1 //
2 // Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #include "RefGatherNdWorkload.hpp"
7
8 #include "Gather.hpp"
9 #include "Profiling.hpp"
10 #include "RefWorkloadUtils.hpp"
11 #include "backendsCommon/WorkloadUtils.hpp"
12
13 namespace armnn
14 {
15
Execute() const16 void RefGatherNdWorkload::Execute() const
17 {
18 Execute(m_Data.m_Inputs, m_Data.m_Outputs);
19 }
20
ExecuteAsync(ExecutionData & executionData)21 void RefGatherNdWorkload::ExecuteAsync(ExecutionData& executionData)
22 {
23 WorkingMemDescriptor* workingMemDescriptor = static_cast<WorkingMemDescriptor*>(executionData.m_Data);
24 Execute(workingMemDescriptor->m_Inputs, workingMemDescriptor->m_Outputs);
25 }
26
Execute(std::vector<ITensorHandle * > inputs,std::vector<ITensorHandle * > outputs) const27 void RefGatherNdWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const
28 {
29 ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefGatherNdWorkload_Execute");
30
31 const TensorInfo& inputInfo0 = GetTensorInfo(inputs[0]);
32 const TensorInfo& inputInfo1 = GetTensorInfo(inputs[1]);
33 const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
34
35 std::unique_ptr<Decoder<float>> params_decoderPtr = MakeDecoder<float>(inputInfo0, inputs[0]->Map());
36
37 const int32_t* indicesDataPtr = reinterpret_cast<int32_t*>(inputs[1]->Map());
38 std::vector<int32_t> indices(indicesDataPtr, indicesDataPtr + inputInfo1.GetNumElements());
39
40 std::unique_ptr<Encoder<float>> output_encoderPtr = MakeEncoder<float>(outputInfo, outputs[0]->Map());
41
42 std::map<std::string, unsigned int> keyIndices = CalculateGatherNdKeyIndices(inputInfo0, inputInfo1);
43
44 /// Calculate flattened indices: flattenedIndices = indices * flattenedCoefficients
45 // Calculate the flattened coefficients to use in the multiplication
46 // to calculate the flattened indices needed by gather
47 TensorShape paramsShape = inputInfo0.GetShape();
48 std::vector<unsigned int> flattenedCoeff(keyIndices["ND"], 1);
49 for (unsigned int i = 1; i < keyIndices["ND"]; ++i)
50 {
51 flattenedCoeff[i-1] = paramsShape[i];
52 }
53 for (unsigned int i = keyIndices["ND"]-1; i > 0; --i)
54 {
55 flattenedCoeff[i-1] *= flattenedCoeff[i];
56 }
57
58 // Prepare the vector to store the output of the matrix multiplication,
59 // which will represent the flattened indices needed by gather
60 armnn::TensorInfo flattenedIndices_Info = inputInfo1;
61 flattenedIndices_Info.SetShape({ keyIndices["W"] });
62 std::vector<int32_t> flattenedIndices(flattenedIndices_Info.GetNumElements(), 0);
63
64 // Multiplication to calculate the flattened indices, which are the indices needed by gather.
65 for (unsigned int i = 0; i < keyIndices["W"]; ++i)
66 {
67 for (unsigned int j = 0; j < keyIndices["ND"]; ++j)
68 {
69 flattenedIndices[i] += indices[i * keyIndices["ND"] + j] * static_cast<int32_t>(flattenedCoeff[j]);
70 }
71 }
72
73 /// Call Gather with adequate shapes
74 // Reshape params into {K, C}
75 armnn::TensorInfo params_K_C_Info = inputInfo0;
76 params_K_C_Info.SetShape({ keyIndices["K"], keyIndices["C"] });
77
78 // Reshape indices into {N, W}
79 armnn::TensorInfo indices_N_W_Info = inputInfo1;
80 indices_N_W_Info.SetShape({ keyIndices["N"], keyIndices["W"] });
81
82 // Reshape output to have the shape given by gather {N, W, C}
83 // (the original outputInfo has the shape given by gatherNd)
84 armnn::TensorInfo outputGather_Info = outputInfo;
85 outputGather_Info.SetShape({ keyIndices["N"], keyIndices["W"], keyIndices["C"] });
86
87 // output_gather = gather(params_K_C, indices_N_W)
88 Gather(params_K_C_Info, indices_N_W_Info, outputGather_Info,
89 *params_decoderPtr, flattenedIndices.data(), *output_encoderPtr, 0);
90 }
91
92 } //namespace armnn
93