diff options
Diffstat (limited to 'src/armnnOnnxParser/OnnxParser.cpp')
-rw-r--r-- | src/armnnOnnxParser/OnnxParser.cpp | 35 |
1 files changed, 18 insertions, 17 deletions
diff --git a/src/armnnOnnxParser/OnnxParser.cpp b/src/armnnOnnxParser/OnnxParser.cpp index e4259980ca..455bd873af 100644 --- a/src/armnnOnnxParser/OnnxParser.cpp +++ b/src/armnnOnnxParser/OnnxParser.cpp @@ -5,6 +5,7 @@ #include "OnnxParser.hpp" #include <armnn/Descriptors.hpp> +#include <armnn/utility/Assert.hpp> #include <VerificationHelpers.hpp> #include <boost/format.hpp> @@ -388,7 +389,7 @@ std::vector<TensorInfo> OnnxParser::ComputeOutputInfo(std::vector<std::string> o const IConnectableLayer* layer, std::vector<TensorShape> inputShapes) { - BOOST_ASSERT(! outNames.empty()); + ARMNN_ASSERT(! outNames.empty()); bool needCompute = std::any_of(outNames.begin(), outNames.end(), [this](std::string name) @@ -401,7 +402,7 @@ std::vector<TensorInfo> OnnxParser::ComputeOutputInfo(std::vector<std::string> o if(needCompute) { inferredShapes = layer->InferOutputShapes(inputShapes); - BOOST_ASSERT(inferredShapes.size() == outNames.size()); + ARMNN_ASSERT(inferredShapes.size() == outNames.size()); } for (uint i = 0; i < outNames.size(); ++i) { @@ -607,7 +608,7 @@ INetworkPtr OnnxParser::CreateNetworkFromModel(onnx::ModelProto& model) void OnnxParser::LoadGraph() { - BOOST_ASSERT(m_Graph.get() != nullptr); + ARMNN_ASSERT(m_Graph.get() != nullptr); //Fill m_TensorsInfo with the shapes and value of every tensor SetupInfo(m_Graph->mutable_output()); @@ -851,7 +852,7 @@ void OnnxParser::AddFullyConnected(const onnx::NodeProto& matmulNode, const onnx CreateConstTensor(weightName).first, Optional<ConstTensor>(CreateConstTensor(biasName).first), matmulNode.name().c_str()); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({addNode->output(0)}, layer, {m_TensorsInfo[inputName].m_info->GetShape(), @@ -868,7 +869,7 @@ void OnnxParser::AddFullyConnected(const onnx::NodeProto& matmulNode, const onnx CreateConstTensor(weightName).first, EmptyOptional(), matmulNode.name().c_str()); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({matmulNode.output(0)}, layer, {m_TensorsInfo[inputName].m_info->GetShape(), @@ -932,7 +933,7 @@ void OnnxParser::ParseGlobalAveragePool(const onnx::NodeProto& node) desc.m_PoolHeight = inputShape[2]; IConnectableLayer* layer = m_Network->AddPooling2dLayer(desc, node.name().c_str()); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({node.output(0)}, layer, {inputShape}); layer->GetOutputSlot(0).SetTensorInfo(outputInfo[0]); @@ -1026,7 +1027,7 @@ void OnnxParser::AddPoolingLayer(const onnx::NodeProto& node, Pooling2dDescripto } IConnectableLayer* layer = m_Network->AddPooling2dLayer(desc, node.name().c_str()); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({node.output(0)}, layer, {m_TensorsInfo[node.input(0)].m_info->GetShape()}); layer->GetOutputSlot(0).SetTensorInfo(outputInfo[0]); @@ -1048,7 +1049,7 @@ void OnnxParser::CreateReshapeLayer(const std::string& inputName, reshapeDesc.m_TargetShape = outputTensorInfo.GetShape(); IConnectableLayer* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str()); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); // register the input connection slots for the layer, connections are made after all layers have been created @@ -1121,7 +1122,7 @@ void OnnxParser::ParseActivation(const onnx::NodeProto& node, const armnn::Activ } IConnectableLayer* const layer = m_Network->AddActivationLayer(desc, node.name().c_str()); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({ node.output(0)}, layer, {m_TensorsInfo[node.input(0)].m_info->GetShape()}); layer->GetOutputSlot(0).SetTensorInfo(outputInfo[0]); @@ -1161,7 +1162,7 @@ void OnnxParser::ParseLeakyRelu(const onnx::NodeProto& node) void OnnxParser::AddConvLayerWithDepthwiseConv(const onnx::NodeProto& node, const Convolution2dDescriptor& convDesc) { - BOOST_ASSERT(node.op_type() == "Conv"); + ARMNN_ASSERT(node.op_type() == "Conv"); DepthwiseConvolution2dDescriptor desc; desc.m_PadLeft = convDesc.m_PadLeft; @@ -1203,7 +1204,7 @@ void OnnxParser::AddConvLayerWithDepthwiseConv(const onnx::NodeProto& node, cons EmptyOptional(), node.name().c_str()); } - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({ node.output(0) }, layer, { m_TensorsInfo[node.input(0)].m_info->GetShape(), @@ -1403,7 +1404,7 @@ void OnnxParser::ParseConv(const onnx::NodeProto& node) EmptyOptional(), node.name().c_str()); } - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({ node.output(0) }, layer, { m_TensorsInfo[node.input(0)].m_info->GetShape(), @@ -1494,7 +1495,7 @@ void OnnxParser::ParseAdd(const onnx::NodeProto& node) auto inputs = AddPrepareBroadcast(node.input(0), node.input(1)); auto input0 = *m_TensorsInfo[inputs.first].m_info; auto input1 = *m_TensorsInfo[inputs.second].m_info; - BOOST_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions()); + ARMNN_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions()); unsigned int numDims = input0.GetNumDimensions(); for (unsigned int i = 0; i < numDims; i++) @@ -1518,7 +1519,7 @@ void OnnxParser::ParseAdd(const onnx::NodeProto& node) IConnectableLayer* layer = m_Network->AddAdditionLayer(node.name().c_str()); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({ node.output(0) }, layer, { m_TensorsInfo[inputs.first].m_info->GetShape(), @@ -1574,7 +1575,7 @@ void OnnxParser::ParseBatchNormalization(const onnx::NodeProto& node) biasTensor.first, scaleTensor.first, node.name().c_str()); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); auto outputInfo = ComputeOutputInfo({node.output(0)}, layer, {m_TensorsInfo[node.input(0)].m_info->GetShape()}); layer->GetOutputSlot(0).SetTensorInfo(outputInfo[0]); @@ -1623,7 +1624,7 @@ void OnnxParser::SetupOutputLayers() void OnnxParser::RegisterInputSlots(IConnectableLayer* layer, const std::vector<std::string>& tensorIds) { - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); if (tensorIds.size() != layer->GetNumInputSlots()) { throw ParseException( @@ -1650,7 +1651,7 @@ void OnnxParser::RegisterInputSlots(IConnectableLayer* layer, const std::vector< void OnnxParser::RegisterOutputSlots(IConnectableLayer* layer, const std::vector<std::string>& tensorIds) { - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); if (tensorIds.size() != layer->GetNumOutputSlots()) { throw ParseException( |