Add maximum parser to tf-lite
Change-Id: Idaf6dd3f4d96dad01e1dc1a0d3fd6c146780626d
Signed-off-by: Bruno Goncalves <bruno.slackware@gmail.com>
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 91a0a0a..edf35ab 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -549,6 +549,7 @@
src/armnnTfLiteParser/test/DepthwiseConvolution2D.cpp
src/armnnTfLiteParser/test/DetectionPostProcess.cpp
src/armnnTfLiteParser/test/FullyConnected.cpp
+ src/armnnTfLiteParser/test/Maximum.cpp
src/armnnTfLiteParser/test/MaxPool2D.cpp
src/armnnTfLiteParser/test/Mean.cpp
src/armnnTfLiteParser/test/Multiplication.cpp
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index e19edc3..80b6d99 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -427,6 +427,7 @@
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 @@
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)
diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp
index e074b76..1e09e72 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -100,6 +100,7 @@
void ParseFullyConnected(size_t subgraphIndex, size_t operatorIndex);
void ParseLogistic(size_t subgraphIndex, size_t operatorIndex);
void ParseMaxPool2D(size_t subgraphIndex, size_t operatorIndex);
+ void ParseMaximum(size_t subgraphIndex, size_t operatorIndex);
void ParseRelu(size_t subgraphIndex, size_t operatorIndex);
void ParseRelu6(size_t subgraphIndex, size_t operatorIndex);
void ParseReshape(size_t subgraphIndex, size_t operatorIndex);
diff --git a/src/armnnTfLiteParser/test/Maximum.cpp b/src/armnnTfLiteParser/test/Maximum.cpp
new file mode 100644
index 0000000..56a1ecf
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Maximum.cpp
@@ -0,0 +1,175 @@
+//
+// 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 MaximumFixture : public ParserFlatbuffersFixture
+{
+ explicit MaximumFixture(const std::string & inputShape1,
+ const std::string & inputShape2,
+ const std::string & outputShape)
+ {
+ m_JsonString = R"(
+ {
+ "version": 3,
+ "operator_codes": [ { "builtin_code": "MAXIMUM" } ],
+ "subgraphs": [ {
+ "tensors": [
+ {
+ "shape": )" + inputShape1 + R"(,
+ "type": "FLOAT32",
+ "buffer": 0,
+ "name": "inputTensor1",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + inputShape2 + R"(,
+ "type": "FLOAT32",
+ "buffer": 1,
+ "name": "inputTensor2",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ },
+ {
+ "shape": )" + outputShape + R"( ,
+ "type": "FLOAT32",
+ "buffer": 2,
+ "name": "outputTensor",
+ "quantization": {
+ "min": [ 0.0 ],
+ "max": [ 255.0 ],
+ "scale": [ 1.0 ],
+ "zero_point": [ 0 ],
+ }
+ }
+ ],
+ "inputs": [ 0, 1 ],
+ "outputs": [ 2 ],
+ "operators": [
+ {
+ "opcode_index": 0,
+ "inputs": [ 0, 1 ],
+ "outputs": [ 2 ],
+ "custom_options_format": "FLEXBUFFERS"
+ }
+ ],
+ } ],
+ "buffers" : [
+ { },
+ { }
+ ]
+ }
+ )";
+ Setup();
+ }
+};
+
+
+struct MaximumFixture4D4D : MaximumFixture
+{
+ MaximumFixture4D4D() : MaximumFixture("[ 1, 2, 2, 3 ]",
+ "[ 1, 2, 2, 3 ]",
+ "[ 1, 2, 2, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMaximum4D4D, MaximumFixture4D4D)
+{
+ RunTest<4, armnn::DataType::Float32>(
+ 0,
+ {{"inputTensor1", { 0.0f, 1.0f, 2.0f,
+ 3.0f, 4.0f, 5.0f,
+ 6.0f, 7.0f, 8.0f,
+ 9.0f, 10.0f, 11.0f }},
+ {"inputTensor2", { 5.0f, 1.0f, 3.0f,
+ 4.0f, 5.5f, 1.0f,
+ 2.0f, 17.0f, 18.0f,
+ 19.0f, 1.0f, 3.0f }}},
+ {{"outputTensor", { 5.0f, 1.0f, 3.0f,
+ 4.0f, 5.5f, 5.0f,
+ 6.0f, 17.0f, 18.0f,
+ 19.0f, 10.0f, 11.0f }}});
+}
+
+struct MaximumBroadcastFixture4D4D : MaximumFixture
+{
+ MaximumBroadcastFixture4D4D() : MaximumFixture("[ 1, 1, 2, 1 ]",
+ "[ 1, 2, 1, 3 ]",
+ "[ 1, 2, 2, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMaximumBroadcast4D4D, MaximumBroadcastFixture4D4D)
+{
+ RunTest<4, armnn::DataType::Float32>(
+ 0,
+ {{"inputTensor1", { 2.0f, 4.0f }},
+ {"inputTensor2", { 1.0f, 2.0f, 3.0f,
+ 4.0f, 5.0f, 6.0f }}},
+ {{"outputTensor", { 2.0f, 2.0f, 3.0f,
+ 4.0f, 4.0f, 4.0f,
+ 4.0f, 5.0f, 6.0f,
+ 4.0f, 5.0f, 6.0f }}});
+}
+
+struct MaximumBroadcastFixture4D1D : MaximumFixture
+{
+ MaximumBroadcastFixture4D1D() : MaximumFixture("[ 1, 2, 2, 3 ]",
+ "[ 1 ]",
+ "[ 1, 2, 2, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMaximumBroadcast4D1D, MaximumBroadcastFixture4D1D)
+{
+ RunTest<4, armnn::DataType::Float32>(
+ 0,
+ {{"inputTensor1", { 0.0f, 1.0f, 2.0f,
+ 3.0f, 4.0f, 5.0f,
+ 6.0f, 7.0f, 8.0f,
+ 9.0f, 10.0f, 11.0f }},
+ {"inputTensor2", { 5.0f }}},
+ {{"outputTensor", { 5.0f, 5.0f, 5.0f,
+ 5.0f, 5.0f, 5.0f,
+ 6.0f, 7.0f, 8.0f,
+ 9.0f, 10.0f, 11.0f }}});
+}
+
+struct MaximumBroadcastFixture1D4D : MaximumFixture
+{
+ MaximumBroadcastFixture1D4D() : MaximumFixture("[ 1 ]",
+ "[ 1, 2, 2, 3 ]",
+ "[ 1, 2, 2, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMaximumBroadcast1D4D, MaximumBroadcastFixture1D4D)
+{
+ RunTest<4, armnn::DataType::Float32>(
+ 0,
+ {{"inputTensor1", { 3.0f }},
+ {"inputTensor2", { 0.0f, 1.0f, 2.0f,
+ 3.0f, 4.0f, 5.0f,
+ 6.0f, 7.0f, 8.0f,
+ 9.0f, 10.0f, 11.0f }}},
+ {{"outputTensor", { 3.0f, 3.0f, 3.0f,
+ 3.0f, 4.0f, 5.0f,
+ 6.0f, 7.0f, 8.0f,
+ 9.0f, 10.0f, 11.0f }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()