Add NEG support to TFLite parser
* Added unit tests
* Updated Documentation
Signed-off-by: Darshan Patel <darsh.jp@gmail.com>
Change-Id: Id22ffebe60732a93798f72801eb8a2a23cdd7ec0
diff --git a/src/armnnTfLiteParser/TensorFlowLiteSupport.md b/src/armnnTfLiteParser/TensorFlowLiteSupport.md
index ff80ffc..9718b22 100644
--- a/src/armnnTfLiteParser/TensorFlowLiteSupport.md
+++ b/src/armnnTfLiteParser/TensorFlowLiteSupport.md
@@ -42,6 +42,8 @@
* MUL
+* NEG
+
* PACK
* PAD
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index f4f675e..08bd68d 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -510,6 +510,7 @@
m_ParserFunctions[tflite::BuiltinOperator_MEAN] = &TfLiteParser::ParseMean;
m_ParserFunctions[tflite::BuiltinOperator_MINIMUM] = &TfLiteParser::ParseMinimum;
m_ParserFunctions[tflite::BuiltinOperator_MUL] = &TfLiteParser::ParseMul;
+ m_ParserFunctions[tflite::BuiltinOperator_NEG] = &TfLiteParser::ParseNeg;
m_ParserFunctions[tflite::BuiltinOperator_PACK] = &TfLiteParser::ParsePack;
m_ParserFunctions[tflite::BuiltinOperator_PAD] = &TfLiteParser::ParsePad;
m_ParserFunctions[tflite::BuiltinOperator_QUANTIZE] = &TfLiteParser::ParseQuantize;
@@ -1819,6 +1820,31 @@
RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]});
}
+void TfLiteParser::ParseNeg(size_t subgraphIndex, size_t operatorIndex)
+{
+ CHECK_MODEL(m_Model, subgraphIndex, operatorIndex);
+
+ auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(inputs.size(), 1);
+
+ auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
+ CHECK_VALID_SIZE(outputs.size(), 1);
+
+ auto layerName = boost::str(boost::format("Neg:%1%:%2%") % subgraphIndex % operatorIndex);
+ armnn::ElementwiseUnaryDescriptor descriptor(armnn::UnaryOperation::Neg);
+ IConnectableLayer* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());
+ ARMNN_ASSERT(layer != nullptr);
+
+ TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+ 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);
+}
+
void TfLiteParser::ParsePad(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 f0f75af..c252b0f 100644
--- a/src/armnnTfLiteParser/TfLiteParser.hpp
+++ b/src/armnnTfLiteParser/TfLiteParser.hpp
@@ -112,6 +112,7 @@
void ParseMean(size_t subgraphIndex, size_t operatorIndex);
void ParseMinimum(size_t subgraphIndex, size_t operatorIndex);
void ParseMul(size_t subgraphIndex, size_t operatorIndex);
+ void ParseNeg(size_t subgraphIndex, size_t operatorIndex);
void ParsePack(size_t subgraphIndex, size_t operatorIndex);
void ParsePad(size_t subgraphIndex, size_t operatorIndex);
void ParsePool(size_t subgraphIndex, size_t operatorIndex, armnn::PoolingAlgorithm algorithm);
diff --git a/src/armnnTfLiteParser/test/Neg.cpp b/src/armnnTfLiteParser/test/Neg.cpp
new file mode 100644
index 0000000..39e1f9e
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Neg.cpp
@@ -0,0 +1,85 @@
+//
+// Copyright © 2020 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersFixture.hpp"
+#include "../TfLiteParser.hpp"
+
+#include <string>
+
+BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
+
+struct NegFixture : public ParserFlatbuffersFixture
+{
+ explicit NegFixture(const std::string & inputShape,
+ const std::string & outputShape)
+ {
+ m_JsonString = R"(
+ {
+ "version": 3,
+ "operator_codes": [ { "builtin_code": "NEG" } ],
+ "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 ],
+ }
+ }
+ ],
+ "inputs": [ 0 ],
+ "outputs": [ 1 ],
+ "operators": [
+ {
+ "opcode_index": 0,
+ "inputs": [ 0 ],
+ "outputs": [ 1 ],
+ "custom_options_format": "FLEXBUFFERS"
+ }
+ ],
+ } ],
+ "buffers" : [
+ { },
+ { }
+ ]
+ }
+ )";
+ Setup();
+ }
+};
+
+struct SimpleNegFixture : public NegFixture
+{
+ SimpleNegFixture() : NegFixture("[ 1, 2, 3, 1 ]", "[ 1, 2, 3, 1 ]") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(ParseNeg, SimpleNegFixture)
+{
+ using armnn::DataType;
+ RunTest<4, DataType::Float32>(0, {{ "inputTensor", { 0.0f, 1.0f, -2.0f,
+ 20.0855185f, -54.5980834f, 5.0f} }},
+ {{ "outputTensor",{ 0.0f, -1.0f, 2.0f,
+ -20.0855185f, 54.5980834f, -5.0f} }});
+}
+
+BOOST_AUTO_TEST_SUITE_END()