Added ParseMean method to TfLiteParser
Change-Id: Idfedf82479fb3d4bb2962fc3cfc6c76e57331943
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index e5af76b..e3306b3 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -452,6 +452,7 @@
m_ParserFunctions[tflite::BuiltinOperator_SQUEEZE] = &TfLiteParser::ParseSqueeze;
m_ParserFunctions[tflite::BuiltinOperator_ADD] = &TfLiteParser::ParseAdd;
m_ParserFunctions[tflite::BuiltinOperator_MUL] = &TfLiteParser::ParseMul;
+ m_ParserFunctions[tflite::BuiltinOperator_MEAN] = &TfLiteParser::ParseMean;
}
void TfLiteParser::ResetParser()
@@ -1049,6 +1050,42 @@
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
}
+void TfLiteParser::ParseMean(size_t subgraphIndex, size_t operatorIndex)
+{
+ CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+ auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+
+ auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(outputs.size(), 1);
+
+ armnn::TensorInfo dimTensorInfo = ToTensorInfo(inputs[1]);
+ BufferRawPtr bufferPtr = GetBuffer(m_Model, inputs[1]->buffer);
+
+ armnn::MeanDescriptor desc;
+ std::vector<unsigned int> axis(dimTensorInfo.GetNumElements());
+ ::memcpy(axis.data(), bufferPtr->data.data(), dimTensorInfo.GetNumBytes());
+ desc.m_Axis = axis;
+
+ armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]);
+ armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+
+ desc.m_KeepDims =
+ inputTensorInfo.GetNumDimensions() == outputTensorInfo.GetNumDimensions() ?
+ true : false;
+
+ auto layerName = boost::str(boost::format("Mean:%1%:%2%") % subgraphIndex % operatorIndex);
+ IConnectableLayer* layer = m_Network->AddMeanLayer(desc, layerName.c_str());
+
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
+ RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
+
+ auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex));
+ RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
+}
+
void TfLiteParser::ParseRelu(size_t subgraphIndex, size_t operatorIndex)
{
CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp
index 42e1814..581e012 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -103,6 +103,7 @@
void ParseSqueeze(size_t subgraphIndex, size_t operatorIndex);
void ParseAdd(size_t subgraphIndex, size_t operatorIndex);
void ParseMul(size_t subgraphIndex, size_t operatorIndex);
+ void ParseMean(size_t subgraphIndex, size_t operatorIndex);
void ParsePool(size_t subgraphIndex, size_t operatorIndex, armnn::PoolingAlgorithm algorithm);
diff --git a/src/armnnTfLiteParser/test/Mean.cpp b/src/armnnTfLiteParser/test/Mean.cpp
new file mode 100644
index 0000000..d7cb2a2
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Mean.cpp
@@ -0,0 +1,99 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersFixture.hpp"
+#include "../TfLiteParser.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
+
+struct MeanNoReduceFixture : public ParserFlatbuffersFixture
+{
+ explicit MeanNoReduceFixture(const std::string & inputShape,
+ const std::string & outputShape,
+ const std::string & dimShape,
+ const std::string & dimData)
+ {
+ m_JsonString = R"(
+ {
+ "version": 3,
+ "operator_codes": [ { "builtin_code": "MEAN" } ],
+ "subgraphs": [ {
+ "tensors": [
+ {
+ "shape": )" + inputShape + R"(,
+ "type": "FLOAT32",
+ "buffer": 0,
+ "name": "inputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + outputShape + R"( ,
+ "type": "FLOAT32",
+ "buffer": 1,
+ "name": "outputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + dimShape + R"( ,
+ "type": "INT32",
+ "buffer": 2,
+ "name": "dimShape",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ }
+ ],
+ "inputs": [ 0 ],
+ "outputs": [ 1 ],
+ "operators": [
+ {
+ "opcode_index": 0,
+ "inputs": [ 0 , 2 ],
+ "outputs": [ 1 ],
+ "custom_options_format": "FLEXBUFFERS"
+ }
+ ],
+ } ],
+ "buffers" : [
+ { },
+ { },
+ { "data": )" + dimData + R"(, },
+ ]
+ }
+ )";
+ SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+ }
+};
+
+struct SimpleMeanNoReduceFixture : public MeanNoReduceFixture
+{
+ SimpleMeanNoReduceFixture() : MeanNoReduceFixture("[ 2, 2 ]", "[ 1, 1 ]", "[ 0 ]", "[ ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMeanNoReduce, SimpleMeanNoReduceFixture)
+{
+ RunTest<2, float>(0, {{ "inputTensor", { 1.0f, 1.0f, 2.0f, 2.0f } } },
+ {{ "outputTensor", { 1.5f } } });
+}
+
+BOOST_AUTO_TEST_SUITE_END()
+