Added AddBroadcastReshapeLayer method to TfLiteParser

Change-Id: I6027f6dcdb3ed23505f0a9c780bd3e3d45d3daff

1 files changed, 79 insertions, 2 deletions

diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 0e8d3c5b68..c45e794274 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -463,6 +463,63 @@ void TfLiteParser::ResetParser()
     m_SubgraphConnections.clear();
 }
 
+void TfLiteParser::AddBroadcastReshapeLayer(size_t subgraphIndex,
+                                            size_t operatorIndex,
+                                            IConnectableLayer *layer)
+{
+    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+    BOOST_ASSERT(layer != nullptr);
+
+    const auto & subGraphPtr = m_Model->subgraphs[subgraphIndex];
+    const auto & operatorPtr = subGraphPtr->operators[operatorIndex];
+
+    BOOST_ASSERT(operatorPtr->inputs.size() > 1);
+
+    uint32_t reshapedInputId = CHECKED_NON_NEGATIVE(operatorPtr->inputs[0]);
+    TensorRawPtr tensorPtr = subGraphPtr->tensors[reshapedInputId].get();
+    uint32_t inputId = CHECKED_NON_NEGATIVE(operatorPtr->inputs[1]);
+    TensorRawPtr tensorPtr1 = subGraphPtr->tensors[inputId].get();
+
+    armnn::TensorInfo reshapedTensorInfo = ToTensorInfo(tensorPtr);
+    armnn::TensorInfo inputTensorInfo    = ToTensorInfo(tensorPtr1);
+
+    if (inputTensorInfo.GetNumDimensions() < reshapedTensorInfo.GetNumDimensions())
+    {
+        uint32_t id = reshapedInputId;
+        reshapedInputId = inputId;
+        inputId = id;
+
+        reshapedTensorInfo = ToTensorInfo(tensorPtr1);
+        inputTensorInfo = ToTensorInfo(tensorPtr);
+    }
+
+    uint32_t numDimensions = inputTensorInfo.GetNumDimensions();
+
+    std::vector<unsigned> reshapedDim;
+    for (unsigned int i = 0; i < reshapedTensorInfo.GetNumDimensions(); ++i)
+    {
+        reshapedDim.push_back(reshapedTensorInfo.GetShape()[i]);
+    }
+
+    std::vector<unsigned int> reshapedDimensions(numDimensions, 1);
+    std::copy_backward (reshapedDim.begin(), reshapedDim.end(), reshapedDimensions.end());
+
+    reshapedTensorInfo.SetShape(armnn::TensorShape{ numDimensions, reshapedDimensions.data() });
+
+    std::string layerName = boost::str(boost::format("Reshape_for:%1%") % layer->GetName());
+    armnn::ReshapeDescriptor desc;
+    desc.m_TargetShape = reshapedTensorInfo.GetShape();
+    armnn::IConnectableLayer* reshapeLayer = m_Network->AddReshapeLayer(desc, layerName.c_str());
+
+    reshapeLayer->GetOutputSlot(0).SetTensorInfo(reshapedTensorInfo);
+    reshapeLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
+
+    RegisterInputSlots(subgraphIndex, operatorIndex, reshapeLayer, {reshapedInputId});
+
+    armnn::IInputSlot* input1Slot = &(layer->GetInputSlot(1));
+    RegisterConsumerOfTensor(subgraphIndex, inputId, input1Slot);
+}
+
 INetworkPtr TfLiteParser::CreateNetworkFromBinaryFile(const char* graphFile)
 {
     ResetParser();
@@ -1008,6 +1065,9 @@ void TfLiteParser::ParseAdd(size_t subgraphIndex, size_t operatorIndex)
     auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
     CHECK_VALID_SIZE(outputs.size(), 1);
 
+    armnn::TensorInfo inputTensorInfo  = ToTensorInfo(inputs[0]);
+    armnn::TensorInfo input1TensorInfo = ToTensorInfo(inputs[1]);
+
     auto layerName = boost::str(boost::format("Add:%1%:%2%") % subgraphIndex % operatorIndex);
     IConnectableLayer* layer = m_Network->AddAdditionLayer(layerName.c_str());
 
@@ -1015,7 +1075,14 @@ void TfLiteParser::ParseAdd(size_t subgraphIndex, size_t operatorIndex)
     layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
 
     auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
-    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
+    if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
+    {
+        AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
+    }
+    else
+    {
+        RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
+    }
 
     layer = AddFusedActivationLayer(layer, 0, options->fused_activation_function);
 
@@ -1036,6 +1103,9 @@ void TfLiteParser::ParseMul(size_t subgraphIndex, size_t operatorIndex)
     auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
     CHECK_VALID_SIZE(outputs.size(), 1);
 
+    armnn::TensorInfo inputTensorInfo  = ToTensorInfo(inputs[0]);
+    armnn::TensorInfo input1TensorInfo = ToTensorInfo(inputs[1]);
+
     auto layerName = boost::str(boost::format("Mul:%1%:%2%") % subgraphIndex % operatorIndex);
     IConnectableLayer* layer = m_Network->AddMultiplicationLayer(layerName.c_str());
 
@@ -1043,7 +1113,14 @@ void TfLiteParser::ParseMul(size_t subgraphIndex, size_t operatorIndex)
     layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
 
     auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
-    RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
+    if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
+    {
+        AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
+    }
+    else
+    {
+        RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
+    }
 
     layer = AddFusedActivationLayer(layer, 0, options->fused_activation_function);