IVGCVSW-7886 Add TILE to delegate and opaque delegate

  * Adding support for Tile in classic and opaque delegates
  * CMake files updated
  * Tests added

Signed-off-by: Tianle Cheng <tianle.cheng@arm.com>
Change-Id: I9b52cea3480eb71961cbccb1a346805f73b5661a

3 files changed, 200 insertions, 4 deletions

diff --git a/delegate/opaque/CMakeLists.txt b/delegate/opaque/CMakeLists.txt
index 787046d80c..c05bccf8c9 100644
--- a/delegate/opaque/CMakeLists.txt
+++ b/delegate/opaque/CMakeLists.txt
@@ -41,6 +41,7 @@ list(APPEND armnnOpaqueDelegateObject_sources
         src/SpaceDepth.hpp
         src/Split.hpp
         src/StridedSlice.hpp
+        src/Tile.hpp
         src/Transpose.hpp
         src/UnidirectionalSequenceLstm.hpp
         src/Unpack.hpp)
diff --git a/delegate/opaque/src/Tile.hpp b/delegate/opaque/src/Tile.hpp
new file mode 100644
index 0000000000..17cbdee7eb
--- /dev/null
+++ b/delegate/opaque/src/Tile.hpp
@@ -0,0 +1,188 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+TfLiteStatus ValidateTileOperator(DelegateData& delegateData,
+                                  TfLiteOpaqueContext *tfLiteContext,
+                                  const armnn::TensorInfo& inputInfo,
+                                  const armnn::TensorInfo& outputInfo,
+                                  const armnn::TileDescriptor& descriptor)
+{
+    bool isSupported = false;
+    FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("TILE",
+                                      tfLiteContext,
+                                      IsTileSupported,
+                                      delegateData.m_Backends,
+                                      isSupported,
+                                      armnn::BackendId(),
+                                      inputInfo,
+                                      outputInfo,
+                                      descriptor);
+    return isSupported ? kTfLiteOk : kTfLiteError;
+}
+
+TfLiteStatus VisitTileOperator(DelegateData& delegateData,
+                               TfLiteOpaqueContext* tfLiteContext,
+                               TfLiteOpaqueNode* tfLiteNode,
+                               int nodeIndex,
+                               int32_t tileOperatorCode)
+{
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    // Gather input tensors
+    auto numInputs = TfLiteOpaqueNodeNumberOfInputs(tfLiteNode);
+    const int* inputTensors;
+    if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ",
+            nodeIndex);
+        return kTfLiteError;
+    }
+
+    // Gather output tensors
+    int numOutputs = 0;
+    const int* outputTensors;
+    if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ",
+            nodeIndex);
+        return kTfLiteError;
+    }
+
+    // The input contains the data that should be tiled
+    const TfLiteOpaqueTensor* tfLiteInputTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
+    if (IsDynamicTensor(tfLiteInputTensor))
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+            tileOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    // The multiples tensor contains the number of copies for each axis
+    const TfLiteOpaqueTensor* tfLiteMultiplesTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]);;
+    if (IsDynamicTensor(tfLiteMultiplesTensor))
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+            tileOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    // The output tensor
+    const TfLiteOpaqueTensor* tfLiteOutputTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+    if (IsDynamicTensor(tfLiteOutputTensor))
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnOpaqueDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ",
+            tileOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
+    const armnn::TensorInfo& multiplesTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteMultiplesTensor);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
+
+    // Multiples length must be the same as the number of dimension in input tensor
+    if (multiplesTensorInfo.GetNumElements() != inputTensorInfo.GetNumDimensions())
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnOpaqueDelegate:",
+            "The Multiples length must be the same as the number of dimension in input tensor",
+            "Operator: #%d node #%d: ",
+            tileOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    // Get the Multiples data: In armnn, the values of the multiples input tensor is saved in the operator descriptor
+    // We have to read it from the input tensor and write it the descriptor
+    auto* multiplesTensorDataPtr = static_cast<int32_t*>(TfLiteOpaqueTensorData(tfLiteMultiplesTensor));
+    auto multiplesTensorNum = TfLiteOpaqueTensorDim(tfLiteMultiplesTensor, 0);
+    std::vector<int32_t> multiplesIntData(multiplesTensorDataPtr, multiplesTensorDataPtr + multiplesTensorNum);
+
+    // The multiples must be positive
+    for (auto multiple : multiplesIntData)
+    {
+        if (multiple < 0)
+        {
+            TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: The Multiples must be positive values",
+                "Operator: #%d node #%d: ",
+                tileOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+    }
+
+    // The original input from TFLite is int32, and we have to make it as uint32 for our descriptor
+    std::vector<uint32_t> multiplesUintData;
+    std::transform(multiplesIntData.begin(),
+                   multiplesIntData.end(),
+                   std::back_inserter(multiplesUintData),
+                   [] (const int value)
+                   {
+                       return static_cast<uint32_t>(value);
+                   });
+
+    armnn::TileDescriptor tileDescriptor;
+    tileDescriptor.m_Multiples = multiplesUintData;
+
+    // Check output dimensions
+    if (inputTensorInfo.GetNumDimensions() != outputTensorInfo.GetNumDimensions())
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: Input tensor dimension and output tensor dimension differ",
+                "Operator: #%d node #%d: ",
+                tileOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    // No network pointer indicates that only support for this operator should be checked
+    if (!delegateData.m_Network)
+    {
+        return ValidateTileOperator(delegateData,
+                                    tfLiteContext,
+                                    inputTensorInfo,
+                                    outputTensorInfo,
+                                    tileDescriptor);
+    }
+
+    std::string layerName("Tile");
+    armnn::IConnectableLayer* layer = delegateData.m_Network->AddTileLayer(tileDescriptor, layerName.c_str());
+
+    if (layer == nullptr)
+    {
+        return kTfLiteError;
+    }
+
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    if (ProcessInputs(layer, delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk)
+    {
+        return kTfLiteError;
+    }
+
+    return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnOpaqueDelegate
\ No newline at end of file
diff --git a/delegate/opaque/src/armnn_delegate.cpp b/delegate/opaque/src/armnn_delegate.cpp
index 510352eae9..49fa30d8f0 100644
--- a/delegate/opaque/src/armnn_delegate.cpp
+++ b/delegate/opaque/src/armnn_delegate.cpp
@@ -38,6 +38,7 @@
 #include "Softmax.hpp"
 #include "SpaceDepth.hpp"
 #include "Split.hpp"
+#include "Tile.hpp"
 #include "Transpose.hpp"
 #include "UnidirectionalSequenceLstm.hpp"
 #include "Unpack.hpp"
@@ -1138,12 +1139,18 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData,
                                            tfLiteNode,
                                            nodeIndex,
                                            kTfLiteBuiltinTanh);
+        case kTfLiteBuiltinTile:
+            return VisitTileOperator(delegateData,
+                                     tfLiteContext,
+                                     tfLiteNode,
+                                     nodeIndex,
+                                     kTfLiteBuiltinTile);
         case kTfLiteBuiltinTranspose:
             return VisitTransposeOperator(delegateData,
-                                            tfLiteContext,
-                                            tfLiteNode,
-                                            nodeIndex,
-                                            kTfLiteBuiltinTranspose);
+                                          tfLiteContext,
+                                          tfLiteNode,
+                                          nodeIndex,
+                                          kTfLiteBuiltinTranspose);
         case kTfLiteBuiltinTransposeConv:
             return VisitConvolutionOperator(delegateData,
                                             tfLiteContext,