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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "RefGatherNdWorkload.hpp"
#include "Gather.hpp"
#include "Profiling.hpp"
#include "RefWorkloadUtils.hpp"
#include "backendsCommon/WorkloadUtils.hpp"
namespace armnn
{
void RefGatherNdWorkload::Execute() const
{
Execute(m_Data.m_Inputs, m_Data.m_Outputs);
}
void RefGatherNdWorkload::ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor)
{
Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
}
void RefGatherNdWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const
{
ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefGatherNdWorkload_Execute");
const TensorInfo& inputInfo0 = GetTensorInfo(inputs[0]);
const TensorInfo& inputInfo1 = GetTensorInfo(inputs[1]);
const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
std::unique_ptr<Decoder<float>> params_decoderPtr = MakeDecoder<float>(inputInfo0, inputs[0]->Map());
const int32_t* indicesDataPtr = reinterpret_cast<int32_t*>(inputs[1]->Map());
std::vector<int32_t> indices(indicesDataPtr, indicesDataPtr + inputInfo1.GetNumElements());
std::unique_ptr<Encoder<float>> output_encoderPtr = MakeEncoder<float>(outputInfo, outputs[0]->Map());
std::map<std::string, unsigned int> keyIndices = CalculateGatherNdKeyIndices(inputInfo0, inputInfo1);
/// Calculate flattened indices: flattenedIndices = indices * flattenedCoefficients
// Calculate the flattened coefficients to use in the multiplication
// to calculate the flattened indices needed by gather
TensorShape paramsShape = inputInfo0.GetShape();
std::vector<unsigned int> flattenedCoeff(keyIndices["ND"], 1);
for (unsigned int i = 1; i < keyIndices["ND"]; ++i)
{
flattenedCoeff[i-1] = paramsShape[i];
}
for (unsigned int i = keyIndices["ND"]-1; i > 0; --i)
{
flattenedCoeff[i-1] *= flattenedCoeff[i];
}
// Prepare the vector to store the output of the matrix multiplication,
// which will represent the flattened indices needed by gather
armnn::TensorInfo flattenedIndices_Info = inputInfo1;
flattenedIndices_Info.SetShape({ keyIndices["W"] });
std::vector<int32_t> flattenedIndices(flattenedIndices_Info.GetNumElements(), 0);
// Multiplication to calculate the flattened indices, which are the indices needed by gather.
for (unsigned int i = 0; i < keyIndices["W"]; ++i)
{
for (unsigned int j = 0; j < keyIndices["ND"]; ++j)
{
flattenedIndices[i] += indices[i * keyIndices["ND"] + j] * static_cast<int32_t>(flattenedCoeff[j]);
}
}
/// Call Gather with adequate shapes
// Reshape params into {K, C}
armnn::TensorInfo params_K_C_Info = inputInfo0;
params_K_C_Info.SetShape({ keyIndices["K"], keyIndices["C"] });
// Reshape indices into {N, W}
armnn::TensorInfo indices_N_W_Info = inputInfo1;
indices_N_W_Info.SetShape({ keyIndices["N"], keyIndices["W"] });
// Reshape output to have the shape given by gather {N, W, C}
// (the original outputInfo has the shape given by gatherNd)
armnn::TensorInfo outputGather_Info = outputInfo;
outputGather_Info.SetShape({ keyIndices["N"], keyIndices["W"], keyIndices["C"] });
// output_gather = gather(params_K_C, indices_N_W)
Gather(params_K_C_Info, indices_N_W_Info, outputGather_Info,
*params_decoderPtr, flattenedIndices.data(), *output_encoderPtr, 0);
}
} //namespace armnn
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