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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/DeserializeBatchToSpaceNd.cpp136
4 files changed, 184 insertions, 0 deletions
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index 64f8e44429..30f7d05c93 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -187,6 +187,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
// register supported layers
m_ParserFunctions[Layer_ActivationLayer] = &Deserializer::ParseActivation;
m_ParserFunctions[Layer_AdditionLayer] = &Deserializer::ParseAdd;
+ m_ParserFunctions[Layer_BatchToSpaceNdLayer] = &Deserializer::ParseBatchToSpaceNd;
m_ParserFunctions[Layer_ConstantLayer] = &Deserializer::ParseConstant;
m_ParserFunctions[Layer_Convolution2dLayer] = &Deserializer::ParseConvolution2d;
m_ParserFunctions[Layer_DepthwiseConvolution2dLayer] = &Deserializer::ParseDepthwiseConvolution2d;
@@ -209,6 +210,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
return graphPtr->layers()->Get(layerIndex)->layer_as_ActivationLayer()->base();
case Layer::Layer_AdditionLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base();
+ case Layer::Layer_BatchToSpaceNdLayer:
+ return graphPtr->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->base();
case Layer::Layer_ConstantLayer:
return graphPtr->layers()->Get(layerIndex)->layer_as_ConstantLayer()->base();
case Layer::Layer_Convolution2dLayer:
@@ -778,6 +781,49 @@ void Deserializer::ParseAdd(GraphPtr graph, unsigned int layerIndex)
RegisterOutputSlots(graph, layerIndex, layer);
}
+void Deserializer::ParseBatchToSpaceNd(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_BatchToSpaceNdLayer()->descriptor();
+ auto flatBufferCrops = flatBufferDescriptor->crops();
+ auto flatBufferBlockShape = flatBufferDescriptor->blockShape();
+
+ if (flatBufferCrops->Length() % 2 != 0)
+ {
+ throw ParseException(boost::str(
+ boost::format("The size of crops must be divisible by 2 %1%") % CHECK_LOCATION().AsString()));
+ }
+
+ std::vector<std::pair<unsigned int, unsigned int>> crops;
+ crops.reserve(flatBufferCrops->Length() / 2);
+ for (unsigned int i = 0; i < flatBufferCrops->Length() - 1; i += 2)
+ {
+ crops.emplace_back(flatBufferCrops->Get(i), flatBufferCrops->Get(i+1));
+ }
+
+ armnn::BatchToSpaceNdDescriptor descriptor;
+ descriptor.m_DataLayout = ToDataLayout(flatBufferDescriptor->dataLayout());
+ descriptor.m_BlockShape =
+ std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());
+ descriptor.m_Crops = crops;
+
+ auto layerName = GetLayerName(graph, layerIndex);
+ IConnectableLayer* layer = m_Network->AddBatchToSpaceNdLayer(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::ParseConstant(GraphPtr graph, unsigned int layerIndex)
{
CHECK_LAYERS(graph, 0, layerIndex);
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index c88459d97a..0e0261f27b 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -70,6 +70,7 @@ private:
void ParseUnsupportedLayer(GraphPtr graph, unsigned int layerIndex);
void ParseActivation(GraphPtr graph, unsigned int layerIndex);
void ParseAdd(GraphPtr graph, unsigned int layerIndex);
+ void ParseBatchToSpaceNd(GraphPtr graph, unsigned int layerIndex);
void ParseConstant(GraphPtr graph, unsigned int layerIndex);
void ParseConvolution2d(GraphPtr graph, unsigned int layerIndex);
void ParseDepthwiseConvolution2d(GraphPtr graph, unsigned int layerIndex);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index 4ae9780bc7..31a53569ad 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -8,6 +8,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
* Activation
* Addition
+* BatchToSpaceNd
* Constant
* Convolution2d
* DepthwiseConvolution2d
diff --git a/src/armnnDeserializer/test/DeserializeBatchToSpaceNd.cpp b/src/armnnDeserializer/test/DeserializeBatchToSpaceNd.cpp
new file mode 100644
index 0000000000..e85f4ada9d
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeBatchToSpaceNd.cpp
@@ -0,0 +1,136 @@
+//
+// 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 BatchToSpaceNdFixture : public ParserFlatbuffersSerializeFixture
+{
+ explicit BatchToSpaceNdFixture(const std::string &inputShape,
+ const std::string &blockShape,
+ const std::string &crops,
+ 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: "BatchToSpaceNdLayer",
+ layer: {
+ base: {
+ index: 1,
+ layerName: "BatchToSpaceNdLayer",
+ layerType: "BatchToSpaceNd",
+ inputSlots: [{
+ index: 0,
+ connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+ }],
+ outputSlots: [{
+ index: 0,
+ tensorInfo: {
+ dimensions: )" + outputShape + R"(,
+ dataType: )" + dataType + R"(
+ }
+ }]
+ },
+ descriptor: {
+ blockShape: )" + blockShape + R"(,
+ crops: )" + crops + 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 SimpleBatchToSpaceNdFixture : BatchToSpaceNdFixture
+{
+ SimpleBatchToSpaceNdFixture() : BatchToSpaceNdFixture("[ 4, 2, 2, 1 ]",
+ "[ 2, 2 ]",
+ "[ 0, 0, 0, 0 ]",
+ "NHWC",
+ "[ 1, 4, 4, 1 ]",
+ "Float32") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SimpleBatchToSpaceNdFloat32, SimpleBatchToSpaceNdFixture)
+{
+ RunTest<4, armnn::DataType::Float32>(0,
+ {
+ 1.0f, 3.0f, 9.0f, 11.0f,
+ 2.0f, 4.0f, 10.0f, 12.0f,
+ 5.0f, 7.0f, 13.0f, 15.0f,
+ 6.0f, 8.0f, 14.0f, 16.0f
+ },
+ {
+ 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
+ });
+}
+
+BOOST_AUTO_TEST_SUITE_END()
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-06 00:22:48 +0000