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Diffstat (limited to 'src/armnn/test/QuantizerTest.cpp')
-rw-r--r-- | src/armnn/test/QuantizerTest.cpp | 83 |
1 files changed, 83 insertions, 0 deletions
diff --git a/src/armnn/test/QuantizerTest.cpp b/src/armnn/test/QuantizerTest.cpp index 56b1497967..fbafbd8f1e 100644 --- a/src/armnn/test/QuantizerTest.cpp +++ b/src/armnn/test/QuantizerTest.cpp @@ -92,5 +92,88 @@ BOOST_AUTO_TEST_CASE(QuantizeAddition) VisitLayersTopologically(quantizedNetwork.get(), validator); } +BOOST_AUTO_TEST_CASE(QuantizeBatchNorm) +{ + + class TestQuantization : public LayerVisitorBase<VisitorThrowingPolicy> + { + public: + virtual void VisitBatchNormalizationLayer(const IConnectableLayer* layer, + const BatchNormalizationDescriptor& desc, + const ConstTensor& mean, + const ConstTensor& variance, + const ConstTensor& beta, + const ConstTensor& gamma, + 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((mean.GetInfo().GetDataType() == DataType::QuantisedAsymm8)); + BOOST_TEST((variance.GetInfo().GetDataType() == DataType::QuantisedAsymm8)); + BOOST_TEST((beta.GetInfo().GetDataType() == DataType::QuantisedAsymm8)); + BOOST_TEST((gamma.GetInfo().GetDataType() == DataType::QuantisedAsymm8)); + + BOOST_CHECK_CLOSE(mean.GetInfo().GetQuantizationScale(), 3.0f/255.0f, 0.000001f); + BOOST_CHECK_CLOSE(variance.GetInfo().GetQuantizationScale(), 3.0f/255.0f, 0.000001f); + BOOST_CHECK_CLOSE(beta.GetInfo().GetQuantizationScale(), 3.0f/255.0f, 0.000001f); + BOOST_CHECK_CLOSE(gamma.GetInfo().GetQuantizationScale(), 3.0f/255.0f, 0.000001f); + + BOOST_TEST((mean.GetInfo().GetQuantizationOffset() == 85)); + } + + virtual void VisitInputLayer(const IConnectableLayer* layer, + LayerBindingId id, + const char* name = nullptr) + {} + + virtual void VisitOutputLayer(const IConnectableLayer* layer, + LayerBindingId id, + const char* name = nullptr) + {} + }; + + auto network = INetwork::Create(); + + TensorShape shape{3U}; + TensorInfo info(shape, DataType::Float32); + + std::vector<float> meanData{-1.0f, 1.5f, 2.0f}; + std::vector<float> varData{-1.0f, 1.5f, 2.0f}; + std::vector<float> betaData{-1.0f, 1.5f, 2.0f}; + std::vector<float> gammaData{-1.0f, 1.5f, 2.0f}; + + ConstTensor mean(info, meanData); + ConstTensor var(info, varData); + ConstTensor beta(info, betaData); + ConstTensor gamma(info, gammaData); + + BatchNormalizationDescriptor desc; + + // Add the layers + IConnectableLayer* input0 = network->AddInputLayer(0); + IConnectableLayer* batchNorm = network->AddBatchNormalizationLayer(desc, mean, var, beta, gamma); + IConnectableLayer* output = network->AddOutputLayer(1); + + // Establish connections + input0->GetOutputSlot(0).Connect(batchNorm->GetInputSlot(0)); + batchNorm->GetOutputSlot(0).Connect(output->GetInputSlot(0)); + + //Set TensorInfo + input0->GetOutputSlot(0).SetTensorInfo(info); + batchNorm->GetOutputSlot(0).SetTensorInfo(info); + + auto quantizedNetwork = INetworkQuantizer::Create(network.get())->ExportNetwork(); + TestQuantization validator; + VisitLayersTopologically(quantizedNetwork.get(), validator); +} + BOOST_AUTO_TEST_SUITE_END() } //namespace armnn |