1 files changed, 87 insertions, 0 deletions
diff --git a/src/armnn/test/QuantizerTest.cpp b/src/armnn/test/QuantizerTest.cpp
index dd90368524..a960c6b772 100644
--- a/src/armnn/test/QuantizerTest.cpp
+++ b/src/armnn/test/QuantizerTest.cpp
@@ -566,5 +566,92 @@ BOOST_AUTO_TEST_CASE(QuantizeFullyConnectedBiasEnabled)
     ValidateFullyConnectedLayer(true);
 }
 
+class TestConv2dQuantization : public TestQuantization
+{
+public:
+    virtual void VisitConvolution2dLayer(const IConnectableLayer *layer,
+                                         const Convolution2dDescriptor &convolution2dDescriptor,
+                                         const ConstTensor &weights,
+                                         const char *name = nullptr)
+    {
+        TensorInfo info = layer->GetOutputSlot(0).GetTensorInfo();
+        BOOST_TEST((info.GetDataType() == DataType::QuantisedAsymm8));
+        BOOST_TEST((info.GetQuantizationOffset() == 128));
+
+        // Based off current static value [-15.0f, 15.0f]
+        BOOST_CHECK_CLOSE(info.GetQuantizationScale(), 30.0f / 255.0f, 0.000001f);
+
+        // test weights const
+        BOOST_TEST((weights.GetInfo().GetDataType() == DataType::QuantisedAsymm8));
+        BOOST_CHECK_CLOSE(weights.GetInfo().GetQuantizationScale(), 3.0f / 255.0f, 0.000001f);
+        BOOST_TEST((weights.GetInfo().GetQuantizationOffset() == 85));
+    }
+
+    virtual void VisitConvolution2dLayer(const IConnectableLayer *layer,
+                                         const Convolution2dDescriptor &convolution2dDescriptor,
+                                         const ConstTensor &weights,
+                                         const ConstTensor &biases,
+                                         const char *name = nullptr)
+    {
+        VisitConvolution2dLayer(layer, convolution2dDescriptor, weights, name);
+
+        // test biases const
+        BOOST_TEST((biases.GetInfo().GetDataType() == DataType::QuantisedAsymm8));
+        BOOST_CHECK_CLOSE(biases.GetInfo().GetQuantizationScale(), 3.0f / 255.0f, 0.000001f);
+        BOOST_TEST((biases.GetInfo().GetQuantizationOffset() == 85));
+    }
+};
+
+void TestQuantizeConvolution2d(bool useBiases)
+{
+    auto network = INetwork::Create();
+
+    TensorShape shape{3U};
+    TensorInfo info(shape, DataType::Float32);
+
+    std::vector<float> weightsData{-1.0f, 1.5f, 2.0f};
+    ConstTensor weights(info, weightsData);
+
+    Convolution2dDescriptor descriptor;
+    descriptor.m_BiasEnabled = useBiases;
+
+    // Add the layers
+    IConnectableLayer* input0 = network->AddInputLayer(0);
+    IConnectableLayer* conv2d;
+    if (useBiases)
+    {
+        std::vector<float> biasesData{-1.0f, 1.5f, 2.0f};
+        ConstTensor biases(info, biasesData);
+        conv2d = network->AddConvolution2dLayer(descriptor, weights, biases);
+    }
+    else
+    {
+        conv2d = network->AddConvolution2dLayer(descriptor, weights);
+    }
+    IConnectableLayer* output = network->AddOutputLayer(1);
+
+    // Establish connections
+    input0->GetOutputSlot(0).Connect(conv2d->GetInputSlot(0));
+    conv2d->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+    //Set TensorInfo
+    input0->GetOutputSlot(0).SetTensorInfo(info);
+    conv2d->GetOutputSlot(0).SetTensorInfo(info);
+
+    auto quantizedNetwork = INetworkQuantizer::Create(network.get())->ExportNetwork();
+    TestConv2dQuantization validator;
+    VisitLayersTopologically(quantizedNetwork.get(), validator);
+}
+
+BOOST_AUTO_TEST_CASE(QuantizeConvolution2d)
+{
+    TestQuantizeConvolution2d(false);
+}
+
+BOOST_AUTO_TEST_CASE(QuantizeConvolution2dWithBiases)
+{
+    TestQuantizeConvolution2d(true);
+}
+
 BOOST_AUTO_TEST_SUITE_END()
 } // namespace armnn