From 389aa70c8a24fa2faf33df5f8cd9a99b0fabe971 Mon Sep 17 00:00:00 2001
From: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Date: Fri, 21 Jun 2019 15:25:19 +0100
Subject: IVGCVSW-3322 Add Quantizer support for TransposeConvolution2DLayer

Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: I26997d7770585055b2b3256baad2800a4c5ed7e8
---
 src/armnn/QuantizerVisitor.cpp   | 28 +++++++++++++++
 src/armnn/QuantizerVisitor.hpp   |  6 ++++
 src/armnn/test/QuantizerTest.cpp | 77 ++++++++++++++++++++++++++++++++++++++++
 3 files changed, 111 insertions(+)

diff --git a/src/armnn/QuantizerVisitor.cpp b/src/armnn/QuantizerVisitor.cpp
index ef6b068145..292924c8e4 100644
--- a/src/armnn/QuantizerVisitor.cpp
+++ b/src/armnn/QuantizerVisitor.cpp
@@ -446,4 +446,32 @@ void QuantizerVisitor::VisitSubtractionLayer(const IConnectableLayer* layer,
     SetQuantizedInputConnections(layer, newLayer);
 }
 
+void QuantizerVisitor::VisitTransposeConvolution2dLayer(const IConnectableLayer* layer,
+                                                        const TransposeConvolution2dDescriptor& descriptor,
+                                                        const ConstTensor& weights,
+                                                        const Optional<ConstTensor>& biases,
+                                                        const char* name)
+{
+    // quantize weights
+    std::vector<uint8_t> weightsBacking;
+    ConstTensor qWeights = CreateQuantizedConst(weights, weightsBacking);
+
+    // quantize biases
+    std::vector<int32_t> biasesBacking;
+    Optional<ConstTensor> optionalQBiases;
+    if (biases.has_value())
+    {
+        ConstTensor qBiases = CreateQuantizedBias(layer, qWeights, biases, biasesBacking);
+        optionalQBiases = Optional<ConstTensor>(qBiases);
+    }
+
+    IConnectableLayer* newLayer = m_QuantizedNetwork->AddTransposeConvolution2dLayer(descriptor,
+                                                                                     qWeights,
+                                                                                     optionalQBiases,
+                                                                                     name);
+
+    RecordLayer(layer, newLayer);
+    SetQuantizedInputConnections(layer, newLayer);
+}
+
 } //namespace armnn
diff --git a/src/armnn/QuantizerVisitor.hpp b/src/armnn/QuantizerVisitor.hpp
index ca9f6940a6..c3a2eaffcb 100644
--- a/src/armnn/QuantizerVisitor.hpp
+++ b/src/armnn/QuantizerVisitor.hpp
@@ -140,6 +140,12 @@ public:
     void VisitSubtractionLayer(const IConnectableLayer* layer,
                                const char* name = nullptr) override;
 
+    void VisitTransposeConvolution2dLayer(const IConnectableLayer* layer,
+                                          const TransposeConvolution2dDescriptor& descriptor,
+                                          const ConstTensor& weights,
+                                          const Optional<ConstTensor>& biases,
+                                          const char* name = nullptr) override;
+
     /// Extract the quantized network
     INetworkPtr RetrieveFinalNetwork() { return std::move(m_QuantizedNetwork); }
 
diff --git a/src/armnn/test/QuantizerTest.cpp b/src/armnn/test/QuantizerTest.cpp
index 2792d5c483..4732da393f 100644
--- a/src/armnn/test/QuantizerTest.cpp
+++ b/src/armnn/test/QuantizerTest.cpp
@@ -1715,6 +1715,83 @@ BOOST_AUTO_TEST_CASE(QuantizePrelu)
     VisitLayersTopologically(quantizedNetworkQSymm16.get(), validatorQSymm16);
 }
 
+void TestQuantizeTransposeConvolution2d(bool useBiases)
+{
+    class TestTransposeConvolution2dQuantization : public TestQuantization
+    {
+    public:
+        TestTransposeConvolution2dQuantization(const TensorShape& inputShape, const TensorShape& outputShape) :
+            TestQuantization(inputShape, outputShape)
+        {}
+
+        TestTransposeConvolution2dQuantization(const QuantizerOptions& options,
+                                               const TensorShape& inputShape,
+                                               const TensorShape& outputShape) :
+            TestQuantization(options, inputShape, outputShape)
+        {}
+
+        void VisitTransposeConvolution2dLayer(const IConnectableLayer *layer,
+                                              const TransposeConvolution2dDescriptor& descriptor,
+                                              const ConstTensor& weights,
+                                              const Optional<ConstTensor>& biases,
+                                              const char *name = nullptr) override
+        {
+            TestQuantizationOnLayersWithBiases(layer, weights, biases);
+        }
+    };
+
+    INetworkPtr network = INetwork::Create();
+
+    TensorShape shape{ 3 };
+    TensorInfo info(shape, DataType::Float32);
+
+    std::initializer_list<float> floatData{ -1.0f, 1.5f, 2.0f };
+    std::vector<float> weightsData(floatData);
+    ConstTensor weights(info, weightsData);
+
+    TransposeConvolution2dDescriptor descriptor;
+    descriptor.m_BiasEnabled = useBiases;
+
+    // construct network
+    IConnectableLayer* input = network->AddInputLayer(0);
+    Optional<ConstTensor> optionalBiases;
+    std::vector<float> biasesData(floatData);
+    if (useBiases)
+    {
+        ConstTensor biases(info, biasesData);
+        optionalBiases = Optional<ConstTensor>(biases);
+    }
+    IConnectableLayer* transposeConv2d = network->AddTransposeConvolution2dLayer(descriptor, weights, optionalBiases);
+    IConnectableLayer* output = network->AddOutputLayer(1);
+
+    input->GetOutputSlot(0).Connect(transposeConv2d->GetInputSlot(0));
+    transposeConv2d->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+    input->GetOutputSlot(0).SetTensorInfo(info);
+    transposeConv2d->GetOutputSlot(0).SetTensorInfo(info);
+
+    // test QAsymm8 quantization
+    INetworkPtr quantizedNetworkQAsymm8 = INetworkQuantizer::Create(network.get())->ExportNetwork();
+    TestTransposeConvolution2dQuantization validatorQAsymm8(shape, shape);
+    VisitLayersTopologically(quantizedNetworkQAsymm8.get(), validatorQAsymm8);
+
+    // test QSymm16 quantization
+    const QuantizerOptions options(DataType::QuantisedSymm16);
+    INetworkPtr quantizedNetworkQSymm16 = INetworkQuantizer::Create(network.get(), options)->ExportNetwork();
+    TestTransposeConvolution2dQuantization validatorQSymm16(options, shape, shape);
+    VisitLayersTopologically(quantizedNetworkQSymm16.get(), validatorQSymm16);
+}
+
+BOOST_AUTO_TEST_CASE(QuantizeTransposeConvolution2d)
+{
+    TestQuantizeTransposeConvolution2d(false);
+}
+
+BOOST_AUTO_TEST_CASE(QuantizeTransposeConvolution2dWithBiases)
+{
+    TestQuantizeTransposeConvolution2d(true);
+}
+
 std::vector<uint8_t> SetupQuantize(float value)
 {
     armnn::TensorInfo inputInfo({ 1, 2, 2 }, armnn::DataType::Float32);
-- 
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