diff options
Diffstat (limited to 'src/armnnDeserializer')
-rw-r--r-- | src/armnnDeserializer/Deserializer.cpp | 23 | ||||
-rw-r--r-- | src/armnnDeserializer/Deserializer.hpp | 1 | ||||
-rw-r--r-- | src/armnnDeserializer/DeserializerSupport.md | 1 | ||||
-rw-r--r-- | src/armnnDeserializer/test/DeserializeEqual.cpp | 148 |
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() |