IVGCVSW-6127 ConstTensorsAsInput: DepthwiseConvolution2d
!android-nn-driver:7418
* Update Front-end and Tools.
* Updated Serializer, Deserializer and unit tests to reflect this.
* Updated TfLiteDelegate, TfLiteParser and OnnxParser.
* Change NNDriver to new API.
* Updated Ref.
* Neon and Cl backend partially completed (Backend.cpp files).
* Added dynamic or constant input EndToEnd tests.
* Added ConstantTensorAsInputMemeberVariableRedirect Optimization.
Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: Ib18b6c10a093042e165e25237dc04a4c67ba82da
diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp
index 3b9dfb0..99d1c2b 100644
--- a/src/armnnSerializer/Serializer.cpp
+++ b/src/armnnSerializer/Serializer.cpp
@@ -441,13 +441,10 @@
void SerializerStrategy::SerializeDepthwiseConvolution2dLayer(const armnn::IConnectableLayer* layer,
const armnn::DepthwiseConvolution2dDescriptor& descriptor,
- const std::vector<armnn::ConstTensor>& constants,
const char* name)
{
IgnoreUnused(name);
- const armnn::ConstTensor& weights = constants[0];
-
auto fbBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_DepthwiseConvolution2d);
auto fbDescriptor = CreateDepthwiseConvolution2dDescriptor(m_flatBufferBuilder,
descriptor.m_PadLeft,
@@ -461,20 +458,9 @@
descriptor.m_BiasEnabled,
GetFlatBufferDataLayout(descriptor.m_DataLayout));
- flatbuffers::Offset<serializer::ConstTensor> fbWeightsConstTensorInfo = CreateConstTensorInfo(weights);
- flatbuffers::Offset<serializer::ConstTensor> fbBiasesConstTensorInfo;
-
- if (constants.size() > 1)
- {
- const armnn::ConstTensor& biases = constants[1];
- fbBiasesConstTensorInfo = CreateConstTensorInfo(biases);
- }
-
auto flatBufferLayer = CreateDepthwiseConvolution2dLayer(m_flatBufferBuilder,
fbBaseLayer,
- fbDescriptor,
- fbWeightsConstTensorInfo,
- fbBiasesConstTensorInfo);
+ fbDescriptor);
CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_DepthwiseConvolution2dLayer);
}
@@ -2090,7 +2076,6 @@
static_cast<const armnn::DepthwiseConvolution2dDescriptor&>(descriptor);
SerializeDepthwiseConvolution2dLayer(layer,
layerDescriptor,
- constants,
name);
break;
}
diff --git a/src/armnnSerializer/Serializer.hpp b/src/armnnSerializer/Serializer.hpp
index 98c1984..afde778 100644
--- a/src/armnnSerializer/Serializer.hpp
+++ b/src/armnnSerializer/Serializer.hpp
@@ -158,7 +158,6 @@
void SerializeDepthwiseConvolution2dLayer(const armnn::IConnectableLayer* layer,
const armnn::DepthwiseConvolution2dDescriptor& descriptor,
- const std::vector<armnn::ConstTensor>& constants,
const char* name = nullptr);
void SerializeDequantizeLayer(const armnn::IConnectableLayer* layer,
diff --git a/src/armnnSerializer/test/SerializerTestUtils.cpp b/src/armnnSerializer/test/SerializerTestUtils.cpp
index d0a8e2d..cf2cb15 100644
--- a/src/armnnSerializer/test/SerializerTestUtils.cpp
+++ b/src/armnnSerializer/test/SerializerTestUtils.cpp
@@ -54,8 +54,14 @@
CHECK(
GetDataTypeName(connectedInfo.GetDataType()) == GetDataTypeName(m_InputTensorInfos[i].GetDataType()));
- CHECK(connectedInfo.GetQuantizationScale() == m_InputTensorInfos[i].GetQuantizationScale());
- CHECK(connectedInfo.GetQuantizationOffset() == m_InputTensorInfos[i].GetQuantizationOffset());
+ // If weights and bias are connected to DepthwiseConvolution2d via Constant Layer we do not check.
+ // Constant Layer already disabled in SerializerTestUtils.hpp from entering function.
+ if (layer->GetType() == armnn::LayerType::DepthwiseConvolution2d &&
+ connectedOutput->GetOwningIConnectableLayer().GetType() != armnn::LayerType::Constant)
+ {
+ CHECK(connectedInfo.GetQuantizationScale() == m_InputTensorInfos[i].GetQuantizationScale());
+ CHECK(connectedInfo.GetQuantizationOffset() == m_InputTensorInfos[i].GetQuantizationOffset());
+ }
}
for (unsigned int i = 0; i < m_OutputTensorInfos.size(); i++)
diff --git a/src/armnnSerializer/test/SerializerTestUtils.hpp b/src/armnnSerializer/test/SerializerTestUtils.hpp
index ce4d2cc..ac15ced 100644
--- a/src/armnnSerializer/test/SerializerTestUtils.hpp
+++ b/src/armnnSerializer/test/SerializerTestUtils.hpp
@@ -128,6 +128,7 @@
{
case armnn::LayerType::Input: break;
case armnn::LayerType::Output: break;
+ case armnn::LayerType::Constant: break;
default:
{
this->VerifyNameAndConnections(layer, name);
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index a765290..278715b 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -553,11 +553,8 @@
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const depthwiseConvLayer =
- network->AddDepthwiseConvolution2dLayer(descriptor,
- weights,
- armnn::Optional<armnn::ConstTensor>(biases),
- layerName.c_str());
+ armnn::IConnectableLayer* const depthwiseConvLayer = network->AddDepthwiseConvolution2dLayer(descriptor,
+ layerName.c_str());
armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0));
@@ -566,12 +563,20 @@
inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+ armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights);
+ weightsLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(1u));
+ weightsLayer->GetOutputSlot(0).SetTensorInfo(weights.GetInfo());
+
+ armnn::IConnectableLayer* const biasLayer = network->AddConstantLayer(biases);
+ biasLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(2u));
+ biasLayer->GetOutputSlot(0).SetTensorInfo(biases.GetInfo());
+
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
CHECK(deserializedNetwork);
const std::vector<armnn::ConstTensor>& constants {weights, biases};
LayerVerifierBaseWithDescriptorAndConstants<armnn::DepthwiseConvolution2dDescriptor> verifier(
- layerName, {inputInfo}, {outputInfo}, descriptor, constants);
+ layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor, constants);
deserializedNetwork->ExecuteStrategy(verifier);
}
@@ -610,11 +615,8 @@
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const depthwiseConvLayer =
- network->AddDepthwiseConvolution2dLayer(descriptor,
- weights,
- armnn::Optional<armnn::ConstTensor>(biases),
- layerName.c_str());
+ armnn::IConnectableLayer* const depthwiseConvLayer = network->AddDepthwiseConvolution2dLayer(descriptor,
+ layerName.c_str());
armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0));
@@ -623,12 +625,75 @@
inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+ armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights);
+ weightsLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(1u));
+ weightsLayer->GetOutputSlot(0).SetTensorInfo(weights.GetInfo());
+
+ armnn::IConnectableLayer* const biasLayer = network->AddConstantLayer(biases);
+ biasLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(2u));
+ biasLayer->GetOutputSlot(0).SetTensorInfo(biases.GetInfo());
+
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
CHECK(deserializedNetwork);
const std::vector<armnn::ConstTensor>& constants {weights, biases};
LayerVerifierBaseWithDescriptorAndConstants<armnn::DepthwiseConvolution2dDescriptor> verifier(
- layerName, {inputInfo}, {outputInfo}, descriptor, constants);
+ layerName, {inputInfo, kernelInfo, biasInfo}, {outputInfo}, descriptor, constants);
+ deserializedNetwork->ExecuteStrategy(verifier);
+}
+
+TEST_CASE("SerializeDepthwiseConvolution2dWeightsAndBiasesAsConstantLayers")
+{
+ const std::string layerName("depthwiseConvolution2d");
+ const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
+
+ const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32, 0.0f, 0, true);
+ const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32, 0.0f, 0, true);
+
+ std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
+ armnn::ConstTensor weights(weightsInfo, weightsData);
+
+ std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
+ armnn::ConstTensor biases(biasesInfo, biasesData);
+
+ armnn::DepthwiseConvolution2dDescriptor descriptor;
+ descriptor.m_PadLeft = 1;
+ descriptor.m_PadRight = 1;
+ descriptor.m_PadTop = 1;
+ descriptor.m_PadBottom = 1;
+ descriptor.m_StrideX = 2;
+ descriptor.m_StrideY = 2;
+ descriptor.m_DilationX = 2;
+ descriptor.m_DilationY = 2;
+ descriptor.m_BiasEnabled = true;
+ descriptor.m_DataLayout = armnn::DataLayout::NHWC;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights, "Weights");
+ armnn::IConnectableLayer* const biasesLayer = network->AddConstantLayer(biases, "Biases");
+ armnn::IConnectableLayer* const convLayer = network->AddDepthwiseConvolution2dLayer(descriptor,
+ layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
+ weightsLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(1));
+ biasesLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2));
+ convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
+ biasesLayer->GetOutputSlot(0).SetTensorInfo(biasesInfo);
+ convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ CHECK(deserializedNetwork);
+
+ const std::vector<armnn::ConstTensor>& constants {weights, biases};
+ LayerVerifierBaseWithDescriptorAndConstants<armnn::DepthwiseConvolution2dDescriptor> verifier(
+ layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor, constants);
+
deserializedNetwork->ExecuteStrategy(verifier);
}