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-rw-r--r--src/armnn/test/QuantizerTest.cpp107
1 files changed, 107 insertions, 0 deletions
diff --git a/src/armnn/test/QuantizerTest.cpp b/src/armnn/test/QuantizerTest.cpp
index ba10fd8b79..dd90368524 100644
--- a/src/armnn/test/QuantizerTest.cpp
+++ b/src/armnn/test/QuantizerTest.cpp
@@ -459,5 +459,112 @@ BOOST_AUTO_TEST_CASE(OverrideInputRangeInputLayers)
BOOST_CHECK(guidToRangesMap[input1->GetGuid()].at(0).second == minMaxRange.second);
}
+INetworkPtr CreateNetworkWithFullyConnectedLayer(const bool biasEnabled)
+{
+ FullyConnectedDescriptor desc;
+ desc.m_BiasEnabled = biasEnabled;
+ 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);
+
+ // Add the layers
+ IConnectableLayer* input0 = network->AddInputLayer(0);
+ IConnectableLayer* fullyConnected;
+ if (desc.m_BiasEnabled)
+ {
+ std::vector<float> biasData{10.0f, 20.0f, 30.0f};
+ ConstTensor bias(info, biasData);
+ fullyConnected = network->AddFullyConnectedLayer(desc, weights, bias);
+ }
+ else
+ {
+ fullyConnected = network->AddFullyConnectedLayer(desc, weights);
+ }
+ IConnectableLayer* output = network->AddOutputLayer(1);
+
+ // Establish connections
+ input0->GetOutputSlot(0).Connect(fullyConnected->GetInputSlot(0));
+ fullyConnected->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ //Set TensorInfo
+ input0->GetOutputSlot(0).SetTensorInfo(info);
+ fullyConnected->GetOutputSlot(0).SetTensorInfo(info);
+
+ return network;
+}
+
+class TestFullyConnectedQuantization : public TestQuantization
+{
+public:
+ virtual void VisitFullyConnectedLayer(const IConnectableLayer* layer,
+ const FullyConnectedDescriptor& desc,
+ 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 constants
+ 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 VisitFullyConnectedLayer(const IConnectableLayer* layer,
+ const FullyConnectedDescriptor& desc,
+ const ConstTensor& weights,
+ const ConstTensor& bias,
+ 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 constants
+ BOOST_TEST((weights.GetInfo().GetDataType() == DataType::QuantisedAsymm8));
+ BOOST_TEST((bias.GetInfo().GetDataType() == DataType::QuantisedAsymm8));
+
+ BOOST_CHECK_CLOSE(weights.GetInfo().GetQuantizationScale(), 3.0f/255.0f, 0.000001f);
+ BOOST_CHECK_CLOSE(bias.GetInfo().GetQuantizationScale(), 30.0f/255.0f, 0.000001f);
+
+ BOOST_TEST((weights.GetInfo().GetQuantizationOffset() == 85));
+ }
+};
+
+void ValidateFullyConnectedLayer(const bool biasEnabled)
+{
+ auto network = CreateNetworkWithFullyConnectedLayer(biasEnabled);
+ auto quantizedNetwork = INetworkQuantizer::Create(network.get())->ExportNetwork();
+ TestFullyConnectedQuantization validator;
+ VisitLayersTopologically(quantizedNetwork.get(), validator);
+}
+
+BOOST_AUTO_TEST_CASE(QuantizeFullyConnected)
+{
+ ValidateFullyConnectedLayer(false);
+}
+
+BOOST_AUTO_TEST_CASE(QuantizeFullyConnectedBiasEnabled)
+{
+ ValidateFullyConnectedLayer(true);
+}
+
BOOST_AUTO_TEST_SUITE_END()
} // namespace armnn