ArmNN
 24.02
ClGatherNdWorkload.cpp
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1 //
2 // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "ClGatherNdWorkload.hpp"
7 #include "ClWorkloadUtils.hpp"
10 #include <cl/ClTensorHandle.hpp>
11 
12 using namespace armnn::armcomputetensorutils;
13 
14 namespace armnn
15 {
17  const TensorInfo& indicesInfo,
18  const TensorInfo& outputInfo)
19 {
20  // Calculate ND, K, W, C.
21  std::map<std::string, unsigned int> keyIndices = CalculateGatherNdKeyIndices(paramsInfo, indicesInfo);
22 
23  /// Validate Mul
24  // Indices with shape { W, ND }
25  armnn::TensorInfo indices_W_ND_Info = indicesInfo;
26  indices_W_ND_Info.SetShape({ keyIndices["W"], keyIndices["ND"] });
27  const arm_compute::TensorInfo aclIndicesInfo = BuildArmComputeTensorInfo(indices_W_ND_Info);
28 
29  // Flattened coefficients with shape { ND }
30  armnn::TensorInfo flattenedCoeff_Info = indicesInfo;
31  flattenedCoeff_Info.SetShape({ keyIndices["ND"] });
32  const arm_compute::TensorInfo aclFlattenedCoeffInfo = BuildArmComputeTensorInfo(flattenedCoeff_Info);
33 
34  // Output of Mul with shape { W, ND }
35  const arm_compute::TensorInfo aclOutputMulInfo = BuildArmComputeTensorInfo(indices_W_ND_Info);
36 
37  auto statusMul = arm_compute::CLPixelWiseMultiplication::validate(&aclIndicesInfo,
38  &aclFlattenedCoeffInfo,
39  &aclOutputMulInfo,
40  1.0f,
41  arm_compute::ConvertPolicy::WRAP,
42  arm_compute::RoundingPolicy::TO_ZERO,
43  arm_compute::ActivationLayerInfo());
44 
45  /// Validate ReduceSum
46  // Flattened indices with shape { W }
47  armnn::TensorInfo flattenedIndices_Info = indicesInfo;
48  flattenedIndices_Info.SetShape({ keyIndices["W"] });
49  const arm_compute::TensorInfo aclFlattenedIndicesInfo = BuildArmComputeTensorInfo(flattenedIndices_Info);
50 
51  const std::vector<unsigned int> armnnReduceAxes(1, 1);
52  arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclOutputMulInfo.num_dimensions(),
53  indices_W_ND_Info.GetNumDimensions(),
54  armnnReduceAxes);
55 
56  auto statusReduceSum = arm_compute::CLReductionOperation::validate(&aclOutputMulInfo,
57  &aclFlattenedIndicesInfo,
58  static_cast<unsigned int>(coords[0]),
59  arm_compute::ReductionOperation::SUM,
60  false);
61 
62  /// Validate Gather
63  // Params with shape { K, C }
64  armnn::TensorInfo params_K_C_Info = paramsInfo;
65  params_K_C_Info.SetShape({ keyIndices["K"], keyIndices["C"] });
66  const arm_compute::TensorInfo aclParamsInfo = BuildArmComputeTensorInfo(params_K_C_Info);
67 
68  // Output of gather with shape { W, C }
69  armnn::TensorInfo outputGather_Info = outputInfo;
70  outputGather_Info.SetShape({ keyIndices["W"], keyIndices["C"] });
71  const arm_compute::TensorInfo aclOutputGatherInfo = BuildArmComputeTensorInfo(outputGather_Info);
72 
73  auto aclAxis = ComputeAclAxis(0, params_K_C_Info);
74  auto statusGather =
75  arm_compute::CLGather::validate(&aclParamsInfo, &aclFlattenedIndicesInfo, &aclOutputGatherInfo, aclAxis);
76 
77  /// Validate Reshape
78  const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(outputInfo);
79 
80  auto statusReshape = arm_compute::CLReshapeLayer::validate(&aclOutputGatherInfo, &aclOutputInfo);
81 
82  /// Return OK if all the layers are valid
83  auto okCode = arm_compute::ErrorCode::OK;
84  if (statusMul.error_code() == okCode &&
85  statusReduceSum.error_code() == okCode &&
86  statusGather.error_code() == okCode &&
87  statusReshape.error_code() == okCode)
88  {
89  return arm_compute::Status(arm_compute::ErrorCode::OK,
90  "All GatherND layers validate status OK.");
91  }
92  else
93  {
94  return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR,
95  "GatherND layer validate status failed.");
96  }
97 }
98 
100  const WorkloadInfo& info,
101  const arm_compute::CLCompileContext& clCompileContext)
103 {
104  m_Data.ValidateInputsOutputs("ClGatherNdWorkload", 2, 1);
105 
106  TensorInfo paramsInfo = info.m_InputTensorInfos[0];
107  TensorInfo indicesInfo = info.m_InputTensorInfos[1];
108  TensorInfo outputInfo = info.m_OutputTensorInfos[0];
109 
110  arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
111  arm_compute::ICLTensor& indices = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
112  arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
113 
114  // Calculate ND, K, W, C.
115  std::map<std::string, unsigned int> keyIndices = CalculateGatherNdKeyIndices(paramsInfo, indicesInfo);
116 
117  /// Calculate flattened indices: m_FlattenedIndices = indices * m_FlattenedCoeff.
118  /// This could be done using MatMul instead of multiplication followed by reduce sum operation,
119  /// but GeMM does not support s32 at the moment.
120 
121  // Prepare the tensor to store the output of the reduce_sum operation
122  armnn::TensorInfo flattenedIndices_Info = indicesInfo;
123  flattenedIndices_Info.SetShape({ keyIndices["W"] });
124  BuildArmComputeTensor(m_FlattenedIndices, flattenedIndices_Info);
125  armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_FlattenedIndices);
126 
127  // Reshape indices into { W, ND }
128  indices.info()->set_tensor_shape(BuildArmComputeTensorShape({ keyIndices["W"], keyIndices["ND"] }));
129 
130  // Calculate the m_FlattenedCoeff
131  TensorShape paramsShape = paramsInfo.GetShape();
132  std::vector<int32_t> flattenedCoeff(keyIndices["ND"], 1);
133  for (unsigned int i = 1; i < keyIndices["ND"]; ++i)
134  {
135  flattenedCoeff[i - 1] = static_cast<int32_t>(paramsShape[i]);
136  }
137  for (unsigned int i = keyIndices["ND"] - 1; i > 0; --i)
138  {
139  flattenedCoeff[i - 1] *= flattenedCoeff[i];
140  }
141  armnn::TensorInfo flattenedCoeff_Info = indicesInfo;
142  flattenedCoeff_Info.SetShape({ keyIndices["ND"] });
143  BuildArmComputeTensor(m_FlattenedCoeff, flattenedCoeff_Info);
144  armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_FlattenedCoeff);
146  "flattenedCoeff must be same data type as m_FlattenedCoeff");
147  CopyArmComputeClTensorData<int32_t>(m_FlattenedCoeff, flattenedCoeff.data());
148 
149  // Prepare the tensor to store the output of the multiplication
150  armnn::TensorInfo outputMul_Info = indicesInfo;
151  outputMul_Info.SetShape({ keyIndices["W"], keyIndices["ND"] });
152  BuildArmComputeTensor(m_OutputMul, outputMul_Info);
153  armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_OutputMul);
154 
155  // Multiply
156  m_MulLayer.configure(clCompileContext,
157  &indices,
158  &m_FlattenedCoeff,
159  &m_OutputMul,
160  1.0f,
161  arm_compute::ConvertPolicy::WRAP,
162  arm_compute::RoundingPolicy::TO_ZERO,
163  arm_compute::ActivationLayerInfo());
164 
165  // Reduce Sum
166  const std::vector<unsigned int> armnnReduceAxes(1, 1);
167  arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(m_OutputMul.info()->num_dimensions(),
168  outputMul_Info.GetNumDimensions(),
169  armnnReduceAxes);
170  m_ReduceSumLayer.configure(clCompileContext,
171  &m_OutputMul,
172  &m_FlattenedIndices,
173  static_cast<unsigned int>(coords[0]),
174  arm_compute::ReductionOperation::SUM,
175  false);
176 
177  /// Call Gather with adequate shapes
178  // Reshape params into { K, C }
179  paramsInfo.SetShape({ keyIndices["K"], keyIndices["C"] });
180  input.info()->set_tensor_shape(BuildArmComputeTensorShape(paramsInfo.GetShape()));
181 
182  // Reshape output to have the shape given by gather { W, C }
183  // (the original outputInfo has the shape given by gatherNd)
184  armnn::TensorInfo outputGather_Info = outputInfo;
185  outputGather_Info.SetShape({ keyIndices["W"], keyIndices["C"] });
186  BuildArmComputeTensor(m_OutputGather, outputGather_Info);
187  armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_OutputGather);
188  {
189  ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClGatherNdWorkload_configure");
190  auto aclAxis = ComputeAclAxis(0, paramsInfo);
191  m_GatherLayer.configure(clCompileContext, &input, &m_FlattenedIndices, &m_OutputGather, aclAxis);
192  }
193 
194  // Reshape output to the original output shape
195  m_ReshapeLayer.configure(clCompileContext, &m_OutputGather, &output);
196 };
197 
199 {
200  ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClGatherNdWorkload_Execute");
201  RunClFunction(m_MulLayer, CHECK_LOCATION());
202  RunClFunction(m_ReduceSumLayer, CHECK_LOCATION());
203  RunClFunction(m_GatherLayer, CHECK_LOCATION());
204  RunClFunction(m_ReshapeLayer, CHECK_LOCATION());
205 }
206 } // namespace armnn
armnn::GatherNdQueueDescriptor
Definition: WorkloadData.hpp:502
WorkloadUtils.hpp
armnn::QueueDescriptor::ValidateInputsOutputs
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Definition: WorkloadData.cpp:446
armnn::ClGatherNdWorkloadValidate
arm_compute::Status ClGatherNdWorkloadValidate(const TensorInfo &paramsInfo, const TensorInfo &indicesInfo, const TensorInfo &outputInfo)
Definition: ClGatherNdWorkload.cpp:16
armnn::TensorInfo
Definition: Tensor.hpp:152
armnn::TensorInfo::GetNumDimensions
unsigned int GetNumDimensions() const
Definition: Tensor.hpp:197
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::ClBaseWorkload
Definition: ClBaseWorkload.hpp:13
ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
armnn::Coordinates
std::array< unsigned int, MaxNumOfTensorDimensions > Coordinates
Definition: InternalTypes.hpp:15
ClGatherNdWorkload.hpp
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::ClGatherNdWorkload::Execute
virtual void Execute() const override
Definition: ClGatherNdWorkload.cpp:198
ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID
#define ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID(label)
Creates a profiling event that uses GetGuid() and GetName() from the calling class.
Definition: ClWorkloadUtils.hpp:36
armnn::WorkloadInfo
Contains information about TensorInfos of a layer.
Definition: WorkloadInfo.hpp:16
armnn::CalculateGatherNdKeyIndices
std::map< std::string, unsigned int > CalculateGatherNdKeyIndices(TensorInfo inputInfo0, TensorInfo inputInfo1)
Calculates the key index values needed for GatherNd: N, ND, K, W, C (N is always 1)
Definition: WorkloadUtils.cpp:312
ClWorkloadUtils.hpp
ArmComputeUtils.hpp
armnn::BoostLogSeverityMapping::info
@ info
armnn::TensorInfo::GetDataType
DataType GetDataType() const
Definition: Tensor.hpp:200
armnn::QueueDescriptor::m_Outputs
std::vector< ITensorHandle * > m_Outputs
Definition: WorkloadData.hpp:27
armnn::DataType::Signed32
@ Signed32
armnn::IClTensorHandle
Definition: IClTensorHandle.hpp:13
armnn::Status
Status
Definition: Types.hpp:42
ClTensorHandle.hpp
armnn::BaseWorkload< GatherNdQueueDescriptor >::m_Data
GatherNdQueueDescriptor m_Data
Definition: Workload.hpp:89
armnn::RunClFunction
void RunClFunction(arm_compute::IFunction &function, const CheckLocation &location)
Definition: ClWorkloadUtils.hpp:168
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::TensorInfo::SetShape
void SetShape(const TensorShape &newShape)
Definition: Tensor.hpp:195
armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6
armnn::ComputeAclAxis
int ComputeAclAxis(const int &armnnAxis, const armnn::TensorInfo &tensor)
Function to convert ArmNN axis (left to right) to ACL axis (right to left) ranging from [-rank,...
Definition: ArmComputeUtils.hpp:273
armnn::QueueDescriptor::m_Inputs
std::vector< ITensorHandle * > m_Inputs
Definition: WorkloadData.hpp:26
armnn::ClGatherNdWorkload::ClGatherNdWorkload
ClGatherNdWorkload(const GatherNdQueueDescriptor &descriptor, const WorkloadInfo &info, const arm_compute::CLCompileContext &clCompileContext)
Definition: ClGatherNdWorkload.cpp:99