1 files changed, 135 insertions, 0 deletions
diff --git a/delegate/classic/src/Comparison.hpp b/delegate/classic/src/Comparison.hpp
new file mode 100644
index 0000000000..6d7700d191
--- /dev/null
+++ b/delegate/classic/src/Comparison.hpp
@@ -0,0 +1,135 @@
+//
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <DelegateUtils.hpp>
+#include <armnn/utility/IgnoreUnused.hpp>
+
+#include <tensorflow/lite/builtin_ops.h>
+#include <tensorflow/lite/c/builtin_op_data.h>
+#include <tensorflow/lite/c/common.h>
+#include <tensorflow/lite/minimal_logging.h>
+
+namespace armnnDelegate
+{
+
+TfLiteStatus VisitComparisonOperator(DelegateData& delegateData,
+                                     TfLiteContext* tfLiteContext,
+                                     TfLiteNode* tfLiteNode,
+                                     int nodeIndex,
+                                     int32_t tfLiteComparisonOperatorCode)
+{
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
+    const TfLiteTensor& tfLiteInputTensor0 = tfLiteTensors[tfLiteNode->inputs->data[0]];
+    if (IsDynamicTensor(tfLiteInputTensor0))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+            tfLiteComparisonOperatorCode, nodeIndex);
+
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteInputTensor1 = tfLiteTensors[tfLiteNode->inputs->data[1]];
+    if (IsDynamicTensor(tfLiteInputTensor1))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+            tfLiteComparisonOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
+    if (IsDynamicTensor(tfLiteOutputTensor))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(
+            tfLiteContext,
+            "TfLiteArmnnDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ",
+            tfLiteComparisonOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    armnn::TensorInfo inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0);
+    armnn::TensorInfo inputTensorInfo1 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor1);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
+
+    // Check if we need to expand the dims of any of the input tensor infos.
+    // This is required for a few of the backends.
+    if(inputTensorInfo0.GetNumDimensions() != inputTensorInfo1.GetNumDimensions())
+    {
+        ExpandTensorRankToEqual(inputTensorInfo0, inputTensorInfo1);
+    }
+
+    armnn::ComparisonOperation comparisonOperation = armnn::ComparisonOperation::Equal;
+    switch(tfLiteComparisonOperatorCode)
+    {
+        case kTfLiteBuiltinEqual:
+            comparisonOperation = armnn::ComparisonOperation::Equal;
+            break;
+        case kTfLiteBuiltinGreater:
+            comparisonOperation = armnn::ComparisonOperation::Greater;
+            break;
+        case kTfLiteBuiltinGreaterEqual:
+            comparisonOperation = armnn::ComparisonOperation::GreaterOrEqual;
+            break;
+        case kTfLiteBuiltinLess:
+            comparisonOperation = armnn::ComparisonOperation::Less;
+            break;
+        case kTfLiteBuiltinLessEqual:
+            comparisonOperation = armnn::ComparisonOperation::LessOrEqual;
+            break;
+        case kTfLiteBuiltinNotEqual:
+            comparisonOperation = armnn::ComparisonOperation::NotEqual;
+            break;
+        default:
+            return kTfLiteError;
+    }
+
+    armnn::ComparisonDescriptor descriptor(comparisonOperation);
+    bool isSupported = false;
+    armnn::BackendId setBackend;
+    auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_SUPPORT_FUNC("COMPARISON",
+                                   tfLiteContext,
+                                   IsComparisonSupported,
+                                   delegateData.m_Backends,
+                                   isSupported,
+                                   setBackend,
+                                   inputTensorInfo0,
+                                   inputTensorInfo1,
+                                   outputTensorInfo,
+                                   descriptor);
+    };
+
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    armnn::IConnectableLayer* comparisonLayer = delegateData.m_Network->AddComparisonLayer(descriptor);
+    comparisonLayer->SetBackendId(setBackend);
+    ARMNN_ASSERT(comparisonLayer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = comparisonLayer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    // try to connect the Constant Inputs if there are any
+    if(ProcessInputs(comparisonLayer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+    {
+        return kTfLiteError;
+    }
+
+    return Connect(comparisonLayer, tfLiteNode, delegateData);
+}
+
+} // namespace armnnDelegate