Add minimum parser to tf-lite
Change-Id: I617c2715e0fb8d01b96fa9d3d5d9a16a33477b66
Signed-off-by: Bruno Goncalves <bruno.slackware@gmail.com>
diff --git a/CMakeLists.txt b/CMakeLists.txt
index edf35ab..4cdce75 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -552,6 +552,7 @@
src/armnnTfLiteParser/test/Maximum.cpp
src/armnnTfLiteParser/test/MaxPool2D.cpp
src/armnnTfLiteParser/test/Mean.cpp
+ src/armnnTfLiteParser/test/Minimum.cpp
src/armnnTfLiteParser/test/Multiplication.cpp
src/armnnTfLiteParser/test/Pad.cpp
src/armnnTfLiteParser/test/Reshape.cpp
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 80b6d99..521c5db 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -428,6 +428,7 @@
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 @@
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)
diff --git a/src/armnnTfLiteParser/TfLiteParser.hpp b/src/armnnTfLiteParser/TfLiteParser.hpp
index 1e09e72..6940376 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -101,6 +101,7 @@
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 ParseMinimum(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/Minimum.cpp b/src/armnnTfLiteParser/test/Minimum.cpp
new file mode 100644
index 0000000..70b249f
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Minimum.cpp
@@ -0,0 +1,176 @@
+//
+// 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 MinimumFixture : public ParserFlatbuffersFixture
+{
+ explicit MinimumFixture(const std::string & inputShape1,
+ const std::string & inputShape2,
+ const std::string & outputShape)
+ {
+ m_JsonString = R"(
+ {
+ "version": 3,
+ "operator_codes": [ { "builtin_code": "MINIMUM" } ],
+ "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 MinimumFixture4D : MinimumFixture
+{
+ MinimumFixture4D() : MinimumFixture("[ 1, 2, 2, 3 ]",
+ "[ 1, 2, 2, 3 ]",
+ "[ 1, 2, 2, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMinimum4D, MinimumFixture4D)
+{
+ 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", { 0.0f, 0.0f, 0.0f,
+ 5.0f, 5.0f, 5.0f,
+ 7.0f, 7.0f, 7.0f,
+ 9.0f, 9.0f, 9.0f }}},
+ {{"outputTensor", { 0.0f, 0.0f, 0.0f,
+ 3.0f, 4.0f, 5.0f,
+ 6.0f, 7.0f, 7.0f,
+ 9.0f, 9.0f, 9.0f }}});
+}
+
+struct MinimumBroadcastFixture4D : MinimumFixture
+{
+ MinimumBroadcastFixture4D() : MinimumFixture("[ 1, 1, 2, 1 ]",
+ "[ 1, 2, 1, 3 ]",
+ "[ 1, 2, 2, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMinimumBroadcast4D, MinimumBroadcastFixture4D)
+{
+ 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", { 1.0f, 2.0f, 2.0f,
+ 1.0f, 2.0f, 3.0f,
+ 2.0f, 2.0f, 2.0f,
+ 4.0f, 4.0f, 4.0f }}});
+}
+
+struct MinimumBroadcastFixture4D1D : MinimumFixture
+{
+ MinimumBroadcastFixture4D1D() : MinimumFixture("[ 1, 2, 2, 3 ]",
+ "[ 1 ]",
+ "[ 1, 2, 2, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMinimumBroadcast4D1D, MinimumBroadcastFixture4D1D)
+{
+ 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", { 0.0f, 1.0f, 2.0f,
+ 3.0f, 4.0f, 5.0f,
+ 5.0f, 5.0f, 5.0f,
+ 5.0f, 5.0f, 5.0f }}});
+}
+
+struct MinimumBroadcastFixture1D4D : MinimumFixture
+{
+ MinimumBroadcastFixture1D4D() : MinimumFixture("[ 3 ]",
+ "[ 1, 2, 2, 3 ]",
+ "[ 1, 2, 2, 3 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseMinimumBroadcast1D4D, MinimumBroadcastFixture1D4D)
+{
+ RunTest<4, armnn::DataType::Float32>(
+ 0,
+ {{"inputTensor1", { 5.0f, 6.0f, 7.0f }},
+ {"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", { 0.0f, 1.0f, 2.0f,
+ 3.0f, 4.0f, 5.0f,
+ 5.0f, 6.0f, 7.0f,
+ 5.0f, 6.0f, 7.0f }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()