Add Split support to TOSA Reference Backend

* Resolves IVGCVSW-7918

Signed-off-by: Kevin May <kevin.may@arm.com>
Change-Id: Ic2afaa55f7ee88ce4c9b8ea696eef5f28663f8c6

1 files changed, 116 insertions, 0 deletions

diff --git a/src/backends/tosaCommon/operatorMappings/SplitOperator.cpp b/src/backends/tosaCommon/operatorMappings/SplitOperator.cpp
new file mode 100644
index 0000000000..5231f96c36
--- /dev/null
+++ b/src/backends/tosaCommon/operatorMappings/SplitOperator.cpp
@@ -0,0 +1,116 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+// Copyright © 2020 The TensorFlow Authors. All Rights Reserved.
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "SplitOperator.hpp"
+
+// This function is paraphrased from:
+// tensorflow/compiler/mlir/tosa/transforms/legalize_common.cc from function convertSplitOp
+TosaSerializationBasicBlock* ConvertSplitToTosaOperator(const Layer* layer,
+                                                        const std::vector<const TensorInfo*>& inputs,
+                                                        const std::vector<const TensorInfo*>& outputs,
+                                                        const SplitterDescriptor* splitDescriptor)
+{
+    ARMNN_THROW_INVALIDARG_MSG_IF_FALSE( inputs.size() == 1,
+                                         "ConvertSplitToTosaOperator: Split must have only one input" );
+
+    ARMNN_THROW_INVALIDARG_MSG_IF_FALSE( outputs.size() < 1,
+                                         "ConvertSplitToTosaOperator: Split must have more than one output" );
+
+    if (!inputs[0]->GetShape().AreAllDimensionsSpecified())
+    {
+        throw armnn::Exception("ConvertSplitToTosaOperator: Dynamic input dimensions are unsupported.");
+    }
+
+    std::string inputName = std::string("input0_");
+    std::vector<std::string> outputNames;
+    std::string blockName  = std::string("Op_SPLIT_block_") + GetUniqueTosaMappingID();
+
+    unsigned int numSplit = splitDescriptor->GetNumViews();
+    // 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 layers connected to the input slots and determine unique tensor names.
+        Layer& connectedLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
+        inputName = GenerateUniqueName(connectedLayer, 0);
+
+        for (unsigned int i=0; i < numSplit; ++i)
+        {
+            // Determine unique output(s) tensor name.
+            std::string outputName = GenerateUniqueOutputName(*layer, i);
+            outputNames.push_back(outputName);
+        }
+    }
+    else
+    {
+        for (unsigned int i=0; i < numSplit; ++i)
+        {
+            // Determine unique output(s) tensor name.
+            std::string outputName = "output" + std::to_string(i) + "_";
+            outputNames.push_back(outputName);
+        }
+    }
+
+    // Each slice op has a different beginning point.
+    // The size is the same for each slice op.
+    std::vector<int32_t> beginVals;
+    beginVals.reserve(inputs[0]->GetNumDimensions());
+    std::vector<int32_t> sizeVals;
+    sizeVals.reserve(inputs[0]->GetNumDimensions());
+    for (unsigned int j = 0; j < inputs[0]->GetNumDimensions(); ++j)
+    {
+        beginVals.emplace_back(0);
+        uint32_t dim = inputs[0]->GetShape()[j];
+        sizeVals.emplace_back(dim);
+    }
+
+    uint32_t axis = static_cast<uint32_t>(splitDescriptor->GetAxis());
+    sizeVals[axis] = sizeVals[axis] / static_cast<int32_t>(numSplit);
+
+    std::vector<TosaSerializationOperator*> ops;
+    for (unsigned int i=0; i < numSplit; ++i)
+    {
+        beginVals[axis] = static_cast<int>(i) * sizeVals[axis];
+        TosaSliceAttribute attribute(beginVals, sizeVals);
+        auto* op = new TosaSerializationOperator(Op_SLICE,
+                                                 Attribute_SliceAttribute,
+                                                 &attribute,
+                                                 {inputName},
+                                                 {outputNames[i]});
+
+        ops.push_back(op);
+    }
+
+    std::vector<TosaSerializationTensor*> tensors;
+    // Only add input tensors if connected layer is an input layer.
+    // As intermediate or constant tensors will be created separately.
+    // There also can't be duplicate tensor.
+    if(inputName.find("input0_") != std::string::npos)
+    {
+        std::vector<int32_t> inputShape = GetTosaTensorShape(inputs[0]->GetShape());
+        DType inputDType = ArmNNToDType(inputs[0]->GetDataType());
+
+        tensors.push_back(new TosaSerializationTensor(inputName, inputShape, inputDType, {}));
+    }
+
+    std::vector<int32_t> outputShape = GetTosaTensorShape(outputs[0]->GetShape());
+    DType outputDType = ArmNNToDType(outputs[0]->GetDataType());
+
+    for (unsigned int i=0; i < numSplit; ++i)
+    {
+        tensors.push_back(new TosaSerializationTensor(outputNames[i], outputShape, outputDType, {}));
+    }
+    // operatorInputNames/operatorOutputNames ends up being the same as
+    // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings
+    return new TosaSerializationBasicBlock(blockName, // name
+                                           mainName, // region name
+                                           ops, // operators
+                                           tensors, // tensors
+                                           {inputName}, // inputs
+                                           outputNames); // outputs
+}
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