IVGCVSW-7400 POW IVGCVSW-7278 SQUARED_DIFFERENCE.

* Added 2 new operators as ElementWiseBinary ops
* Ref End to End and unit tests
* Serialize and Deserialize tests
* Delegate and Opaque Delegate tests
* TfLite Parser tests

Signed-off-by: John Mcloughlin <john.mcloughlin@arm.com>
Change-Id: I537158127f602f0c41ca0402aa31655cd3bd4281

4 files changed, 266 insertions, 0 deletions

diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 244f1fa197..5075da41c2 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -797,6 +797,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt
     m_ParserFunctions[tflite::BuiltinOperator_PACK]                    = &TfLiteParserImpl::ParsePack;
     m_ParserFunctions[tflite::BuiltinOperator_PAD]                     = &TfLiteParserImpl::ParsePad;
     m_ParserFunctions[tflite::BuiltinOperator_PADV2]                   = &TfLiteParserImpl::ParsePad;
+    m_ParserFunctions[tflite::BuiltinOperator_POW]                     = &TfLiteParserImpl::ParsePower;
     m_ParserFunctions[tflite::BuiltinOperator_PRELU]                   = &TfLiteParserImpl::ParsePrelu;
     m_ParserFunctions[tflite::BuiltinOperator_QUANTIZE]                = &TfLiteParserImpl::ParseQuantize;
     m_ParserFunctions[tflite::BuiltinOperator_RELU]                    = &TfLiteParserImpl::ParseRelu;
@@ -818,6 +819,7 @@ TfLiteParserImpl::TfLiteParserImpl(const Optional<ITfLiteParser::TfLiteParserOpt
     m_ParserFunctions[tflite::BuiltinOperator_SPLIT]                   = &TfLiteParserImpl::ParseSplit;
     m_ParserFunctions[tflite::BuiltinOperator_SPLIT_V]                 = &TfLiteParserImpl::ParseSplitV;
     m_ParserFunctions[tflite::BuiltinOperator_SQUEEZE]                 = &TfLiteParserImpl::ParseSqueeze;
+    m_ParserFunctions[tflite::BuiltinOperator_SQUARED_DIFFERENCE]      = &TfLiteParserImpl::ParseSquaredDifference;
     m_ParserFunctions[tflite::BuiltinOperator_STRIDED_SLICE]           = &TfLiteParserImpl::ParseStridedSlice;
     m_ParserFunctions[tflite::BuiltinOperator_SUB]                     = &TfLiteParserImpl::ParseSub;
     m_ParserFunctions[tflite::BuiltinOperator_SUM]                     = &TfLiteParserImpl::ParseSum;
@@ -4584,6 +4586,36 @@ void TfLiteParserImpl::ParseNeg(size_t subgraphIndex, size_t operatorIndex)
     ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Neg);
 }
 
+void TfLiteParserImpl::ParsePower(size_t subgraphIndex, size_t operatorIndex)
+{
+    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+    auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(inputs.size(), 2);
+
+    auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    auto layerName = fmt::format("Power:{}:{}", subgraphIndex, operatorIndex);
+
+    TensorInfo inputTensorInfo  = InputTensorInfo(subgraphIndex, operatorIndex, 0);
+    TensorInfo input1TensorInfo = InputTensorInfo(subgraphIndex, operatorIndex, 1);
+    CheckMatchingQuantization(inputTensorInfo, input1TensorInfo, layerName, "Input 0", "Input 1");
+
+    IConnectableLayer* layer = m_Network->AddElementwiseBinaryLayer(BinaryOperation::Power, layerName.c_str());
+    ARMNN_ASSERT(layer != nullptr);
+
+    TensorInfo outputTensorInfo = OutputTensorInfoFromInputs(subgraphIndex, operatorIndex, layer, 0, {0, 1});
+    CheckMatchingQuantization(inputTensorInfo, outputTensorInfo, layerName, "Input 0", "Output 0");
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
+
+    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
+}
+
 void TfLiteParserImpl::ParseRsqrt(size_t subgraphIndex, size_t operatorIndex)
 {
     ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Rsqrt);
@@ -4599,6 +4631,36 @@ void TfLiteParserImpl::ParseSqrt(size_t subgraphIndex, size_t operatorIndex)
     ParseElementwiseUnary(subgraphIndex, operatorIndex, armnn::UnaryOperation::Sqrt);
 }
 
+void TfLiteParserImpl::ParseSquaredDifference(size_t subgraphIndex, size_t operatorIndex)
+{
+    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+    auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(inputs.size(), 2);
+
+    auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    auto layerName = fmt::format("SquaredDifference:{}:{}", subgraphIndex, operatorIndex);
+
+    TensorInfo inputTensorInfo  = InputTensorInfo(subgraphIndex, operatorIndex, 0);
+    TensorInfo input1TensorInfo = InputTensorInfo(subgraphIndex, operatorIndex, 1);
+    CheckMatchingQuantization(inputTensorInfo, input1TensorInfo, layerName, "Input 0", "Input 1");
+
+    IConnectableLayer* layer = m_Network->AddElementwiseBinaryLayer(BinaryOperation::SqDiff, layerName.c_str());
+    ARMNN_ASSERT(layer != nullptr);
+
+    TensorInfo outputTensorInfo = OutputTensorInfoFromInputs(subgraphIndex, operatorIndex, layer, 0, {0, 1});
+    CheckMatchingQuantization(inputTensorInfo, outputTensorInfo, layerName, "Input 0", "Output 0");
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
+
+    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
+}
+
 void TfLiteParserImpl::ParseElementwiseUnary(size_t subgraphIndex, size_t operatorIndex, UnaryOperation unaryOperation)
 {
     CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp
index 91fad43b8a..774d054572 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -163,6 +163,7 @@ private:
     void ParsePack(size_t subgraphIndex, size_t operatorIndex);
     void ParsePad(size_t subgraphIndex, size_t operatorIndex);
     void ParsePool(size_t subgraphIndex, size_t operatorIndex, armnn::PoolingAlgorithm algorithm);
+    void ParsePower(size_t subgraphIndex, size_t operatorIndex);
     void ParsePrelu(size_t subgraphIndex, size_t operatorIndex);
     void ParseQuantize(size_t subgraphIndex, size_t operatorIndex);
     void ParseReduce(size_t subgraphIndex, size_t operatorIndex, armnn::ReduceOperation reduceOperation);
@@ -186,6 +187,7 @@ private:
     void ParseSplit(size_t subgraphIndex, size_t operatorIndex);
     void ParseSplitV(size_t subgraphIndex, size_t operatorIndex);
     void ParseSqueeze(size_t subgraphIndex, size_t operatorIndex);
+    void ParseSquaredDifference(size_t subgraphIndex, size_t operatorIndex);
     void ParseStridedSlice(size_t subgraphIndex, size_t operatorIndex);
     void ParseSub(size_t subgraphIndex, size_t operatorIndex);
     void ParseSum(size_t subgraphIndex, size_t operatorIndex);
diff --git a/src/armnnTfLiteParser/test/Power.cpp b/src/armnnTfLiteParser/test/Power.cpp
new file mode 100644
index 0000000000..f8b354a2d2
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Power.cpp
@@ -0,0 +1,101 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ParserFlatbuffersFixture.hpp"
+
+#include <doctest/doctest.h>
+
+
+TEST_SUITE("TensorflowLiteParser_Power")
+{
+    struct PowerFixture : public ParserFlatbuffersFixture
+    {
+        explicit PowerFixture(const std::string & inputShape1,
+                              const std::string & inputShape2,
+                              const std::string & outputShape,
+                              const std::string & activation="NONE")
+        {
+            m_JsonString = R"(
+            {
+                "version": 3,
+                "operator_codes": [ { "builtin_code": "POW" } ],
+                "subgraphs": [ {
+                    "tensors": [
+                        {
+                            "shape": )" + inputShape1 + R"(,
+                            "type": "UINT8",
+                            "buffer": 0,
+                            "name": "inputTensor1",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {
+                            "shape": )" + inputShape2 + R"(,
+                            "type": "UINT8",
+                            "buffer": 1,
+                            "name": "inputTensor2",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {
+                            "shape": )" + outputShape + R"( ,
+                            "type": "UINT8",
+                            "buffer": 2,
+                            "name": "outputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        }
+                    ],
+                    "inputs": [ 0, 1 ],
+                    "outputs": [ 2 ],
+                    "operators": [
+                        {
+                            "opcode_index": 0,
+                            "inputs": [ 0, 1 ],
+                            "outputs": [ 2 ],
+                            "custom_options_format": "FLEXBUFFERS"
+                        }
+                    ],
+                } ],
+                "buffers" : [
+                    { },
+                    { }
+                ]
+            }
+        )";
+            Setup();
+        }
+    };
+
+
+    struct SimplePowerFixture : PowerFixture
+    {
+        SimplePowerFixture() : PowerFixture("[ 2, 2 ]",
+                                            "[ 2, 2 ]",
+                                            "[ 2, 2 ]") {}
+    };
+
+    TEST_CASE_FIXTURE(SimplePowerFixture, "SimplePower")
+    {
+        RunTest<2, armnn::DataType::QAsymmU8>(
+                0,
+                {{"inputTensor1", { 0, 1, 2, 3 }},
+                 {"inputTensor2", { 4, 5, 6, 3 }}},
+                {{"outputTensor", { 0, 1, 64, 27 }}});
+    }
+
+}
\ No newline at end of file
diff --git a/src/armnnTfLiteParser/test/SquaredDifference.cpp b/src/armnnTfLiteParser/test/SquaredDifference.cpp
new file mode 100644
index 0000000000..97b4d3fede
--- /dev/null
+++ b/src/armnnTfLiteParser/test/SquaredDifference.cpp
@@ -0,0 +1,101 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ParserFlatbuffersFixture.hpp"
+
+#include <doctest/doctest.h>
+
+
+TEST_SUITE("TensorflowLiteParser_SquaredDifference")
+{
+    struct SquaredDifferenceFixture : public ParserFlatbuffersFixture
+    {
+        explicit SquaredDifferenceFixture(const std::string & inputShape1,
+                                          const std::string & inputShape2,
+                                          const std::string & outputShape,
+                                          const std::string & activation="NONE")
+        {
+            m_JsonString = R"(
+                {
+                    "version": 3,
+                    "operator_codes": [ { "builtin_code": "SQUARED_DIFFERENCE" } ],
+                    "subgraphs": [ {
+                        "tensors": [
+                            {
+                                "shape": )" + inputShape1 + R"(,
+                                "type": "UINT8",
+                                "buffer": 0,
+                                "name": "inputTensor1",
+                                "quantization": {
+                                    "min": [ 0.0 ],
+                                    "max": [ 255.0 ],
+                                    "scale": [ 1.0 ],
+                                    "zero_point": [ 0 ],
+                                }
+                            },
+                            {
+                                "shape": )" + inputShape2 + R"(,
+                                "type": "UINT8",
+                                "buffer": 1,
+                                "name": "inputTensor2",
+                                "quantization": {
+                                    "min": [ 0.0 ],
+                                    "max": [ 255.0 ],
+                                    "scale": [ 1.0 ],
+                                    "zero_point": [ 0 ],
+                                }
+                            },
+                            {
+                                "shape": )" + outputShape + R"( ,
+                                "type": "UINT8",
+                                "buffer": 2,
+                                "name": "outputTensor",
+                                "quantization": {
+                                    "min": [ 0.0 ],
+                                    "max": [ 255.0 ],
+                                    "scale": [ 1.0 ],
+                                    "zero_point": [ 0 ],
+                                }
+                            }
+                        ],
+                        "inputs": [ 0, 1 ],
+                        "outputs": [ 2 ],
+                        "operators": [
+                            {
+                                "opcode_index": 0,
+                                "inputs": [ 0, 1 ],
+                                "outputs": [ 2 ],
+                                "custom_options_format": "FLEXBUFFERS"
+                            }
+                        ],
+                    } ],
+                    "buffers" : [
+                        { },
+                        { }
+                    ]
+                }
+            )";
+            Setup();
+        }
+    };
+
+
+    struct SimpleSquaredDifferenceFixture : SquaredDifferenceFixture
+    {
+        SimpleSquaredDifferenceFixture() : SquaredDifferenceFixture("[ 2, 2 ]",
+                                                                    "[ 2, 2 ]",
+                                                                    "[ 2, 2 ]") {}
+    };
+
+    TEST_CASE_FIXTURE(SimpleSquaredDifferenceFixture, "SimpleSquaredDifference")
+    {
+        RunTest<2, armnn::DataType::QAsymmU8>(
+            0,
+            {{"inputTensor1", { 4, 1, 8, 9 }},
+            {"inputTensor2", { 0, 5, 6, 3 }}},
+            {{"outputTensor", { 16, 16, 4, 36 }}});
+    }
+
+}
\ No newline at end of file