1 files changed, 72 insertions, 0 deletions
diff --git a/src/backends/tosaCommon/operatorMappings/ElementwiseUnaryOperator.cpp b/src/backends/tosaCommon/operatorMappings/ElementwiseUnaryOperator.cpp
new file mode 100644
index 0000000000..15fb9d746b
--- /dev/null
+++ b/src/backends/tosaCommon/operatorMappings/ElementwiseUnaryOperator.cpp
@@ -0,0 +1,72 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ElementwiseUnaryOperator.hpp"
+
+TosaSerializationBasicBlock* ConvertElementwiseUnaryOperator(const Layer* layer,
+                                                             const std::vector<const TensorInfo*>& inputs,
+                                                             const std::vector<const TensorInfo*>& outputs,
+                                                             const ElementwiseUnaryDescriptor* unaryDescriptor)
+{
+    std::string input0Name = std::string("input0_");
+    std::string outputName = std::string("output0_");
+    std::string blockName  = std::string("Op_ELEMENTWISEUNARY_block_") + GetUniqueTosaMappingID();
+
+
+    // If a layer is present then the block will be used for execution, so input and output names need to be determined
+    // using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
+    if(layer != nullptr)
+    {
+        // Get the layer connected to the input slot and determine unique the tensor name.
+        Layer& connectedLayer0 = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
+        input0Name = GenerateUniqueName(connectedLayer0, 0);
+
+        // Determine unique output tensor name.
+        outputName = GenerateUniqueOutputName(*layer, 0);
+    }
+
+    TosaSerializationOperator* op = nullptr;
+    switch(unaryDescriptor->m_Operation)
+    {
+        case UnaryOperation::Rsqrt:
+        {
+            op = new TosaSerializationOperator(tosa::Op_RSQRT,
+                                               Attribute_NONE,
+                                               nullptr,
+                                               {input0Name},
+                                               {outputName});
+            blockName = std::string("Op_RSQRT_block_") + GetUniqueTosaMappingID();
+            break;
+        }
+        default:
+            throw armnn::Exception("ConvertElementwiseUnaryToTosaOperator: Unsupported layer type.");
+    }
+
+    ARMNN_ASSERT(op != nullptr);
+
+    std::vector<TosaSerializationTensor*> tensors;
+    // Only add input tensor if connected layer is an input layer.
+    // As intermediate or constant tensors will be created separately.
+    // There also can't be duplicate tensor.
+    if(input0Name.find("input0_") != std::string::npos)
+    {
+        std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape());
+        DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType());
+        tensors.push_back(new TosaSerializationTensor(input0Name, inputShape0, inputDType0, {}));
+    }
+
+    std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape());
+    DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType());
+
+    tensors.push_back(new TosaSerializationTensor(outputName, outputShape0, outputDType0, {}));
+
+    // operatorInputNames/operatorOutputNames ends up being the same as
+    // blockInputNames/blockOutputNames for one-to-one ArmNN to Tosa mappings
+    return new TosaSerializationBasicBlock(blockName, // name
+                                           {op}, // operators
+                                           tensors, // tensors
+                                           {input0Name}, // inputs
+                                           {outputName}); // outputs
+}
+\ No newline at end of file