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-rw-r--r--src/armnnDeserializer/Deserializer.cpp23
-rw-r--r--src/armnnDeserializer/Deserializer.hpp1
-rw-r--r--src/armnnDeserializer/DeserializerSupport.md1
-rw-r--r--src/armnnDeserializer/test/DeserializeEqual.cpp148
4 files changed, 173 insertions, 0 deletions
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index 28c6c94c7a..317269ebd0 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -192,6 +192,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
m_ParserFunctions[Layer_Convolution2dLayer] = &Deserializer::ParseConvolution2d;
m_ParserFunctions[Layer_DepthwiseConvolution2dLayer] = &Deserializer::ParseDepthwiseConvolution2d;
m_ParserFunctions[Layer_DivisionLayer] = &Deserializer::ParseDivision;
+ m_ParserFunctions[Layer_EqualLayer] = &Deserializer::ParseEqual;
m_ParserFunctions[Layer_FullyConnectedLayer] = &Deserializer::ParseFullyConnected;
m_ParserFunctions[Layer_MinimumLayer] = &Deserializer::ParseMinimum;
m_ParserFunctions[Layer_MultiplicationLayer] = &Deserializer::ParseMultiplication;
@@ -222,6 +223,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
return graphPtr->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer()->base();
case Layer::Layer_DivisionLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_DivisionLayer()->base();
+ case Layer::Layer_EqualLayer:
+ return graphPtr->layers()->Get(layerIndex)->layer_as_EqualLayer()->base();
case Layer::Layer_FullyConnectedLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer()->base();
case Layer::Layer_InputLayer:
@@ -958,6 +961,26 @@ void Deserializer::ParseDivision(GraphPtr graph, unsigned int layerIndex)
RegisterOutputSlots(graph, layerIndex, layer);
}
+void Deserializer::ParseEqual(GraphPtr graph, unsigned int layerIndex)
+{
+ CHECK_LAYERS(graph, 0, layerIndex);
+ auto inputs = GetInputs(graph, layerIndex);
+ CHECK_LOCATION();
+ CHECK_VALID_SIZE(inputs.size(), 2);
+
+ auto outputs = GetOutputs(graph, layerIndex);
+ CHECK_VALID_SIZE(outputs.size(), 1);
+
+ auto layerName = GetLayerName(graph, layerIndex);
+ IConnectableLayer* layer = m_Network->AddEqualLayer(layerName.c_str());
+
+ armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ RegisterInputSlots(graph, layerIndex, layer);
+ RegisterOutputSlots(graph, layerIndex, layer);
+}
+
void Deserializer::ParseMinimum(GraphPtr graph, unsigned int layerIndex)
{
CHECK_LAYERS(graph, 0, layerIndex);
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index 657c7f5ed8..e75ab1c5b6 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -75,6 +75,7 @@ private:
void ParseConvolution2d(GraphPtr graph, unsigned int layerIndex);
void ParseDepthwiseConvolution2d(GraphPtr graph, unsigned int layerIndex);
void ParseDivision(GraphPtr graph, unsigned int layerIndex);
+ void ParseEqual(GraphPtr graph, unsigned int layerIndex);
void ParseFullyConnected(GraphPtr graph, unsigned int layerIndex);
void ParseMinimum(GraphPtr graph, unsigned int layerIndex);
void ParseMultiplication(GraphPtr graph, unsigned int layerIndex);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index 8fd7b421a3..791068340f 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -13,6 +13,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
* Convolution2d
* DepthwiseConvolution2d
* Division
+* Equal
* FullyConnected
* Minimum
* Multiplication
diff --git a/src/armnnDeserializer/test/DeserializeEqual.cpp b/src/armnnDeserializer/test/DeserializeEqual.cpp
new file mode 100644
index 0000000000..7d8213cd95
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeEqual.cpp
@@ -0,0 +1,148 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersSerializeFixture.hpp"
+#include "../Deserializer.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(Deserializer)
+
+struct EqualFixture : public ParserFlatbuffersSerializeFixture
+{
+ explicit EqualFixture(const std::string & inputShape1,
+ const std::string & inputShape2,
+ const std::string & outputShape,
+ const std::string & dataType)
+ {
+ m_JsonString = R"(
+ {
+ inputIds: [0, 1],
+ outputIds: [3],
+ layers: [
+ {
+ layer_type: "InputLayer",
+ layer: {
+ base: {
+ layerBindingId: 0,
+ base: {
+ index: 0,
+ layerName: "InputLayer1",
+ layerType: "Input",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + inputShape1 + R"(,
+ dataType: )" + dataType + R"(
+ },
+ }],
+ },
+ }
+ },
+ },
+ {
+ layer_type: "InputLayer",
+ layer: {
+ base: {
+ layerBindingId: 1,
+ base: {
+ index:1,
+ layerName: "InputLayer2",
+ layerType: "Input",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + inputShape2 + R"(,
+ dataType: )" + dataType + R"(
+ },
+ }],
+ },
+ }
+ },
+ },
+ {
+ layer_type: "EqualLayer",
+ layer: {
+ base: {
+ index:2,
+ layerName: "EqualLayer",
+ layerType: "Equal",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ },
+ {
+ index: 1,
+ connection: {sourceLayerIndex:1, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + outputShape + R"(,
+ dataType: Boolean
+ },
+ }],
+ }
+ },
+ },
+ {
+ layer_type: "OutputLayer",
+ layer: {
+ base:{
+ layerBindingId: 0,
+ base: {
+ index: 3,
+ layerName: "OutputLayer",
+ layerType: "Output",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:2, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + outputShape + R"(,
+ dataType: Boolean
+ },
+ }],
+ }
+ }
+ },
+ }
+ ]
+ }
+ )";
+ Setup();
+ }
+};
+
+struct SimpleEqualFixture : EqualFixture
+{
+ SimpleEqualFixture() : EqualFixture("[ 2, 2, 2, 1 ]",
+ "[ 2, 2, 2, 1 ]",
+ "[ 2, 2, 2, 1 ]",
+ "QuantisedAsymm8") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(EqualQuantisedAsymm8, SimpleEqualFixture)
+{
+ RunTest<4, armnn::DataType::QuantisedAsymm8, armnn::DataType::Boolean>(
+ 0,
+ {{"InputLayer1", { 0, 1, 2, 3, 4, 5, 6, 7 }},
+ {"InputLayer2", { 0, 0, 0, 3, 0, 0, 6, 7 }}},
+ {{"OutputLayer", { 1, 0, 0, 1, 0, 0, 1, 1 }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-02 09:50:51 +0000