diff options
Diffstat (limited to 'src/armnnDeserializer/Deserializer.cpp')
| -rw-r--r-- | src/armnnDeserializer/Deserializer.cpp | 95 |
1 files changed, 95 insertions, 0 deletions
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp index 076b23e5a4..c7049f6a15 100644 --- a/src/armnnDeserializer/Deserializer.cpp +++ b/src/armnnDeserializer/Deserializer.cpp @@ -197,6 +197,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer) m_ParserFunctions[Layer_MinimumLayer] = &Deserializer::ParseMinimum; m_ParserFunctions[Layer_MaximumLayer] = &Deserializer::ParseMaximum; m_ParserFunctions[Layer_MultiplicationLayer] = &Deserializer::ParseMultiplication; + m_ParserFunctions[Layer_NormalizationLayer] = &Deserializer::ParseNormalization; m_ParserFunctions[Layer_PermuteLayer] = &Deserializer::ParsePermute; m_ParserFunctions[Layer_Pooling2dLayer] = &Deserializer::ParsePooling2d; m_ParserFunctions[Layer_ReshapeLayer] = &Deserializer::ParseReshape; @@ -236,6 +237,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt return graphPtr->layers()->Get(layerIndex)->layer_as_MaximumLayer()->base(); case Layer::Layer_MultiplicationLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_MultiplicationLayer()->base(); + case Layer::Layer_NormalizationLayer: + return graphPtr->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->base(); case Layer::Layer_OutputLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base(); case Layer::Layer_PermuteLayer: @@ -1360,4 +1363,96 @@ void Deserializer::ParseSpaceToBatchNd(GraphPtr graph, unsigned int layerIndex) RegisterOutputSlots(graph, layerIndex, layer); } +armnn::NormalizationDescriptor Deserializer::GetNormalizationDescriptor( + Deserializer::NormalizationDescriptorPtr normalizationDescriptor, + unsigned int layerIndex) +{ + armnn::NormalizationDescriptor desc; + + switch (normalizationDescriptor->normChannelType()) + { + case NormalizationAlgorithmChannel_Across: + { + desc.m_NormChannelType = armnn::NormalizationAlgorithmChannel::Across; + break; + } + case NormalizationAlgorithmChannel_Within: + { + desc.m_NormChannelType = armnn::NormalizationAlgorithmChannel::Within; + break; + } + default: + { + BOOST_ASSERT_MSG(false, "Unsupported normalization channel type"); + } + } + + switch (normalizationDescriptor->normMethodType()) + { + case NormalizationAlgorithmMethod_LocalBrightness: + { + desc.m_NormMethodType = armnn::NormalizationAlgorithmMethod::LocalBrightness; + break; + } + case NormalizationAlgorithmMethod_LocalContrast: + { + desc.m_NormMethodType = armnn::NormalizationAlgorithmMethod::LocalContrast; + break; + } + default: + { + BOOST_ASSERT_MSG(false, "Unsupported normalization method type"); + } + } + + switch (normalizationDescriptor->dataLayout()) + { + case DataLayout_NCHW: + { + desc.m_DataLayout = armnn::DataLayout::NCHW; + break; + } + case DataLayout_NHWC: + { + desc.m_DataLayout = armnn::DataLayout::NHWC; + break; + } + default: + { + BOOST_ASSERT_MSG(false, "Unsupported data layout"); + } + } + + desc.m_Alpha = normalizationDescriptor->alpha(); + desc.m_Beta = normalizationDescriptor->beta(); + desc.m_K = normalizationDescriptor->k(); + desc.m_NormSize = normalizationDescriptor->normSize(); + + return desc; +} + +void Deserializer::ParseNormalization(GraphPtr graph, unsigned int layerIndex) +{ + CHECK_LAYERS(graph, 0, layerIndex); + + auto normalizationDes = graph->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->descriptor(); + + Deserializer::TensorRawPtrVector inputs = GetInputs(graph, layerIndex); + CHECK_VALID_SIZE(inputs.size(), 1); + + Deserializer::TensorRawPtrVector outputs = GetOutputs(graph, layerIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + auto outputInfo = ToTensorInfo(outputs[0]); + + auto normalizationDescriptor = GetNormalizationDescriptor(normalizationDes, layerIndex); + auto layerName = GetLayerName(graph, layerIndex); + + IConnectableLayer* layer = m_Network->AddNormalizationLayer(normalizationDescriptor, layerName.c_str()); + layer->GetOutputSlot(0).SetTensorInfo(outputInfo); + + RegisterInputSlots(graph, layerIndex, layer); + RegisterOutputSlots(graph, layerIndex, layer); +} + } // namespace armnnDeserializer |