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-rw-r--r--src/armnnDeserializer/Deserializer.cpp46
-rw-r--r--src/armnnDeserializer/Deserializer.hpp1
-rw-r--r--src/armnnDeserializer/DeserializerSupport.md1
-rw-r--r--src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp140
4 files changed, 188 insertions, 0 deletions
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index b263c3a769..64f8e44429 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -196,6 +196,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
m_ParserFunctions[Layer_Pooling2dLayer] = &Deserializer::ParsePooling2d;
m_ParserFunctions[Layer_ReshapeLayer] = &Deserializer::ParseReshape;
m_ParserFunctions[Layer_SoftmaxLayer] = &Deserializer::ParseSoftmax;
+ m_ParserFunctions[Layer_SpaceToBatchNdLayer] = &Deserializer::ParseSpaceToBatchNd;
}
Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPtr, unsigned int layerIndex)
@@ -230,6 +231,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
return graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base();
case Layer::Layer_SoftmaxLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base();
+ case Layer::Layer_SpaceToBatchNdLayer:
+ return graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->base();
case Layer::Layer_NONE:
default:
throw ParseException(boost::str(
@@ -1176,4 +1179,47 @@ void Deserializer::ParseSoftmax(GraphPtr graph, unsigned int layerIndex)
RegisterOutputSlots(graph, layerIndex, layer);
}
+void Deserializer::ParseSpaceToBatchNd(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_SpaceToBatchNdLayer()->descriptor();
+ auto flatBufferPadList = flatBufferDescriptor->padList();
+ auto flatBufferBlockShape = flatBufferDescriptor->blockShape();
+
+ if (flatBufferPadList->Length() % 2 != 0)
+ {
+ throw ParseException(boost::str(
+ boost::format("The size of the pad list must be divisible by 2 %1%") % CHECK_LOCATION().AsString()));
+ }
+
+ std::vector<std::pair<unsigned int, unsigned int>> padList;
+ padList.reserve(flatBufferPadList->Length() / 2);
+ for (unsigned int i = 0; i < flatBufferPadList->Length() - 1; i += 2)
+ {
+ padList.emplace_back(flatBufferPadList->Get(i), flatBufferPadList->Get(i+1));
+ }
+
+ armnn::SpaceToBatchNdDescriptor descriptor;
+ descriptor.m_DataLayout = ToDataLayout(flatBufferDescriptor->dataLayout());
+ descriptor.m_BlockShape =
+ std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());
+ descriptor.m_PadList = padList;
+
+ auto layerName = GetLayerName(graph, layerIndex);
+ IConnectableLayer* layer = m_Network->AddSpaceToBatchNdLayer(descriptor, layerName.c_str());
+
+ armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ RegisterInputSlots(graph, layerIndex, layer);
+ RegisterOutputSlots(graph, layerIndex, layer);
+}
+
} // namespace armnnDeserializer
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index 9159ff2f36..c88459d97a 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -79,6 +79,7 @@ private:
void ParsePooling2d(GraphPtr graph, unsigned int layerIndex);
void ParseReshape(GraphPtr graph, unsigned int layerIndex);
void ParseSoftmax(GraphPtr graph, unsigned int layerIndex);
+ void ParseSpaceToBatchNd(GraphPtr graph, unsigned int layerIndex);
void RegisterOutputSlotOfConnection(uint32_t connectionIndex, armnn::IOutputSlot* slot);
void RegisterInputSlotOfConnection(uint32_t connectionIndex, armnn::IInputSlot* slot);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index 988144425c..4ae9780bc7 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -17,5 +17,6 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
* Pooling2d
* Reshape
* Softmax
+* SpaceToBatchNd
More machine learning layers will be supported in future releases.
diff --git a/src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp b/src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp
new file mode 100644
index 0000000000..4b34390ed5
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp
@@ -0,0 +1,140 @@
+//
+// 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 SpaceToBatchNdFixture : public ParserFlatbuffersSerializeFixture
+{
+ explicit SpaceToBatchNdFixture(const std::string &inputShape,
+ const std::string &blockShape,
+ const std::string &padList,
+ 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: "SpaceToBatchNdLayer",
+ layer: {
+ base: {
+ index: 1,
+ layerName: "SpaceToBatchNdLayer",
+ layerType: "SpaceToBatchNd",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + outputShape + R"(,
+ dataType: )" + dataType + R"(
+ }
+ }]
+ },
+ descriptor: {
+ blockShape: )" + blockShape + R"(,
+ padList: )" + padList + 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 SimpleSpaceToBatchNdFixture : SpaceToBatchNdFixture
+{
+ SimpleSpaceToBatchNdFixture() : SpaceToBatchNdFixture("[ 2, 1, 2, 4 ]",
+ "[ 2, 2 ]",
+ "[ 0, 0, 2, 0 ]",
+ "NCHW",
+ "[ 8, 1, 1, 3 ]",
+ "Float32") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SimpleSpaceToBatchNdFloat32, SimpleSpaceToBatchNdFixture)
+{
+ RunTest<4, armnn::DataType::Float32>(0,
+ {
+ 1.0f, 2.0f, 3.0f, 4.0f,
+ 5.0f, 6.0f, 7.0f, 8.0f,
+ 9.0f, 10.0f, 11.0f, 12.0f,
+ 13.0f, 14.0f, 15.0f, 16.0f
+ },
+ {
+ 0.0f, 1.0f, 3.0f,
+ 0.0f, 9.0f, 11.0f,
+ 0.0f, 2.0f, 4.0f,
+ 0.0f, 10.0f, 12.0f,
+ 0.0f, 5.0f, 7.0f,
+ 0.0f, 13.0f, 15.0f,
+ 0.0f, 6.0f, 8.0f,
+ 0.0f, 14.0f, 16.0f
+ });
+}
+
+BOOST_AUTO_TEST_SUITE_END()
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-01 01:59:16 +0000