IVGCVSW-5829 Segfault in tflite-parser, int8 models

 * Updated ParseSplit TfLiteParser function to read correct axis data.
 * Improved validation in ParseSplit and ParseSplitV function.
 * Added TensorFlow BOOL support to TfLiteParser.
 * Added supported ElementWiseUnary operators to TfLiteParser
   E.g. ABS, LOGICAL_NOT and RSQRT.
 * Removed ParseExp and ParseNeg function implementation in favour
   of reusable ParseElementWiseUnary function.
 * Removed Exp.cpp and Neg.cpp files and moved tests to ElementWiseUnary.cpp.

Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: Ibce36e3ce4d95755dda88abc2ddde1e07e62c5e2

7 files changed, 263 insertions, 231 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 7a1db7bf29..8878065478 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -820,7 +820,7 @@ if(BUILD_UNIT_TESTS)
              src/armnnTfLiteParser/test/Dequantize.cpp
              src/armnnTfLiteParser/test/DetectionPostProcess.cpp
              src/armnnTfLiteParser/test/Div.cpp
-             src/armnnTfLiteParser/test/Exp.cpp
+             src/armnnTfLiteParser/test/ElementWiseUnary.cpp
              src/armnnTfLiteParser/test/FullyConnected.cpp
              src/armnnTfLiteParser/test/Gather.cpp
              src/armnnTfLiteParser/test/L2Normalization.cpp
@@ -831,7 +831,6 @@ if(BUILD_UNIT_TESTS)
              src/armnnTfLiteParser/test/Mean.cpp
              src/armnnTfLiteParser/test/Minimum.cpp
              src/armnnTfLiteParser/test/Multiplication.cpp
-             src/armnnTfLiteParser/test/Neg.cpp
              src/armnnTfLiteParser/test/Pack.cpp
              src/armnnTfLiteParser/test/Pad.cpp
              src/armnnTfLiteParser/test/Reduce.cpp
diff --git a/docs/01_01_parsers.dox b/docs/01_01_parsers.dox
index 05e1225f93..6607921585 100644
--- a/docs/01_01_parsers.dox
+++ b/docs/01_01_parsers.dox
@@ -157,9 +157,10 @@ This reference guide provides a list of TensorFlow Lite operators the Arm NN SDK
 ### Fully supported
 The Arm NN SDK TensorFlow Lite parser currently supports the following operators:
 
+- ABS
 - ADD
 - ARG_MAX
-_ ARG_MIN
+- ARG_MIN
 - AVERAGE_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
 - BATCH_TO_SPACE
 - CONCATENATION, Supported Fused Activation: RELU , RELU6 , TANH, NONE
@@ -174,6 +175,7 @@ _ ARG_MIN
 - GATHER
 - HARD_SWISH
 - LEAKY_RELU
+- LOGICAL_NOT
 - LOGISTIC
 - L2_NORMALIZATION
 - MAX_POOL_2D, Supported Fused Activation: RELU , RELU6 , TANH, NONE
@@ -192,6 +194,7 @@ _ ARG_MIN
 - RESHAPE
 - RESIZE_BILINEAR
 - RESIZE_NEAREST_NEIGHBOR
+- RSQRT
 - SLICE
 - SOFTMAX
 - SPACE_TO_BATCH
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 5f8b08bf85..a68839c20e 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -394,6 +394,9 @@ armnn::TensorInfo ToTensorInfo(TfLiteParserImpl::TensorRawPtr tensorPtr,
         case tflite::TensorType_INT64:
             type = armnn::DataType::Signed64;
             break;
+        case tflite::TensorType_BOOL:
+            type = armnn::DataType::Boolean;
+            break;
         default:
         {
             CheckLocation location = CHECK_LOCATION();
@@ -603,6 +606,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt
 , m_ParserFunctions(tflite::BuiltinOperator_MAX+1, &TfLiteParserImpl::ParseUnsupportedOperator)
 {
     // register supported operators
+    m_ParserFunctions[tflite::BuiltinOperator_ABS]                     = &TfLiteParserImpl::ParseAbs;
     m_ParserFunctions[tflite::BuiltinOperator_ADD]                     = &TfLiteParserImpl::ParseAdd;
     m_ParserFunctions[tflite::BuiltinOperator_ARG_MIN]                 = &TfLiteParserImpl::ParseArgMin;
     m_ParserFunctions[tflite::BuiltinOperator_ARG_MAX]                 = &TfLiteParserImpl::ParseArgMax;
@@ -622,6 +626,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt
     m_ParserFunctions[tflite::BuiltinOperator_GATHER]                  = &TfLiteParserImpl::ParseGather;
     m_ParserFunctions[tflite::BuiltinOperator_HARD_SWISH]              = &TfLiteParserImpl::ParseHardSwish;
     m_ParserFunctions[tflite::BuiltinOperator_LEAKY_RELU]              = &TfLiteParserImpl::ParseLeakyRelu;
+    m_ParserFunctions[tflite::BuiltinOperator_LOGICAL_NOT]             = &TfLiteParserImpl::ParseLogicalNot;
     m_ParserFunctions[tflite::BuiltinOperator_LOGISTIC]                = &TfLiteParserImpl::ParseLogistic;
     m_ParserFunctions[tflite::BuiltinOperator_L2_NORMALIZATION]        = &TfLiteParserImpl::ParseL2Normalization;
     m_ParserFunctions[tflite::BuiltinOperator_MAX_POOL_2D]             = &TfLiteParserImpl::ParseMaxPool2D;
@@ -640,6 +645,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt
     m_ParserFunctions[tflite::BuiltinOperator_RESHAPE]                 = &TfLiteParserImpl::ParseReshape;
     m_ParserFunctions[tflite::BuiltinOperator_RESIZE_BILINEAR]         = &TfLiteParserImpl::ParseResizeBilinear;
     m_ParserFunctions[tflite::BuiltinOperator_RESIZE_NEAREST_NEIGHBOR] = &TfLiteParserImpl::ParseResizeNearestNeighbor;
+    m_ParserFunctions[tflite::BuiltinOperator_RSQRT]                   = &TfLiteParserImpl::ParseRsqrt;
     m_ParserFunctions[tflite::BuiltinOperator_SLICE]                   = &TfLiteParserImpl::ParseSlice;
     m_ParserFunctions[tflite::BuiltinOperator_SOFTMAX]                 = &TfLiteParserImpl::ParseSoftmax;
     m_ParserFunctions[tflite::BuiltinOperator_SPACE_TO_BATCH_ND]       = &TfLiteParserImpl::ParseSpaceToBatchND;
@@ -1090,33 +1096,6 @@ void TfLiteParserImpl::ParseDequantize(size_t subgraphIndex, size_t operatorInde
     RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
 }
 
-void TfLiteParserImpl::ParseExp(size_t subgraphIndex, size_t operatorIndex)
-{
-    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
-
-    auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
-    CHECK_VALID_SIZE(inputs.size(), 1);
-
-    auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
-    CHECK_VALID_SIZE(outputs.size(), 1);
-
-    auto layerName = fmt::format("Exp:{}:{}", subgraphIndex, operatorIndex);
-
-    ElementwiseUnaryDescriptor desc;
-    desc.m_Operation = UnaryOperation::Exp;
-    IConnectableLayer* layer = m_Network->AddElementwiseUnaryLayer(desc, layerName.c_str());
-    ARMNN_ASSERT(layer != nullptr);
-
-    TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true);
-    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
-    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
-    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
-
-    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
-    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
-}
-
 void TfLiteParserImpl::ParseTranspose(size_t subgraphIndex, size_t operatorIndex)
 {
     CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
@@ -1917,31 +1896,6 @@ void TfLiteParserImpl::ParseMean(size_t subgraphIndex, size_t operatorIndex)
     RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
 }
 
-void TfLiteParserImpl::ParseNeg(size_t subgraphIndex, size_t operatorIndex)
-{
-  CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
-
-  auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
-  CHECK_VALID_SIZE(inputs.size(), 1);
-
-  auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
-  CHECK_VALID_SIZE(outputs.size(), 1);
-
-  auto layerName = fmt::format("Neg:{}:{}", subgraphIndex, operatorIndex);
-  armnn::ElementwiseUnaryDescriptor descriptor(armnn::UnaryOperation::Neg);
-  IConnectableLayer* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());
-  ARMNN_ASSERT(layer != nullptr);
-
-  TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true);
-  layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
-  auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
-  RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
-
-  auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
-  RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
-}
-
 void TfLiteParserImpl::ParsePad(size_t subgraphIndex, size_t operatorIndex)
 {
     CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
@@ -2758,15 +2712,35 @@ void TfLiteParserImpl::ParseSplit(size_t subgraphIndex, size_t operatorIndex)
     auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
     CHECK_VALID_SIZE(outputs.size(), numSplits);
 
-    armnn::TensorInfo inputTensorInfo  = ToTensorInfo(inputs[1]);
-    armnn::TensorInfo axisTensorInfo = ToTensorInfo(inputs[0]);
+    armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[1]);
+    armnn::TensorInfo axisTensorInfo  = ToTensorInfo(inputs[0]);
+    ARMNN_ASSERT(axisTensorInfo.GetNumElements() == 1);
 
     BufferRawPtr axisBufferPtr = GetBuffer(m_Model, inputs[0]->buffer);
-    std::vector<unsigned int> axisData(axisTensorInfo.GetNumElements());
+    if (axisBufferPtr == nullptr)
+    {
+        throw ParseException(
+                fmt::format("Operation has invalid inputs. Failed to read axis. {}",
+                            CHECK_LOCATION().AsString()));
+    }
+
+    std::vector<int32_t> axisData(axisTensorInfo.GetNumElements());
     ::memcpy(axisData.data(), axisBufferPtr->data.data(), axisTensorInfo.GetNumBytes());
+    int32_t axis = axisData[0];
 
-    ARMNN_ASSERT(axisTensorInfo.GetNumElements() == 1);
-    const unsigned int splitDim = axisData[0];
+    auto inputDimensions = static_cast<int32_t>(inputTensorInfo.GetNumDimensions());
+    if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0)))
+    {
+        // Square bracket denotes inclusive n while parenthesis denotes exclusive n
+        // E.g. Rank 4 tensor can have axis in range [-4, 3)
+        // -1 == 3, -2 == 2, -3 == 1, -4 == 0
+        throw ParseException(
+                fmt::format("Operation has invalid axis: {}. Axis must be in range [-n, n) {}",
+                            axis,
+                            CHECK_LOCATION().AsString()));
+    }
+
+    const unsigned int splitDim = armnnUtils::GetUnsignedAxis(inputTensorInfo.GetNumDimensions(), axis);
 
     auto inputDimSize = inputTensorInfo.GetNumDimensions();
     if (inputDimSize > MaxNumOfTensorDimensions)
@@ -2863,9 +2837,29 @@ void TfLiteParserImpl::ParseSplitV(size_t subgraphIndex, size_t operatorIndex)
 
     // Get split axis
     BufferRawPtr axisBufferPtr = GetBuffer(m_Model, axisTensor->buffer);
+    if (axisBufferPtr == nullptr)
+    {
+        throw ParseException(
+                fmt::format("Operation has invalid inputs. Failed to read axis. {}",
+                            CHECK_LOCATION().AsString()));
+    }
+
     std::vector<int> axisData(axisTensorInfo.GetNumElements());
     ::memcpy(axisData.data(), axisBufferPtr->data.data(), axisTensorInfo.GetNumBytes());
-    const unsigned int splitDim = ComputeWrappedIndex(axisData[0], inputTensorInfo.GetNumDimensions());
+    int32_t axis = axisData[0];
+
+    auto inputDimensions = static_cast<int32_t>(inputTensorInfo.GetNumDimensions());
+    if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0)))
+    {
+        // Square bracket denotes inclusive n while parenthesis denotes exclusive n
+        // E.g. Rank 4 tensor can have axis in range [-4, 3)
+        // -1 == 3, -2 == 2, -3 == 1, -4 == 0
+        throw ParseException(
+                fmt::format("Operation has invalid axis: {}. Axis must be in range [-n, n) {}",
+                            axis,
+                            CHECK_LOCATION().AsString()));
+    }
+    const unsigned int splitDim = ComputeWrappedIndex(axis, inputTensorInfo.GetNumDimensions());
 
     // Set split sizes
     CHECK_VALID_SIZE(splitsInfo.GetNumDimensions(), 1);
@@ -2988,6 +2982,7 @@ void TfLiteParserImpl::ParseArgMinMax(size_t subgraphIndex, size_t operatorIndex
     armnn::TensorInfo inputTensorInfo  = ToTensorInfo(inputs[0]);
     armnn::TensorInfo axisTensorInfo   = ToTensorInfo(inputs[1]);
     armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+    ARMNN_ASSERT(axisTensorInfo.GetNumElements() == 1);
 
     // Check if output tensor type is Signed32 or Signed64
     if (outputTensorInfo.GetDataType() != armnn::DataType::Signed32 &&
@@ -3210,6 +3205,59 @@ void TfLiteParserImpl::ParseReduce(size_t subgraphIndex, size_t operatorIndex, R
     RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
 }
 
+void TfLiteParserImpl::ParseAbs(size_t subgraphIndex, size_t operatorIndex)
+{
+    ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Abs);
+}
+
+void TfLiteParserImpl::ParseExp(size_t subgraphIndex, size_t operatorIndex)
+{
+    ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Exp);
+}
+
+void TfLiteParserImpl::ParseLogicalNot(size_t subgraphIndex, size_t operatorIndex)
+{
+    ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::LogicalNot);
+}
+
+void TfLiteParserImpl::ParseNeg(size_t subgraphIndex, size_t operatorIndex)
+{
+    ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Neg);
+}
+
+void TfLiteParserImpl::ParseRsqrt(size_t subgraphIndex, size_t operatorIndex)
+{
+    ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Rsqrt);
+}
+
+void TfLiteParserImpl::ParseElementwiseUnary(size_t subgraphIndex, size_t operatorIndex, UnaryOperation unaryOperation)
+{
+    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+    auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(inputs.size(), 1);
+
+    auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    std::string layerName = std::string(GetUnaryOperationAsCString(unaryOperation)) + ":{}:{}";
+    std::string layerNameFormatted = fmt::format(layerName, subgraphIndex, operatorIndex);
+
+    ElementwiseUnaryDescriptor desc;
+    desc.m_Operation = unaryOperation;
+    IConnectableLayer* layer = m_Network->AddElementwiseUnaryLayer(desc, layerNameFormatted.c_str());
+    ARMNN_ASSERT(layer != nullptr);
+
+    TensorInfo outputTensorInfo = ToTensorInfo(outputs[0], true);
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
+
+    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, outputTensorIndexes);
+}
+
 armnn::IConnectableLayer* TfLiteParserImpl::AddFusedActivationLayer(armnn::IConnectableLayer* prevLayer,
                                                                     unsigned int outputSlot,
                                                                     tflite::ActivationFunctionType activationType)
diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp
index af844d2ef3..0aee07dc21 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -97,6 +97,7 @@ private:
     void ParseCustomOperator(size_t subgraphIndex, size_t operatorIndex);
     void ParseUnsupportedOperator(size_t subgraphIndex, size_t operatorIndex);
 
+    void ParseAbs(size_t subgraphIndex, size_t operatorIndex);
     void ParseActivation(size_t subgraphIndex, size_t operatorIndex, armnn::ActivationFunction activationType);
     void ParseAdd(size_t subgraphIndex, size_t operatorIndex);
     void ParseArgMinMax(size_t subgraphIndex, size_t operatorIndex, armnn::ArgMinMaxFunction argMinMaxFunction);
@@ -112,12 +113,14 @@ private:
     void ParseDequantize(size_t subgraphIndex, size_t operatorIndex);
     void ParseDetectionPostProcess(size_t subgraphIndex, size_t operatorIndex);
     void ParseDiv(size_t subgraphIndex, size_t operatorIndex);
+    void ParseElementwiseUnary(size_t subgraphIndex, size_t operatorIndex, armnn::UnaryOperation unaryOperation);
     void ParseElu(size_t subgraphIndex, size_t operatorIndex);
     void ParseExp(size_t subgraphIndex, size_t operatorIndex);
     void ParseFullyConnected(size_t subgraphIndex, size_t operatorIndex);
     void ParseGather(size_t subgraphIndex, size_t operatorIndex);
     void ParseHardSwish(size_t subgraphIndex, size_t operatorIndex);
     void ParseLeakyRelu(size_t subgraphIndex, size_t operatorIndex);
+    void ParseLogicalNot(size_t subgraphIndex, size_t operatorIndex);
     void ParseLogistic(size_t subgraphIndex, size_t operatorIndex);
     void ParseL2Normalization(size_t subgraphIndex, size_t operatorIndex);
     void ParseMaxPool2D(size_t subgraphIndex, size_t operatorIndex);
@@ -139,6 +142,7 @@ private:
     void ParseResize(size_t subgraphIndex, size_t operatorIndex, armnn::ResizeMethod resizeMethod);
     void ParseResizeBilinear(size_t subgraphIndex, size_t operatorIndex);
     void ParseResizeNearestNeighbor(size_t subgraphIndex, size_t operatorIndex);
+    void ParseRsqrt(size_t subgraphIndex, size_t operatorIndex);
     void ParseSlice(size_t subgraphIndex, size_t operatorIndex);
     void ParseSoftmax(size_t subgraphIndex, size_t operatorIndex);
     void ParseSpaceToBatchND(size_t subgraphIndex, size_t operatorIndex);
diff --git a/src/armnnTfLiteParser/test/ElementWiseUnary.cpp b/src/armnnTfLiteParser/test/ElementWiseUnary.cpp
new file mode 100644
index 0000000000..dc236d2637
--- /dev/null
+++ b/src/armnnTfLiteParser/test/ElementWiseUnary.cpp
@@ -0,0 +1,148 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersFixture.hpp"
+#include "../TfLiteParser.hpp"
+
+#include <string>
+
+BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
+
+struct ElementWiseUnaryFixture : public ParserFlatbuffersFixture
+{
+    explicit ElementWiseUnaryFixture(const std::string& operatorCode,
+                                     const std::string& dataType,
+                                     const std::string& inputShape,
+                                     const std::string& outputShape)
+    {
+        m_JsonString = R"(
+            {
+                "version": 3,
+                "operator_codes": [ { "builtin_code": )" + operatorCode + R"( } ],
+                "subgraphs": [ {
+                    "tensors": [
+                        {
+                            "shape": )" + inputShape + R"(,
+                            "type": )" + dataType + R"( ,
+                            "buffer": 0,
+                            "name": "inputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {
+                            "shape": )" + outputShape + R"( ,
+                            "type": )" + dataType + R"( ,
+                            "buffer": 1,
+                            "name": "outputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        }
+                    ],
+                    "inputs": [ 0 ],
+                    "outputs": [ 1 ],
+                    "operators": [
+                        {
+                            "opcode_index": 0,
+                            "inputs": [ 0 ],
+                            "outputs": [ 1 ],
+                            "custom_options_format": "FLEXBUFFERS"
+                        }
+                    ],
+                } ],
+                "buffers" : [
+                    { },
+                    { }
+                ]
+            }
+        )";
+        Setup();
+    }
+};
+
+struct SimpleAbsFixture : public ElementWiseUnaryFixture
+{
+    SimpleAbsFixture() : ElementWiseUnaryFixture("ABS", "FLOAT32", "[ 2, 2 ]", "[ 2, 2 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseAbs, SimpleAbsFixture)
+{
+    std::vector<float> inputValues
+    {
+        -0.1f, 0.2f,
+        0.3f, -0.4f
+    };
+
+    // Calculate output data
+    std::vector<float> expectedOutputValues(inputValues.size());
+    for (unsigned int i = 0; i < inputValues.size(); ++i)
+    {
+        expectedOutputValues[i] = std::abs(inputValues[i]);
+    }
+
+    RunTest<2, armnn::DataType::Float32>(0, {{ "inputTensor", { inputValues } }},
+                                            {{ "outputTensor",{ expectedOutputValues } } });
+}
+
+struct SimpleExpFixture : public ElementWiseUnaryFixture
+{
+    SimpleExpFixture() : ElementWiseUnaryFixture("EXP", "FLOAT32", "[ 1, 2, 3, 1 ]", "[ 1, 2, 3, 1 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseExp, SimpleExpFixture)
+{
+    RunTest<4, armnn::DataType::Float32>(0, {{ "inputTensor", { 0.0f,  1.0f,  2.0f,
+                                                                3.0f,  4.0f,  5.0f} }},
+                                            {{ "outputTensor",{ 1.0f,  2.718281f,  7.3890515f,
+                                                                20.0855185f, 54.5980834f, 148.4129329f} } });
+}
+
+struct SimpleLogicalNotFixture : public ElementWiseUnaryFixture
+{
+    SimpleLogicalNotFixture() : ElementWiseUnaryFixture("LOGICAL_NOT", "BOOL", "[ 1, 1, 1, 4 ]", "[ 1, 1, 1, 4 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseLogicalNot, SimpleLogicalNotFixture)
+{
+    RunTest<4, armnn::DataType::Boolean>(0, {{ "inputTensor", { 0, 1, 0, 1 } }},
+                                            {{ "outputTensor",{ 1, 0, 1, 0 } } });
+}
+
+struct SimpleNegFixture : public ElementWiseUnaryFixture
+{
+    SimpleNegFixture() : ElementWiseUnaryFixture("NEG", "FLOAT32", "[ 1, 2, 3, 1 ]", "[ 1, 2, 3, 1 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseNeg, SimpleNegFixture)
+{
+    RunTest<4, armnn::DataType::Float32>(0, {{ "inputTensor", { 0.0f, 1.0f, -2.0f,
+                                                                20.0855185f, -54.5980834f, 5.0f} }},
+                                            {{ "outputTensor",{ 0.0f, -1.0f, 2.0f,
+                                                                -20.0855185f, 54.5980834f, -5.0f} }});
+}
+
+struct SimpleRsqrtFixture : public ElementWiseUnaryFixture
+{
+    SimpleRsqrtFixture() : ElementWiseUnaryFixture("RSQRT", "FLOAT32", "[ 1, 2, 3, 1 ]", "[ 1, 2, 3, 1 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseRsqrt, SimpleRsqrtFixture)
+{
+    RunTest<4, armnn::DataType::Float32>(0, {{ "inputTensor", { 1.0f, 4.0f, 16.0f,
+                                                                25.0f, 64.0f, 100.0f } }},
+                                            {{ "outputTensor",{ 1.0f, 0.5f, 0.25f,
+                                                                0.2f, 0.125f, 0.1f} }});
+}
+
+
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnTfLiteParser/test/Exp.cpp b/src/armnnTfLiteParser/test/Exp.cpp
deleted file mode 100644
index 168cc45dd9..0000000000
--- a/src/armnnTfLiteParser/test/Exp.cpp
+++ /dev/null
@@ -1,85 +0,0 @@
-//
-// Copyright © 2020 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include <boost/test/unit_test.hpp>
-#include "ParserFlatbuffersFixture.hpp"
-#include "../TfLiteParser.hpp"
-
-#include <string>
-
-BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
-
-struct ExpFixture : public ParserFlatbuffersFixture
-{
-    explicit ExpFixture(const std::string & inputShape,
-                                   const std::string & outputShape)
-    {
-        m_JsonString = R"(
-            {
-                "version": 3,
-                "operator_codes": [ { "builtin_code": "EXP" } ],
-                "subgraphs": [ {
-                    "tensors": [
-                        {
-                            "shape": )" + inputShape + R"(,
-                            "type": "FLOAT32",
-                            "buffer": 0,
-                            "name": "inputTensor",
-                            "quantization": {
-                                "min": [ 0.0 ],
-                                "max": [ 255.0 ],
-                                "scale": [ 1.0 ],
-                                "zero_point": [ 0 ],
-                            }
-                        },
-                        {
-                            "shape": )" + outputShape + R"( ,
-                            "type": "FLOAT32",
-                            "buffer": 1,
-                            "name": "outputTensor",
-                            "quantization": {
-                                "min": [ 0.0 ],
-                                "max": [ 255.0 ],
-                                "scale": [ 1.0 ],
-                                "zero_point": [ 0 ],
-                            }
-                        }
-                    ],
-                    "inputs": [ 0 ],
-                    "outputs": [ 1 ],
-                    "operators": [
-                        {
-                            "opcode_index": 0,
-                            "inputs": [ 0 ],
-                            "outputs": [ 1 ],
-                            "custom_options_format": "FLEXBUFFERS"
-                        }
-                    ],
-                } ],
-                "buffers" : [
-                    { },
-                    { }
-                ]
-            }
-        )";
-        Setup();
-    }
-};
-
-struct SimpleExpFixture : public ExpFixture
-{
-    SimpleExpFixture() : ExpFixture("[ 1, 2, 3, 1 ]", "[ 1, 2, 3, 1 ]") {}
-};
-
-BOOST_FIXTURE_TEST_CASE(ParseExp, SimpleExpFixture)
-{
-    using armnn::DataType;
-    RunTest<4, DataType::Float32>(0, {{ "inputTensor", { 0.0f,  1.0f,  2.0f,
-                                                            3.0f,  4.0f,  5.0f} }},
-                                  {{ "outputTensor", { 1.0f,  2.718281f,  7.3890515f,
-                                                         20.0855185f, 54.5980834f, 148.4129329f} } });
-}
-
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
diff --git a/src/armnnTfLiteParser/test/Neg.cpp b/src/armnnTfLiteParser/test/Neg.cpp
deleted file mode 100644
index 39e1f9e82c..0000000000
--- a/src/armnnTfLiteParser/test/Neg.cpp
+++ /dev/null
@@ -1,85 +0,0 @@
-//
-// Copyright © 2020 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include <boost/test/unit_test.hpp>
-#include "ParserFlatbuffersFixture.hpp"
-#include "../TfLiteParser.hpp"
-
-#include <string>
-
-BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
-
-struct NegFixture : public ParserFlatbuffersFixture
-{
-    explicit NegFixture(const std::string & inputShape,
-                        const std::string & outputShape)
-    {
-        m_JsonString = R"(
-            {
-                "version": 3,
-                "operator_codes": [ { "builtin_code": "NEG" } ],
-                "subgraphs": [ {
-                    "tensors": [
-                        {
-                            "shape": )" + inputShape + R"(,
-                            "type": "FLOAT32",
-                            "buffer": 0,
-                            "name": "inputTensor",
-                            "quantization": {
-                                "min": [ 0.0 ],
-                                "max": [ 255.0 ],
-                                "scale": [ 1.0 ],
-                                "zero_point": [ 0 ],
-                            }
-                        },
-                        {
-                            "shape": )" + outputShape + R"( ,
-                            "type": "FLOAT32",
-                            "buffer": 1,
-                            "name": "outputTensor",
-                            "quantization": {
-                                "min": [ 0.0 ],
-                                "max": [ 255.0 ],
-                                "scale": [ 1.0 ],
-                                "zero_point": [ 0 ],
-                            }
-                        }
-                    ],
-                    "inputs": [ 0 ],
-                    "outputs": [ 1 ],
-                    "operators": [
-                        {
-                            "opcode_index": 0,
-                            "inputs": [ 0 ],
-                            "outputs": [ 1 ],
-                            "custom_options_format": "FLEXBUFFERS"
-                        }
-                    ],
-                } ],
-                "buffers" : [
-                    { },
-                    { }
-                ]
-            }
-        )";
-        Setup();
-    }
-};
-
-struct SimpleNegFixture : public NegFixture
-{
-    SimpleNegFixture() : NegFixture("[ 1, 2, 3, 1 ]", "[ 1, 2, 3, 1 ]") {}
-};
-
-BOOST_FIXTURE_TEST_CASE(ParseNeg, SimpleNegFixture)
-{
-    using armnn::DataType;
-    RunTest<4, DataType::Float32>(0, {{ "inputTensor", { 0.0f, 1.0f, -2.0f,
-                                                         20.0855185f, -54.5980834f, 5.0f} }},
-                                     {{ "outputTensor",{ 0.0f, -1.0f, 2.0f,
-                                                         -20.0855185f, 54.5980834f, -5.0f} }});
-}
-
-BOOST_AUTO_TEST_SUITE_END()