1 files changed, 91 insertions, 0 deletions
diff --git a/src/backends/reference/workloads/RefGatherNdWorkload.cpp b/src/backends/reference/workloads/RefGatherNdWorkload.cpp
new file mode 100644
index 0000000000..4c6b559943
--- /dev/null
+++ b/src/backends/reference/workloads/RefGatherNdWorkload.cpp
@@ -0,0 +1,91 @@
+//
+// 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