IVGCVSW-6862 Modify GATHERNd Neon workload
* Add validate for all layers for GatherNd
* Fix convert policy for Mul
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I0f2bae5107607ba3c02b5546f60dd9623cd95853
diff --git a/src/backends/neon/workloads/NeonGatherNdWorkload.cpp b/src/backends/neon/workloads/NeonGatherNdWorkload.cpp
index 00c66cf..2d56ef2 100644
--- a/src/backends/neon/workloads/NeonGatherNdWorkload.cpp
+++ b/src/backends/neon/workloads/NeonGatherNdWorkload.cpp
@@ -11,33 +11,87 @@
namespace armnn
{
-arm_compute::Status NeonGatherNdWorkloadValidate(const TensorInfo& paramInfo,
+arm_compute::Status NeonGatherNdWorkloadValidate(const TensorInfo& paramsInfo,
const TensorInfo& indicesInfo,
const TensorInfo& outputInfo)
{
// Calculate ND, K, W, C.
- std::map<std::string, unsigned int> keyIndices = CalculateGatherNdKeyIndices(paramInfo, indicesInfo);
+ std::map<std::string, unsigned int> keyIndices = CalculateGatherNdKeyIndices(paramsInfo, indicesInfo);
- /// Call Gather with adequate shapes
- // Reshape params into { K, C }
- armnn::TensorInfo params_K_C_Info = paramInfo;
+ /// Validate Mul
+ // Indices with shape { W, ND }
+ armnn::TensorInfo indices_W_ND_Info = indicesInfo;
+ indices_W_ND_Info.SetShape({ keyIndices["W"], keyIndices["ND"] });
+ const arm_compute::TensorInfo aclIndicesInfo = BuildArmComputeTensorInfo(indices_W_ND_Info);
+
+ // Flattened coefficients with shape { ND }
+ armnn::TensorInfo flattenedCoeff_Info = indicesInfo;
+ flattenedCoeff_Info.SetShape({ keyIndices["ND"] });
+ const arm_compute::TensorInfo aclFlattenedCoeffInfo = BuildArmComputeTensorInfo(flattenedCoeff_Info);
+
+ // Output of Mul with shape { W, ND }
+ const arm_compute::TensorInfo aclOutputMulInfo = BuildArmComputeTensorInfo(indices_W_ND_Info);
+
+ auto statusMul = arm_compute::NEPixelWiseMultiplication::validate(&aclIndicesInfo,
+ &aclFlattenedCoeffInfo,
+ &aclOutputMulInfo,
+ 1.0f,
+ arm_compute::ConvertPolicy::WRAP,
+ arm_compute::RoundingPolicy::TO_ZERO,
+ arm_compute::ActivationLayerInfo());
+
+ /// Validate ReduceSum
+ // Flattened indices with shape { W }
+ armnn::TensorInfo flattenedIndices_Info = indicesInfo;
+ flattenedIndices_Info.SetShape({ keyIndices["W"] });
+ const arm_compute::TensorInfo aclFlattenedIndicesInfo = BuildArmComputeTensorInfo(flattenedIndices_Info);
+
+ const std::vector<unsigned int> armnnReduceAxes(1, 1);
+ arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclOutputMulInfo.num_dimensions(),
+ indices_W_ND_Info.GetNumDimensions(),
+ armnnReduceAxes);
+
+ auto statusReduceSum = arm_compute::NEReductionOperation::validate(&aclOutputMulInfo,
+ &aclFlattenedIndicesInfo,
+ static_cast<unsigned int>(coords[0]),
+ arm_compute::ReductionOperation::SUM,
+ false);;
+
+ /// Validate Gather
+ // Params with shape { K, C }
+ armnn::TensorInfo params_K_C_Info = paramsInfo;
params_K_C_Info.SetShape({ keyIndices["K"], keyIndices["C"] });
+ const arm_compute::TensorInfo aclParamsInfo = BuildArmComputeTensorInfo(params_K_C_Info);
- // Reshape indices into { W }
- armnn::TensorInfo indices_W_Info = indicesInfo;
- indices_W_Info.SetShape({ keyIndices["W"] });
-
- // Reshape output to have the shape given by gather { W, C }
- // (the original outputInfo has the shape given by gatherNd)
+ // Output of gather with shape { W, C }
armnn::TensorInfo outputGather_Info = outputInfo;
outputGather_Info.SetShape({ keyIndices["W"], keyIndices["C"] });
-
- const arm_compute::TensorInfo aclParamsInfo = BuildArmComputeTensorInfo(params_K_C_Info);
- const arm_compute::TensorInfo aclIndicesInfo = BuildArmComputeTensorInfo(indices_W_Info);
- const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(outputGather_Info);
+ const arm_compute::TensorInfo aclOutputGatherInfo = BuildArmComputeTensorInfo(outputGather_Info);
auto aclAxis = ComputeAclAxis(0, params_K_C_Info);
- return arm_compute::NEGather::validate(&aclParamsInfo, &aclIndicesInfo, &aclOutputInfo, aclAxis);
+ auto statusGather =
+ arm_compute::NEGather::validate(&aclParamsInfo, &aclFlattenedIndicesInfo, &aclOutputGatherInfo, aclAxis);
+
+ /// Validate Reshape
+ const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(outputInfo);
+
+ auto statusReshape = arm_compute::NEReshapeLayer::validate(&aclOutputGatherInfo, &aclOutputInfo);
+
+ /// Return OK if all the layers are valid
+ auto okCode = arm_compute::ErrorCode::OK;
+ if (statusMul.error_code() == okCode &&
+ statusReduceSum.error_code() == okCode &&
+ statusGather.error_code() == okCode &&
+ statusReshape.error_code() == okCode)
+ {
+ return arm_compute::Status(arm_compute::ErrorCode::OK,
+ "All GatherND layers validate status OK.");
+ }
+ else
+ {
+ return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR,
+ "GatherND layer validate status failed.");
+ }
}
NeonGatherNdWorkload::NeonGatherNdWorkload(const GatherNdQueueDescriptor& descriptor,
@@ -94,16 +148,11 @@
armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_outputMul);
// Multiply
- auto convertPolicy = (IsQuantizedType(info.m_InputTensorInfos[0].GetDataType()) ||
- IsQuantizedType(info.m_InputTensorInfos[1].GetDataType())) ?
- arm_compute::ConvertPolicy::SATURATE :
- arm_compute::ConvertPolicy::WRAP;
-
m_MulLayer.configure(&indices,
&m_FlattenedCoeff,
&m_outputMul,
1.0f,
- convertPolicy,
+ arm_compute::ConvertPolicy::WRAP,
arm_compute::RoundingPolicy::TO_ZERO,
arm_compute::ActivationLayerInfo());