IVGCVSW-1650 Add Support for Reshape layer on TF Lite parser

 * Added Reshape operator support for the TfLite Parser.

Change-Id: I64a5650dac089905a402be4a9cb6032aa0d81f00

4 files changed, 209 insertions, 1 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index e4ed9b4515..429046142f 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -728,6 +728,7 @@ if(BUILD_UNIT_TESTS)
              src/armnnTfLiteParser/test/GetSubgraphInputsOutputs.cpp
              src/armnnTfLiteParser/test/GetInputsOutputs.cpp
              src/armnnTfLiteParser/test/Activations.cpp
+             src/armnnTfLiteParser/test/Reshape.cpp
              )
     endif()
 
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index dd1f5773af..13e4604490 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -24,6 +24,7 @@
 #include <fstream>
 #include <algorithm>
 #include <limits>
+#include <numeric>
 
 using namespace armnn;
 using armnn::CheckLocation;
@@ -457,6 +458,7 @@ TfLiteParser::TfLiteParser()
     m_ParserFunctions[tflite::BuiltinOperator_SQUEEZE]           =  &TfLiteParser::ParseSqueeze;
     m_ParserFunctions[tflite::BuiltinOperator_RELU]              =  &TfLiteParser::ParseRelu;
     m_ParserFunctions[tflite::BuiltinOperator_RELU6]             =  &TfLiteParser::ParseRelu6;
+    m_ParserFunctions[tflite::BuiltinOperator_RESHAPE]           =  &TfLiteParser::ParseReshape;
 }
 
 void TfLiteParser::ResetParser()
@@ -1033,6 +1035,68 @@ void TfLiteParser::ParseRelu6(size_t subgraphIndex, size_t operatorIndex)
     RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
 }
 
+armnn::TensorInfo TfLiteParser::OutputShapeOfReshape(const armnn::TensorInfo & inputTensorInfo,
+                                                     const std::vector<int32_t> & targetDimsIn)
+{
+    std::vector<unsigned int> outputDims(targetDimsIn.begin(), targetDimsIn.end());
+    const auto stretchDim = std::find(targetDimsIn.begin(), targetDimsIn.end(), -1);
+
+    if (stretchDim != targetDimsIn.end())
+    {
+        if (std::find(std::next(stretchDim), targetDimsIn.end(), -1) != targetDimsIn.end())
+        {
+            throw ParseException(
+                boost::str(
+                    boost::format("At most one component of shape can be -1 %1%") % CHECK_LOCATION().AsString()));
+        }
+
+        auto targetNumElements =
+            boost::numeric_cast<unsigned int>(
+                std::accumulate(targetDimsIn.begin(), targetDimsIn.end(), -1, std::multiplies<int32_t>()));
+
+        auto stretchIndex = static_cast<size_t>(std::distance(targetDimsIn.begin(), stretchDim));
+        outputDims[stretchIndex] = inputTensorInfo.GetNumElements() / targetNumElements;
+    }
+
+    TensorShape outputShape = TensorShape(static_cast<unsigned int>(outputDims.size()), outputDims.data());
+
+    TensorInfo reshapeInfo = inputTensorInfo;
+    reshapeInfo.SetShape(outputShape);
+
+    return reshapeInfo;
+}
+
+void TfLiteParser::ParseReshape(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);
+
+    const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex];
+    const auto * options = operatorPtr->builtin_options.AsReshapeOptions();
+
+    armnn::TensorInfo inputTensorInfo  = ToTensorInfo(inputs[0]);
+    armnn::TensorInfo outputTensorInfo =
+        TfLiteParser::OutputShapeOfReshape(inputTensorInfo, options->new_shape);
+
+    ReshapeDescriptor reshapeDesc;
+    reshapeDesc.m_TargetShape = outputTensorInfo.GetShape();
+
+    auto layerName = boost::str(boost::format("Reshape:%1%:%2%") % subgraphIndex % operatorIndex);
+    IConnectableLayer* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str());
+    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[0]});
+}
+
 armnn::IConnectableLayer* TfLiteParser::AddFusedActivationLayer(armnn::IConnectableLayer* prevLayer,
                                                                 unsigned int outputSlot,
                                                                 tflite::ActivationFunctionType activationType)
diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp
index b9f81e4118..f949484a4f 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -74,7 +74,8 @@ public:
     static BufferRawPtr GetBuffer(const ModelPtr& model, size_t bufferIndex);
     static armnn::TensorInfo OutputShapeOfSqueeze(const std::vector<uint32_t> & squeezeDims,
                                                   const armnn::TensorInfo & inputTensorInfo);
-
+    static armnn::TensorInfo OutputShapeOfReshape(const armnn::TensorInfo & inputTensorInfo,
+                                                  const std::vector<int32_t> & targetDimsIn);
 
 private:
     // No copying allowed until it is wanted and properly implemented
@@ -95,6 +96,7 @@ private:
     void ParseSqueeze(size_t subgraphIndex, size_t operatorIndex);
     void ParseRelu(size_t subgraphIndex, size_t operatorIndex);
     void ParseRelu6(size_t subgraphIndex, size_t operatorIndex);
+    void ParseReshape(size_t subgraphIndex, size_t operatorIndex);
 
     void RegisterProducerOfTensor(size_t subgraphIndex, size_t tensorIndex, armnn::IOutputSlot* slot);
     void RegisterConsumerOfTensor(size_t subgraphIndex, size_t tensorIndex, armnn::IInputSlot* slot);
diff --git a/src/armnnTfLiteParser/test/Reshape.cpp b/src/armnnTfLiteParser/test/Reshape.cpp
new file mode 100644
index 0000000000..ae5a09a711
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Reshape.cpp
@@ -0,0 +1,141 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersFixture.hpp"
+#include "../TfLiteParser.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
+
+struct ReshapeFixture : public ParserFlatbuffersFixture
+{
+    explicit ReshapeFixture(const std::string& inputShape,
+                            const std::string& outputShape,
+                            const std::string& newShape)
+    {
+        m_JsonString = R"(
+            {
+                "version": 3,
+                "operator_codes": [ { "builtin_code": "RESHAPE" } ],
+                "subgraphs": [ {
+                    "tensors": [
+                        {)";
+        m_JsonString += R"(
+                            "shape" : )" + inputShape + ",";
+        m_JsonString += R"(
+                            "type": "UINT8",
+                            "buffer": 0,
+                            "name": "inputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {)";
+        m_JsonString += R"(
+                            "shape" : )" + outputShape;
+        m_JsonString += R"(,
+                            "type": "UINT8",
+                            "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 ],
+                            "builtin_options_type": "ReshapeOptions",
+                            "builtin_options": {)";
+        if (!newShape.empty())
+        {
+            m_JsonString += R"("new_shape" : )" + newShape;
+        }
+        m_JsonString += R"(},
+                            "custom_options_format": "FLEXBUFFERS"
+                        }
+                    ],
+                } ],
+                "buffers" : [ {}, {} ]
+            }
+        )";
+
+    }
+};
+
+struct ReshapeFixtureWithReshapeDims : ReshapeFixture
+{
+    ReshapeFixtureWithReshapeDims() : ReshapeFixture("[ 1, 9 ]", "[ 3, 3 ]", "[ 3, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseReshapeWithReshapeDims, ReshapeFixtureWithReshapeDims)
+{
+    SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+    RunTest<2, uint8_t>(0,
+                        { 1, 2, 3, 4, 5, 6, 7, 8, 9 },
+                        { 1, 2, 3, 4, 5, 6, 7, 8, 9 });
+    BOOST_TEST((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape()
+                == armnn::TensorShape({3,3})));
+}
+
+struct ReshapeFixtureWithReshapeDimsFlatten : ReshapeFixture
+{
+    ReshapeFixtureWithReshapeDimsFlatten() : ReshapeFixture("[ 3, 3 ]", "[ 1, 9 ]", "[ -1 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseReshapeWithReshapeDimsFlatten, ReshapeFixtureWithReshapeDimsFlatten)
+{
+    SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+    RunTest<2, uint8_t>(0,
+                        { 1, 2, 3, 4, 5, 6, 7, 8, 9 },
+                        { 1, 2, 3, 4, 5, 6, 7, 8, 9 });
+    BOOST_TEST((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape()
+                == armnn::TensorShape({1,9})));
+}
+
+struct ReshapeFixtureWithReshapeDimsFlattenTwoDims : ReshapeFixture
+{
+    ReshapeFixtureWithReshapeDimsFlattenTwoDims() : ReshapeFixture("[ 3, 2, 3 ]", "[ 2, 9 ]", "[ 2, -1 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseReshapeWithReshapeDimsFlattenTwoDims, ReshapeFixtureWithReshapeDimsFlattenTwoDims)
+{
+    SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+    RunTest<2, uint8_t>(0,
+                        { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 },
+                        { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 });
+    BOOST_TEST((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape()
+                == armnn::TensorShape({2,9})));
+}
+
+struct ReshapeFixtureWithReshapeDimsFlattenOneDim : ReshapeFixture
+{
+    ReshapeFixtureWithReshapeDimsFlattenOneDim() : ReshapeFixture("[ 2, 9 ]", "[ 2, 3, 3 ]", "[ 2, -1, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseReshapeWithReshapeDimsFlattenOneDim, ReshapeFixtureWithReshapeDimsFlattenOneDim)
+{
+    SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+    RunTest<3, uint8_t>(0,
+                        { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 },
+                        { 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6 });
+    BOOST_TEST((m_Parser->GetNetworkOutputBindingInfo(0, "outputTensor").second.GetShape()
+                == armnn::TensorShape({2,3,3})));
+}
+
+BOOST_AUTO_TEST_SUITE_END()