Add minimum parser to tf-lite

Change-Id: I617c2715e0fb8d01b96fa9d3d5d9a16a33477b66
Signed-off-by: Bruno Goncalves <bruno.slackware@gmail.com>

1 files changed, 34 insertions, 0 deletions

diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 80b6d99920..521c5db299 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -428,6 +428,7 @@ TfLiteParser::TfLiteParser()
     m_ParserFunctions[tflite::BuiltinOperator_LOGISTIC]          =  &TfLiteParser::ParseLogistic;
     m_ParserFunctions[tflite::BuiltinOperator_MAX_POOL_2D]       =  &TfLiteParser::ParseMaxPool2D;
     m_ParserFunctions[tflite::BuiltinOperator_MAXIMUM]           =  &TfLiteParser::ParseMaximum;
+    m_ParserFunctions[tflite::BuiltinOperator_MINIMUM]           =  &TfLiteParser::ParseMinimum;
     m_ParserFunctions[tflite::BuiltinOperator_RELU]              =  &TfLiteParser::ParseRelu;
     m_ParserFunctions[tflite::BuiltinOperator_RELU6]             =  &TfLiteParser::ParseRelu6;
     m_ParserFunctions[tflite::BuiltinOperator_RESHAPE]           =  &TfLiteParser::ParseReshape;
@@ -925,6 +926,39 @@ void TfLiteParser::ParseMaximum(size_t subgraphIndex, size_t operatorIndex)
     RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
 }
 
+void TfLiteParser::ParseMinimum(size_t subgraphIndex, size_t operatorIndex)
+{
+    CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+    auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+    CHECK_VALID_SIZE(inputs.size(), 2);
+
+    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("Minimum:%1%:%2%") % subgraphIndex % operatorIndex);
+    IConnectableLayer* layer = m_Network->AddMinimumLayer(layerName.c_str());
+
+    TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    if (inputTensorInfo.GetNumDimensions() != input1TensorInfo.GetNumDimensions())
+    {
+        AddBroadcastReshapeLayer(subgraphIndex, operatorIndex, layer);
+    }
+    else
+    {
+        RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0], inputTensorIndexes[1]});
+    }
+
+    auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+    RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
+}
+
 void TfLiteParser::ParsePool(size_t subgraphIndex,
                              size_t operatorIndex,
                              PoolingAlgorithm algorithm)