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author | Bruno Goncalves <bruno.slackware@gmail.com> | 2019-02-12 22:57:13 -0200 |
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committer | derek.lamberti <derek.lamberti@arm.com> | 2019-02-25 11:47:00 +0000 |
commit | b8d805ea3f4db36c316fc40e671e3317d1ef5a0f (patch) | |
tree | d32d2c927f210fc5560c4f77a1fef1c7bac02c13 /src/armnnTfLiteParser/TfLiteParser.cpp | |
parent | 0d0a78ebd60e058746ea161914b45709245d4e1b (diff) | |
download | armnn-b8d805ea3f4db36c316fc40e671e3317d1ef5a0f.tar.gz |
Add maximum parser to tf-lite
Change-Id: Idaf6dd3f4d96dad01e1dc1a0d3fd6c146780626d
Signed-off-by: Bruno Goncalves <bruno.slackware@gmail.com>
Diffstat (limited to 'src/armnnTfLiteParser/TfLiteParser.cpp')
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 34 |
1 files changed, 34 insertions, 0 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index e19edc3821..80b6d99920 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -427,6 +427,7 @@ TfLiteParser::TfLiteParser() m_ParserFunctions[tflite::BuiltinOperator_FULLY_CONNECTED] = &TfLiteParser::ParseFullyConnected; 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_RELU] = &TfLiteParser::ParseRelu; m_ParserFunctions[tflite::BuiltinOperator_RELU6] = &TfLiteParser::ParseRelu6; m_ParserFunctions[tflite::BuiltinOperator_RESHAPE] = &TfLiteParser::ParseReshape; @@ -891,6 +892,39 @@ void TfLiteParser::ParseMaxPool2D(size_t subgraphIndex, size_t operatorIndex) ParsePool(subgraphIndex, operatorIndex, PoolingAlgorithm::Max); } +void TfLiteParser::ParseMaximum(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("Maximum:%1%:%2%") % subgraphIndex % operatorIndex); + IConnectableLayer* layer = m_Network->AddMaximumLayer(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) |