IVGCVSW-7606 IVGCVSW-7607 Add Resize and Reduce to Opaque Delegate

* Added 2 opaque delegate operators and associated test cases
* Removed IsDynamicTensor check from BatchMatMul as covered by IsValid.

Signed-off-by: John Mcloughlin <john.mcloughlin@arm.com>
Change-Id: If7c58cb23ae5c5b8a9451dddfd7b6dfcbf248d4c

6 files changed, 423 insertions, 9 deletions

diff --git a/delegate/CMakeLists.txt b/delegate/CMakeLists.txt
index acd1255b0f..4f190c0601 100644
--- a/delegate/CMakeLists.txt
+++ b/delegate/CMakeLists.txt
@@ -302,6 +302,10 @@ if(BUILD_UNIT_TESTS)
              test/Pooling3dTestHelper.hpp
              test/PreluTest.cpp
              test/PreluTestHelper.hpp
+             test/ReduceTest.cpp
+             test/ReduceTestHelper.hpp
+             test/ResizeTest.cpp
+             test/ResizeTestHelper.hpp
              test/RoundTest.cpp
              test/RoundTestHelper.hpp
              test/QuantizationTest.cpp
diff --git a/delegate/opaque/CMakeLists.txt b/delegate/opaque/CMakeLists.txt
index ac205ee959..897263d63e 100644
--- a/delegate/opaque/CMakeLists.txt
+++ b/delegate/opaque/CMakeLists.txt
@@ -28,6 +28,8 @@ list(APPEND armnnOpaqueDelegateObject_sources
         src/Pack.hpp
         src/Prelu.hpp
         src/Redefine.hpp
+        src/Reduce.hpp
+        src/Resize.hpp
         src/Round.hpp
         src/Shape.hpp
         src/SharedFunctions.cpp
diff --git a/delegate/opaque/src/BatchMatMul.hpp b/delegate/opaque/src/BatchMatMul.hpp
index 5da6e5ac6a..5261fbd6c4 100644
--- a/delegate/opaque/src/BatchMatMul.hpp
+++ b/delegate/opaque/src/BatchMatMul.hpp
@@ -44,15 +44,6 @@ TfLiteStatus VisitBatchMatMulOperator(DelegateData& delegateData,
         return kTfLiteError;
     }
 
-    if (IsDynamicTensor(kTfLiteLHSInputTensor) || IsDynamicTensor(kTfLiteRHSInputTensor))
-    {
-        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
-                tfLiteContext,
-                "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
-                operatorCode, nodeIndex);
-        return kTfLiteError;
-    }
-
     // Gather output indices and use to get output tensors.
     int numOutputs = 0;
     const int* outputTensors;
diff --git a/delegate/opaque/src/Reduce.hpp b/delegate/opaque/src/Reduce.hpp
index e16969768e..afea7aafb0 100644
--- a/delegate/opaque/src/Reduce.hpp
+++ b/delegate/opaque/src/Reduce.hpp
@@ -2,3 +2,166 @@
 // Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+
+TfLiteStatus VisitReduceOperator(DelegateData& delegateData,
+                                 TfLiteOpaqueContext* tfLiteContext,
+                                 TfLiteOpaqueNode* tfLiteNode,
+                                 int nodeIndex,
+                                 int32_t reduceOperatorCode)
+{
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    // Gather input indices and use to get input tensor.
+    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;
+    }
+
+    const TfLiteOpaqueTensor* tfLiteInputTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
+    if (!IsValid(tfLiteContext, tfLiteInputTensor, reduceOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const TfLiteOpaqueTensor* tfLiteAxisTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]);
+    if (!IsValid(tfLiteContext, tfLiteAxisTensor, reduceOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    // Gather output indices and use to get 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;
+    }
+
+    const TfLiteOpaqueTensor* tfLiteOutputTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+    if (!IsValid(tfLiteContext, tfLiteOutputTensor, reduceOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo  = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
+
+    // Get const axis value from model and set it to descriptor.
+    const armnn::TensorInfo& axisTensorInfo =   GetTensorInfoForTfLiteOpaqueTensor(tfLiteAxisTensor);
+    auto* axisTensorData = static_cast<int*>(TfLiteOpaqueTensorData(tfLiteAxisTensor));
+
+    std::vector<int32_t> axis;
+    // Add axis data to vector to be converter to unsigned int and assigned to descriptor axis.
+    if (axisTensorData != nullptr)
+    {
+        for (unsigned int i = 0; i < axisTensorInfo.GetNumElements(); ++i)
+        {
+            axis.emplace_back(axisTensorData[i]);
+        }
+    }
+    else
+    {
+        for (unsigned int i = 0; i < inputTensorInfo.GetNumDimensions(); ++i)
+        {
+            axis.push_back(i);
+        }
+    }
+
+    // Convert the axis to unsigned int and remove duplicates.
+    unsigned int rank = inputTensorInfo.GetNumDimensions();
+    std::set<unsigned int> uniqueAxis;
+    std::transform(axis.begin(),
+                   axis.end(),
+                   std::inserter(uniqueAxis, uniqueAxis.begin()),
+                   [rank](int i)->unsigned int{ return (i + rank) % rank; });
+
+    armnn::ReduceDescriptor desc;
+    desc.m_vAxis.assign(uniqueAxis.begin(), uniqueAxis.end());
+
+    auto* reducerParameters = reinterpret_cast<TfLiteReducerParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+    desc.m_KeepDims = reducerParameters->keep_dims;
+    if (reduceOperatorCode == kTfLiteBuiltinReduceMax)
+    {
+        desc.m_ReduceOperation = armnn::ReduceOperation::Max;
+    }
+    else if (reduceOperatorCode == kTfLiteBuiltinReduceMin)
+    {
+        desc.m_ReduceOperation = armnn::ReduceOperation::Min;
+    }
+    else if (reduceOperatorCode == kTfLiteBuiltinSum)
+    {
+        desc.m_ReduceOperation = armnn::ReduceOperation::Sum;
+    }
+    else if (reduceOperatorCode == kTfLiteBuiltinReduceProd)
+    {
+        desc.m_ReduceOperation = armnn::ReduceOperation::Prod;
+    }
+    else
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: Unsupported Reduction Operator #%d node #%d: ",
+                reduceOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    bool isSupported = false;
+    armnn::BackendId setBackend;
+    auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("REDUCE",
+                                           tfLiteContext,
+                                           IsReduceSupported,
+                                           delegateData.m_Backends,
+                                           isSupported,
+                                           setBackend,
+                                           inputTensorInfo,
+                                           outInfo,
+                                           desc);
+    };
+
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    // Add an Reduce layer
+    armnn::IConnectableLayer* layer = delegateData.m_Network->AddReduceLayer(desc);
+    layer->SetBackendId(setBackend);
+    ARMNN_ASSERT(layer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    // try to connect the Constant Inputs if there are any
+    if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+    {
+        return kTfLiteError;
+    }
+
+    // Connect
+    return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnOpaqueDelegate
diff --git a/delegate/opaque/src/Resize.hpp b/delegate/opaque/src/Resize.hpp
index e16969768e..509ae62524 100644
--- a/delegate/opaque/src/Resize.hpp
+++ b/delegate/opaque/src/Resize.hpp
@@ -2,3 +2,221 @@
 // Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+
+TfLiteStatus ValidateResizeOperator(DelegateData& delegateData,
+                                    TfLiteOpaqueContext* tfLiteContext,
+                                    const armnn::TensorInfo& inputInfo,
+                                    const armnn::TensorInfo& outputInfo,
+                                    const armnn::ResizeDescriptor& descriptor)
+{
+    bool isSupported = false;
+    FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("RESIZE",
+                                       tfLiteContext,
+                                       IsResizeSupported,
+                                       delegateData.m_Backends,
+                                       isSupported,
+                                       armnn::BackendId(),
+                                       inputInfo,
+                                       outputInfo,
+                                       descriptor);
+
+    return isSupported ? kTfLiteOk : kTfLiteError;
+}
+
+TfLiteStatus VisitResizeOperator(DelegateData& delegateData,
+                                 TfLiteOpaqueContext* tfLiteContext,
+                                 TfLiteOpaqueNode* tfLiteNode,
+                                 int nodeIndex,
+                                 int32_t resizeOperatorCode)
+{
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    // Gather input indices and use to get input tensor.
+    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;
+    }
+
+    // The first input contains the data of the image that should be resized [batch, height, width, channels]
+    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: ",
+                resizeOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    // The second input contains a size tensor. The size tensor contains two integer values
+    // that describe the new height and width of the image [new_height, new_width]
+    const TfLiteOpaqueTensor* tfLiteSizeTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]);
+    if (IsDynamicTensor(tfLiteSizeTensor))
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+                resizeOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    // Gather output indices and use to get 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 output tensor should have the shape [batch, new_height, new_width, channels]
+    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: ",
+                resizeOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo =
+            GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
+    const armnn::TensorInfo& outputTensorInfo =
+            GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
+
+    std::string layerName("Resize");
+
+    // Fill descriptor
+    armnn::ResizeDescriptor desc;
+    switch (resizeOperatorCode)
+    {
+        case kTfLiteBuiltinResizeBilinear:
+        {
+            desc.m_Method = armnn::ResizeMethod::Bilinear;
+
+            layerName += "Bilinear:" + std::to_string(nodeIndex);
+
+            TfLiteResizeBilinearParams* bilinearOptions =
+                    reinterpret_cast<TfLiteResizeBilinearParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+
+            desc.m_AlignCorners = bilinearOptions->align_corners;
+            desc.m_HalfPixelCenters = bilinearOptions->half_pixel_centers;
+            break;
+        }
+        case kTfLiteBuiltinResizeNearestNeighbor:
+        {
+            desc.m_Method =  armnn::ResizeMethod::NearestNeighbor;
+            layerName += "NearestNeighbor:" + std::to_string(nodeIndex);
+
+            TfLiteResizeNearestNeighborParams* nearestNeighborOptions =
+                    reinterpret_cast<TfLiteResizeNearestNeighborParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+
+            desc.m_AlignCorners = nearestNeighborOptions->align_corners;
+            desc.m_HalfPixelCenters = nearestNeighborOptions->half_pixel_centers;
+            break;
+        }
+        default:
+        {
+            TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLiteArmnnOpaqueDelegate: Unknown TfLite built in operation for Resize. "
+                    "Given operator: #%d node #%d: ",
+                    resizeOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+    }
+
+    // In Arm NN the values of the size input tensor [new_height, new_width] is saved in the operator
+    // descriptor. We have to read it from the input tensor and write it to the descriptor.
+
+    auto* sizeTensorDataPtr = static_cast<int*>(TfLiteOpaqueTensorData(tfLiteSizeTensor));
+    auto sizeTensorNumDimensions = TfLiteOpaqueTensorNumDims(tfLiteSizeTensor);
+    // The size tensor is only a 1D tensor -> [new_height, new width]
+    if (sizeTensorNumDimensions != 1)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation is not allowed to be a "
+                "dynamic tensor. Operator: #%d node #%d: ",
+                resizeOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    // Get number of values in the size tensor
+    auto sizeTensorNumValues = TfLiteOpaqueTensorDim(tfLiteSizeTensor,0);
+    if (sizeTensorNumValues == 0)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation is not allowed to be a "
+                "dynamic tensor. Operator: #%d node #%d: ",
+                resizeOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+    else if (sizeTensorNumValues != 2)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation requires to "
+                "have a dimension of 2 [new_height, new width] but a tensor with a dimension of #%d was given. "
+                "Operator: #%d node #%d: ",
+                sizeTensorNumValues, resizeOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+    // get size tensor data
+    std::vector<int32_t> sizeTensorData(sizeTensorDataPtr, sizeTensorDataPtr+sizeTensorNumValues);
+
+    desc.m_TargetHeight = static_cast<uint32_t> (sizeTensorData[0]);
+    desc.m_TargetWidth  = static_cast<uint32_t> (sizeTensorData[1]);
+    desc.m_DataLayout   = armnn::DataLayout::NHWC;
+
+    // No network pointer indicates that only support for this operator should be checked
+    if (!delegateData.m_Network)
+    {
+        return ValidateResizeOperator(delegateData,
+                                      tfLiteContext,
+                                      inputTensorInfo,
+                                      outputTensorInfo,
+                                      desc);
+    }
+
+
+    armnn::IConnectableLayer* resizeLayer = nullptr;
+    resizeLayer = delegateData.m_Network->AddResizeLayer(desc, layerName.c_str());
+
+    armnn::IOutputSlot& outputSlot = resizeLayer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    // try to connect the Constant Inputs if there are any
+    if(ProcessInputs(resizeLayer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+    {
+        return kTfLiteError;
+    }
+
+    ARMNN_ASSERT(resizeLayer != nullptr);
+
+    return Connect(resizeLayer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnOpaqueDelegate
diff --git a/delegate/opaque/src/armnn_delegate.cpp b/delegate/opaque/src/armnn_delegate.cpp
index 9b1c3a1f46..936e75a034 100644
--- a/delegate/opaque/src/armnn_delegate.cpp
+++ b/delegate/opaque/src/armnn_delegate.cpp
@@ -966,6 +966,24 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData,
                                          tfLiteNode,
                                          nodeIndex,
                                          kTfLiteBuiltinQuantize);
+        case kTfLiteBuiltinReduceMax:
+            return VisitReduceOperator(delegateData,
+                                       tfLiteContext,
+                                       tfLiteNode,
+                                       nodeIndex,
+                                       kTfLiteBuiltinReduceMax);
+        case kTfLiteBuiltinReduceMin:
+            return VisitReduceOperator(delegateData,
+                                       tfLiteContext,
+                                       tfLiteNode,
+                                       nodeIndex,
+                                       kTfLiteBuiltinReduceMin);
+        case kTfLiteBuiltinReduceProd:
+            return VisitReduceOperator(delegateData,
+                                       tfLiteContext,
+                                       tfLiteNode,
+                                       nodeIndex,
+                                       kTfLiteBuiltinReduceProd);
         case kTfLiteBuiltinRelu:
             return VisitActivationOperator(delegateData,
                                            tfLiteContext,
@@ -984,6 +1002,18 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData,
                                            tfLiteNode,
                                            nodeIndex,
                                            kTfLiteBuiltinRelu6);
+        case kTfLiteBuiltinResizeNearestNeighbor:
+            return VisitResizeOperator(delegateData,
+                                       tfLiteContext,
+                                       tfLiteNode,
+                                       nodeIndex,
+                                       kTfLiteBuiltinResizeNearestNeighbor);
+        case kTfLiteBuiltinResizeBilinear:
+            return VisitResizeOperator(delegateData,
+                                       tfLiteContext,
+                                       tfLiteNode,
+                                       nodeIndex,
+                                       kTfLiteBuiltinResizeBilinear);
         case kTfLiteBuiltinRsqrt:
             return VisitElementwiseUnaryOperator(delegateData,
                                                  tfLiteContext,
@@ -1035,6 +1065,12 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData,
                                                  nodeIndex,
                                                  kTfLiteBuiltinSqrt,
                                                  armnn::UnaryOperation::Sqrt);
+        case kTfLiteBuiltinSum:
+            return VisitReduceOperator(delegateData,
+                                       tfLiteContext,
+                                       tfLiteNode,
+                                       nodeIndex,
+                                       kTfLiteBuiltinSum);
         case kTfLiteBuiltinTanh:
             return VisitActivationOperator(delegateData,
                                            tfLiteContext,