAxis));
169 }
170 }
171 else
172 {
173 output.Set(tempOut[idx]);
174 }
175 }
176 }
177
178 } //namespace armnn