IVGCVSW-5381 TfLiteDelegate: Implement the Logical operators

 * Implemented Logical AND, NOT and OR operators.
 * NOT uses existing ElementwiseUnary VisitLayer function & tests.
 * AND/OR uses new LogicalBinary VisitLayer function & tests.

Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: I5e7f1e78b30c36ac7f14c70a712b54f98d664b83

1 files changed, 122 insertions, 0 deletions

diff --git a/delegate/src/LogicalBinary.hpp b/delegate/src/LogicalBinary.hpp
new file mode 100644
index 0000000000..07b55c3e32
--- /dev/null
+++ b/delegate/src/LogicalBinary.hpp
@@ -0,0 +1,122 @@
+//
+// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#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 VisitLogicalBinaryOperator(DelegateData& delegateData,
+                                        TfLiteContext* tfLiteContext,
+                                        TfLiteNode* tfLiteNode,
+                                        int nodeIndex,
+                                        int32_t logicalOperatorCode,
+                                        armnn::LogicalBinaryOperation binaryOperation)
+{
+    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 (!IsValid(tfLiteContext, tfLiteInputTensor0, logicalOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteInputTensor1 = tfLiteTensors[tfLiteNode->inputs->data[1]];
+    if (!IsValid(tfLiteContext, tfLiteInputTensor1, logicalOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
+    if (!IsValid(tfLiteContext, tfLiteOutputTensor, logicalOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    armnn::TensorInfo inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0);
+    armnn::TensorInfo inputTensorInfo1 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor1);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor);
+
+    // Setup descriptor and assign operation
+    armnn::LogicalBinaryDescriptor desc;
+    desc.m_Operation = binaryOperation;
+
+    // Check if supported
+    bool isSupported = false;
+    auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_SUPPORT_FUNC(__func__,
+                                   tfLiteContext,
+                                   IsLogicalBinarySupported,
+                                   delegateData.m_Backends,
+                                   isSupported,
+                                   inputTensorInfo0,
+                                   inputTensorInfo1,
+                                   outputTensorInfo,
+                                   desc);
+    };
+
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    armnn::IConnectableLayer* logicalBinaryLayer = delegateData.m_Network->AddLogicalBinaryLayer(desc);
+    ARMNN_ASSERT(logicalBinaryLayer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = logicalBinaryLayer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    if(tflite::IsConstantTensor(&tfLiteInputTensor0))
+    {
+        auto status = ConnectConstant(logicalBinaryLayer,
+                                      inputTensorInfo0,
+                                      tfLiteContext,
+                                      tfLiteInputTensor0,
+                                      delegateData,
+                                      tfLiteNode->inputs->data[0]);
+        if (status == kTfLiteError)
+        {
+            return status;
+        }
+    }
+
+    if(tflite::IsConstantTensor(&tfLiteInputTensor1))
+    {
+        auto status = ConnectConstant(logicalBinaryLayer,
+                                      inputTensorInfo1,
+                                      tfLiteContext,
+                                      tfLiteInputTensor1,
+                                      delegateData,
+                                      tfLiteNode->inputs->data[1]);
+        if (status == kTfLiteError)
+        {
+            return status;
+        }
+    }
+
+    // LogicalBinary operators support broadcasting
+    auto reshapeLayer = BroadcastTensor(inputTensorInfo0,
+                                        inputTensorInfo1,
+                                        logicalBinaryLayer,
+                                        tfLiteContext,
+                                        tfLiteNode,
+                                        delegateData);
+    if (!reshapeLayer)
+    {
+        return kTfLiteError;
+    }
+    return kTfLiteOk;
+}
+
+} // namespace armnnDelegate