IVGCVSW-6862 Use same datatype for all containers of indices in NeonGatherNd
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I6b1c7c1c499dc93aa58fa9f58b64fb664e8bcc56
diff --git a/src/backends/neon/workloads/NeonGatherNdWorkload.cpp b/src/backends/neon/workloads/NeonGatherNdWorkload.cpp
index 2d56ef2..f83f48a 100644
--- a/src/backends/neon/workloads/NeonGatherNdWorkload.cpp
+++ b/src/backends/neon/workloads/NeonGatherNdWorkload.cpp
@@ -55,7 +55,7 @@
&aclFlattenedIndicesInfo,
static_cast<unsigned int>(coords[0]),
arm_compute::ReductionOperation::SUM,
- false);;
+ false);
/// Validate Gather
// Params with shape { K, C }
@@ -126,10 +126,10 @@
// Calculate the m_FlattenedCoeff
TensorShape paramsShape = paramsInfo.GetShape();
- std::vector<unsigned int> flattenedCoeff(keyIndices["ND"], 1);
+ std::vector<int32_t> flattenedCoeff(keyIndices["ND"], 1);
for (unsigned int i = 1; i < keyIndices["ND"]; ++i)
{
- flattenedCoeff[i - 1] = paramsShape[i];
+ flattenedCoeff[i - 1] = static_cast<int32_t>(paramsShape[i]);
}
for (unsigned int i = keyIndices["ND"] - 1; i > 0; --i)
{
@@ -139,18 +139,20 @@
flattenedCoeff_Info.SetShape({ keyIndices["ND"] });
BuildArmComputeTensor(m_FlattenedCoeff, flattenedCoeff_Info);
armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_FlattenedCoeff);
- CopyArmComputeITensorData(flattenedCoeff.data(), m_FlattenedCoeff);
+ ARMNN_ASSERT_MSG(indicesInfo.GetDataType() == DataType::Signed32,
+ "flattenedCoeff must be same data type as m_FlattenedCoeff");
+ CopyArmComputeITensorData<int32_t>(flattenedCoeff.data(), m_FlattenedCoeff);
// Prepare the tensor to store the output of the multiplication
armnn::TensorInfo outputMul_Info = indicesInfo;
outputMul_Info.SetShape({ keyIndices["W"], keyIndices["ND"] });
- BuildArmComputeTensor(m_outputMul, outputMul_Info);
- armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_outputMul);
+ BuildArmComputeTensor(m_OutputMul, outputMul_Info);
+ armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_OutputMul);
// Multiply
m_MulLayer.configure(&indices,
&m_FlattenedCoeff,
- &m_outputMul,
+ &m_OutputMul,
1.0f,
arm_compute::ConvertPolicy::WRAP,
arm_compute::RoundingPolicy::TO_ZERO,
@@ -158,10 +160,10 @@
// Reduce Sum
const std::vector<unsigned int> armnnReduceAxes(1, 1);
- arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(m_outputMul.info()->num_dimensions(),
+ arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(m_OutputMul.info()->num_dimensions(),
outputMul_Info.GetNumDimensions(),
armnnReduceAxes);
- m_ReduceSumLayer.configure(&m_outputMul,
+ m_ReduceSumLayer.configure(&m_OutputMul,
&m_FlattenedIndices,
static_cast<unsigned int>(coords[0]),
arm_compute::ReductionOperation::SUM,
@@ -176,13 +178,13 @@
// (the original outputInfo has the shape given by gatherNd)
armnn::TensorInfo outputGather_Info = outputInfo;
outputGather_Info.SetShape({ keyIndices["W"], keyIndices["C"] });
- BuildArmComputeTensor(m_outputGather, outputGather_Info);
- armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_outputGather);
+ BuildArmComputeTensor(m_OutputGather, outputGather_Info);
+ armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_OutputGather);
- m_GatherLayer.configure(&input, &m_FlattenedIndices, &m_outputGather, ComputeAclAxis(0, paramsInfo));
+ m_GatherLayer.configure(&input, &m_FlattenedIndices, &m_OutputGather, ComputeAclAxis(0, paramsInfo));
// Reshape output to the original output shape
- m_ReshapeLayer.configure(&m_outputGather, &output);
+ m_ReshapeLayer.configure(&m_OutputGather, &output);
}
void NeonGatherNdWorkload::Execute() const
diff --git a/src/backends/neon/workloads/NeonGatherNdWorkload.hpp b/src/backends/neon/workloads/NeonGatherNdWorkload.hpp
index 848aac6..e9588f4 100644
--- a/src/backends/neon/workloads/NeonGatherNdWorkload.hpp
+++ b/src/backends/neon/workloads/NeonGatherNdWorkload.hpp
@@ -27,9 +27,9 @@
private:
arm_compute::Tensor m_FlattenedCoeff;
- arm_compute::Tensor m_outputMul;
+ arm_compute::Tensor m_OutputMul;
arm_compute::Tensor m_FlattenedIndices;
- arm_compute::Tensor m_outputGather;
+ arm_compute::Tensor m_OutputGather;
mutable arm_compute::NEPixelWiseMultiplication m_MulLayer;
mutable arm_compute::NEReductionOperation m_ReduceSumLayer;