IVGCVSW-7576 IVGCVSW-7609 Add BatchMatMul and Shape to Opaque Delegate

Signed-off-by: John Mcloughlin <john.mcloughlin@arm.com>
Change-Id: Id4b02b951ed81c69171f6af2d0d327175c6e5d3c

6 files changed, 255 insertions, 1 deletions

diff --git a/delegate/CMakeLists.txt b/delegate/CMakeLists.txt
index 4bb9bdd5de..4600f42301 100644
--- a/delegate/CMakeLists.txt
+++ b/delegate/CMakeLists.txt
@@ -263,6 +263,8 @@ if(BUILD_UNIT_TESTS)
              test/ActivationTestHelper.hpp
              test/ArgMinMaxTest.cpp
              test/ArgMinMaxTestHelper.hpp
+             test/BatchMatMulTest.cpp
+             test/BatchMatMulTestHelper.hpp
              test/BatchSpaceTest.cpp
              test/BatchSpaceTestHelper.hpp
              test/CastTest.cpp
@@ -289,6 +291,8 @@ if(BUILD_UNIT_TESTS)
              test/NormalizationTestHelper.hpp
              test/PreluTest.cpp
              test/PreluTestHelper.hpp
+             test/ShapeTest.cpp
+             test/ShapeTestHelper.hpp
              test/TestUtils.hpp
              test/TestUtils.cpp
              test/TransposeConvolution2dTest.cpp)
diff --git a/delegate/opaque/CMakeLists.txt b/delegate/opaque/CMakeLists.txt
index c019649ddf..dd16a70048 100644
--- a/delegate/opaque/CMakeLists.txt
+++ b/delegate/opaque/CMakeLists.txt
@@ -10,6 +10,7 @@ list(APPEND armnnOpaqueDelegateObject_sources
         src/Activation.hpp
         src/ArgMinMax.hpp
         src/armnn_delegate.cpp
+        src/BatchMatMul.hpp
         src/BatchSpace.hpp
         src/Comparison.hpp
         src/Control.hpp
@@ -22,6 +23,7 @@ list(APPEND armnnOpaqueDelegateObject_sources
         src/Normalization.hpp
         src/Prelu.hpp
         src/Redefine.hpp
+        src/Shape.hpp
         src/SharedFunctions.cpp
         src/SharedFunctions.hpp)
 
diff --git a/delegate/opaque/src/ArgMinMax.hpp b/delegate/opaque/src/ArgMinMax.hpp
index 7dfd89f57b..e5499022c6 100644
--- a/delegate/opaque/src/ArgMinMax.hpp
+++ b/delegate/opaque/src/ArgMinMax.hpp
@@ -63,7 +63,7 @@ TfLiteStatus VisitArgMinMaxOperator(DelegateData& delegateData,
     }
 
     const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
-    if (!IsValid(tfLiteContext, tfLiteInputTensor, argMinMaxOperatorCode, nodeIndex))
+    if (!IsValid(tfLiteContext, tfLiteOutputTensor, argMinMaxOperatorCode, nodeIndex))
     {
         return kTfLiteError;
     }
diff --git a/delegate/opaque/src/BatchMatMul.hpp b/delegate/opaque/src/BatchMatMul.hpp
index e16969768e..5da6e5ac6a 100644
--- a/delegate/opaque/src/BatchMatMul.hpp
+++ b/delegate/opaque/src/BatchMatMul.hpp
@@ -2,3 +2,129 @@
 // Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+TfLiteStatus VisitBatchMatMulOperator(DelegateData& delegateData,
+                                      TfLiteOpaqueContext* tfLiteContext,
+                                      TfLiteOpaqueNode* tfLiteNode,
+                                      int nodeIndex,
+                                      int32_t operatorCode)
+{
+    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* kTfLiteLHSInputTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
+    const TfLiteOpaqueTensor* kTfLiteRHSInputTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]);
+
+    if (!IsValid(tfLiteContext, kTfLiteLHSInputTensor, operatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+    if (!IsValid(tfLiteContext, kTfLiteRHSInputTensor, operatorCode, nodeIndex))
+    {
+        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;
+    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* kTfLiteOutputTensor =
+            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+    if (IsDynamicTensor(kTfLiteOutputTensor))
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ",
+                operatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& armnnLHSInputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(kTfLiteLHSInputTensor);
+    const armnn::TensorInfo& armnnRHSInputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(kTfLiteRHSInputTensor);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(kTfLiteOutputTensor, true);
+
+    armnn::BatchMatMulDescriptor descriptor;
+    auto* params = reinterpret_cast<TfLiteBatchMatMulParams *>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+
+    // Tensorflow params are called adjoint, however they are actually just transposes behind the scene. They do
+    // not perform ajoint.
+    descriptor.m_TransposeX = params->adj_x;
+    descriptor.m_TransposeY = params->adj_y;
+
+    // Check if supported
+    bool isSupported = false;
+    armnn::BackendId setBackend;
+    auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("BATCH_MATMUL",
+                                           tfLiteContext,
+                                           IsBatchMatMulSupported,
+                                           delegateData.m_Backends,
+                                           isSupported,
+                                           setBackend,
+                                           armnnLHSInputTensorInfo,
+                                           armnnRHSInputTensorInfo,
+                                           outputTensorInfo,
+                                           descriptor);
+    };
+
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    armnn::IConnectableLayer* layer = delegateData.m_Network->AddBatchMatMulLayer(descriptor);
+    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;
+    }
+
+    return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnOpaqueDelegate
diff --git a/delegate/opaque/src/Shape.hpp b/delegate/opaque/src/Shape.hpp
index e16969768e..ecc545d7c5 100644
--- a/delegate/opaque/src/Shape.hpp
+++ b/delegate/opaque/src/Shape.hpp
@@ -2,3 +2,113 @@
 // Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+
+TfLiteStatus VisitShapeOperator(DelegateData& delegateData,
+                                TfLiteOpaqueContext* tfLiteContext,
+                                TfLiteOpaqueNode* tfLiteNode,
+                                int nodeIndex,
+                                int32_t operatorCode)
+{
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, 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, operatorCode, 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, operatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo  = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
+
+    auto* shapeParameters = reinterpret_cast<TfLiteShapeParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+    if ( shapeParameters->out_type != kTfLiteInt32 && shapeParameters->out_type != kTfLiteInt64 )
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: output_type data type is not supported in operator #%d node #%d: ",
+                operatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    bool isSupported = false;
+    armnn::BackendId setBackend;
+    auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("SHAPE",
+                                           tfLiteContext,
+                                           IsShapeSupported,
+                                           delegateData.m_Backends,
+                                           isSupported,
+                                           setBackend,
+                                           inputTensorInfo,
+                                           outInfo);
+    };
+
+    // If the m_Network is a nullptr, this signals that a prerequisite TfLite callback is required to clarify the
+    // support for the operator
+    // If supported, VisitShapeOperator will be called again to add the layer to the network as seen further below
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    // Add a Shape layer
+    armnn::IConnectableLayer* layer = delegateData.m_Network->AddShapeLayer();
+    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/armnn_delegate.cpp b/delegate/opaque/src/armnn_delegate.cpp
index bffbca8111..3b647f3531 100644
--- a/delegate/opaque/src/armnn_delegate.cpp
+++ b/delegate/opaque/src/armnn_delegate.cpp
@@ -641,6 +641,12 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData,
                                           tfLiteNode,
                                           nodeIndex,
                                           kTfLiteBuiltinArgMin);
+        case kTfLiteBuiltinBatchMatmul:
+            return VisitBatchMatMulOperator(delegateData,
+                                            tfLiteContext,
+                                            tfLiteNode,
+                                            nodeIndex,
+                                            kTfLiteBuiltinBatchMatmul);
         case kTfLiteBuiltinBatchToSpaceNd:
             return VisitBatchToSpaceNdOperator(delegateData,
                                                tfLiteContext,
@@ -853,6 +859,12 @@ TfLiteStatus ArmnnSubgraph::VisitNode(DelegateData& delegateData,
                                                  nodeIndex,
                                                  kTfLiteBuiltinRsqrt,
                                                  armnn::UnaryOperation::Rsqrt);
+        case kTfLiteBuiltinShape:
+            return VisitShapeOperator(delegateData,
+                                      tfLiteContext,
+                                      tfLiteNode,
+                                      nodeIndex,
+                                      kTfLiteBuiltinShape);
         case kTfLiteBuiltinSin:
             return VisitElementwiseUnaryOperator(delegateData,
                                                  tfLiteContext,