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-rw-r--r--src/armnnDeserializer/Deserializer.cpp30
-rw-r--r--src/armnnDeserializer/Deserializer.hpp1
-rw-r--r--src/armnnDeserializer/DeserializerSupport.md1
-rw-r--r--src/armnnDeserializer/test/DeserializeResizeBilinear.cpp131
4 files changed, 163 insertions, 0 deletions
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index aebdf0e52c..aa7454339e 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -205,6 +205,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
m_ParserFunctions[Layer_PermuteLayer] = &Deserializer::ParsePermute;
m_ParserFunctions[Layer_Pooling2dLayer] = &Deserializer::ParsePooling2d;
m_ParserFunctions[Layer_ReshapeLayer] = &Deserializer::ParseReshape;
+ m_ParserFunctions[Layer_ResizeBilinearLayer] = &Deserializer::ParseResizeBilinear;
m_ParserFunctions[Layer_RsqrtLayer] = &Deserializer::ParseRsqrt;
m_ParserFunctions[Layer_SoftmaxLayer] = &Deserializer::ParseSoftmax;
m_ParserFunctions[Layer_SpaceToBatchNdLayer] = &Deserializer::ParseSpaceToBatchNd;
@@ -260,6 +261,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
return graphPtr->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->base();
case Layer::Layer_ReshapeLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base();
+ case Layer::Layer_ResizeBilinearLayer:
+ return graphPtr->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->base();
case Layer::Layer_RsqrtLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_RsqrtLayer()->base();
case Layer::Layer_SoftmaxLayer:
@@ -1431,6 +1434,33 @@ void Deserializer::ParseReshape(GraphPtr graph, unsigned int layerIndex)
RegisterOutputSlots(graph, layerIndex, layer);
}
+void Deserializer::ParseResizeBilinear(GraphPtr graph, unsigned int layerIndex)
+{
+ CHECK_LAYERS(graph, 0, layerIndex);
+
+ Deserializer::TensorRawPtrVector inputs = GetInputs(graph, layerIndex);
+ CHECK_VALID_SIZE(inputs.size(), 1);
+
+ Deserializer::TensorRawPtrVector outputs = GetOutputs(graph, layerIndex);
+ CHECK_VALID_SIZE(outputs.size(), 1);
+
+ auto flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->descriptor();
+
+ armnn::ResizeBilinearDescriptor descriptor;
+ descriptor.m_TargetWidth = flatBufferDescriptor->targetWidth();
+ descriptor.m_TargetHeight = flatBufferDescriptor->targetHeight();
+ descriptor.m_DataLayout = ToDataLayout(flatBufferDescriptor->dataLayout());
+
+ auto layerName = GetLayerName(graph, layerIndex);
+ IConnectableLayer* layer = m_Network->AddResizeBilinearLayer(descriptor, layerName.c_str());
+
+ armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ RegisterInputSlots(graph, layerIndex, layer);
+ RegisterOutputSlots(graph, layerIndex, layer);
+}
+
void Deserializer::ParseSoftmax(GraphPtr graph, unsigned int layerIndex)
{
CHECK_LAYERS(graph, 0, layerIndex);
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index 7e25534763..cabc91f58d 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -91,6 +91,7 @@ private:
void ParsePermute(GraphPtr graph, unsigned int layerIndex);
void ParsePooling2d(GraphPtr graph, unsigned int layerIndex);
void ParseReshape(GraphPtr graph, unsigned int layerIndex);
+ void ParseResizeBilinear(GraphPtr graph, unsigned int layerIndex);
void ParseRsqrt(GraphPtr graph, unsigned int layerIndex);
void ParseSoftmax(GraphPtr graph, unsigned int layerIndex);
void ParseSpaceToBatchNd(GraphPtr graph, unsigned int layerIndex);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index ba85a04bb2..0a1ef75260 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -26,6 +26,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
* Permute
* Pooling2d
* Reshape
+* ResizeBilinear
* Rsqrt
* Softmax
* SpaceToBatchNd
diff --git a/src/armnnDeserializer/test/DeserializeResizeBilinear.cpp b/src/armnnDeserializer/test/DeserializeResizeBilinear.cpp
new file mode 100644
index 0000000000..b01832499e
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeResizeBilinear.cpp
@@ -0,0 +1,131 @@
+//
+// 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>
+
+BOOST_AUTO_TEST_SUITE(Deserializer)
+
+struct ResizeBilinearFixture : public ParserFlatbuffersSerializeFixture
+{
+ explicit ResizeBilinearFixture(const std::string& inputShape,
+ const std::string& targetWidth,
+ const std::string& targetHeight,
+ const std::string& dataLayout,
+ const std::string& outputShape,
+ const std::string& dataType)
+ {
+ m_JsonString = R"(
+ {
+ inputIds: [0],
+ outputIds: [2],
+ layers: [
+ {
+ layer_type: "InputLayer",
+ layer: {
+ base: {
+ layerBindingId: 0,
+ base: {
+ index: 0,
+ layerName: "InputLayer",
+ layerType: "Input",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + inputShape + R"(,
+ dataType: )" + dataType + R"(
+ }
+ }]
+ }
+ }
+ }
+ },
+ {
+ layer_type: "ResizeBilinearLayer",
+ layer: {
+ base: {
+ index: 1,
+ layerName: "ResizeBilinearLayer",
+ layerType: "ResizeBilinear",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + outputShape + R"(,
+ dataType: )" + dataType + R"(
+ }
+ }]
+ },
+ descriptor: {
+ targetWidth: )" + targetWidth + R"(,
+ targetHeight: )" + targetHeight + R"(,
+ dataLayout: )" + dataLayout + R"(,
+ }
+ }
+ },
+ {
+ layer_type: "OutputLayer",
+ layer: {
+ base:{
+ layerBindingId: 2,
+ base: {
+ index: 2,
+ layerName: "OutputLayer",
+ layerType: "Output",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:1, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + outputShape + R"(,
+ dataType: )" + dataType + R"(
+ },
+ }],
+ }
+ }
+ },
+ }
+ ]
+ }
+ )";
+ SetupSingleInputSingleOutput("InputLayer", "OutputLayer");
+ }
+};
+
+struct SimpleResizeBilinearFixture : ResizeBilinearFixture
+{
+ SimpleResizeBilinearFixture() : ResizeBilinearFixture("[1, 2, 2, 2]",
+ "1",
+ "1",
+ "NCHW",
+ "[1, 2, 1, 1]",
+ "Float32") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SimpleResizeBilinearFloat32, SimpleResizeBilinearFixture)
+{
+ RunTest<4, armnn::DataType::Float32>(0,
+ {
+ 1.0f, 255.0f, 200.0f, 250.0f,
+ 250.0f, 200.0f, 250.0f, 1.0f
+ },
+ {
+ 1.0f, 250.0f
+ });
+}
+
+BOOST_AUTO_TEST_SUITE_END()
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-01 00:59:54 +0000