IVGCVSW-7006 Remove deprecated code due to be removed in 22.08
* AddConv and AddDWConv with weights and bias
* ResizeBilinearDescriptor
* b,blacklist option in accuracy tool
!android-nn-driver:8172
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ibbc04fd18be7f938b11590bf67cd7af103cb4d99
diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp
index c4869fa..3508ee8 100644
--- a/src/armnn/Network.cpp
+++ b/src/armnn/Network.cpp
@@ -88,19 +88,6 @@
return pNetworkImpl->AddConvolution2dLayer(convolution2dDescriptor, name);
}
-ARMNN_NO_DEPRECATE_WARN_BEGIN
-IConnectableLayer* INetwork::AddConvolution2dLayer(const Convolution2dDescriptor& convolution2dDescriptor,
- const ConstTensor& weights,
- const Optional<ConstTensor>& biases,
- const char* name)
-{
- return pNetworkImpl->AddConvolution2dLayer(convolution2dDescriptor,
- weights,
- armnn::Optional<ConstTensor>(biases),
- name);
-}
-ARMNN_NO_DEPRECATE_WARN_END
-
IConnectableLayer* INetwork::AddConvolution3dLayer(const Convolution3dDescriptor& convolution3dDescriptor,
const char* name)
{
@@ -123,18 +110,6 @@
}
-ARMNN_NO_DEPRECATE_WARN_BEGIN
-IConnectableLayer* INetwork::AddDepthwiseConvolution2dLayer(
- const DepthwiseConvolution2dDescriptor& convolution2dDescriptor,
- const ConstTensor& weights,
- const Optional<ConstTensor>& biases,
- const char* name)
-{
- return pNetworkImpl->AddDepthwiseConvolution2dLayer(convolution2dDescriptor, weights, biases, name);
-}
-ARMNN_NO_DEPRECATE_WARN_END
-
-
IConnectableLayer* INetwork::AddDequantizeLayer(const char* name)
{
return pNetworkImpl->AddDequantizeLayer(name);
diff --git a/src/armnn/layers/Convolution2dLayer.hpp b/src/armnn/layers/Convolution2dLayer.hpp
index 5799970..185a672 100644
--- a/src/armnn/layers/Convolution2dLayer.hpp
+++ b/src/armnn/layers/Convolution2dLayer.hpp
@@ -44,7 +44,6 @@
/// @return A vector to the inferred output shape.
std::vector<TensorShape> InferOutputShapes(const std::vector<TensorShape>& inputShapes) const override;
-
void ExecuteStrategy(IStrategy& strategy) const override;
void SerializeLayerParameters(ParameterStringifyFunction& fn) const override;
diff --git a/src/armnn/test/GraphTests.cpp b/src/armnn/test/GraphTests.cpp
index 95421c5..eea7ae8 100644
--- a/src/armnn/test/GraphTests.cpp
+++ b/src/armnn/test/GraphTests.cpp
@@ -632,13 +632,13 @@
TensorInfo weightsInfo = constInfo;
ConstTensor weights(weightsInfo, weightData);
DepthwiseConvolution2dDescriptor desc;
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- // GetConstantTensorsByRef() returns {m_Weights, m_Bias} so we need to use the old AddDepthwiseConvolution2dLayer()
- const auto depthwiseLayer = net->AddDepthwiseConvolution2dLayer(desc, weights, EmptyOptional(), "Depthwise");
- ARMNN_NO_DEPRECATE_WARN_END
- const void* resultData = depthwiseLayer->GetConstantTensorsByRef()[0].get()->GetConstTensor<void>();
- auto resultValue = reinterpret_cast<const uint8_t*>(resultData);
- CHECK(resultValue[0] == 3);
+
+ const auto weightsLayer = net->AddConstantLayer(weights);
+
+ const void* resultDataWeights = weightsLayer->GetConstantTensorsByRef()[0].get()->GetConstTensor<void>();
+ auto resultValueWeights = reinterpret_cast<const uint8_t*>(resultDataWeights);
+ CHECK(resultValueWeights[0] == 3);
+
}
}
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index a568bf1..3573a81 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -436,19 +436,19 @@
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- armnn::IConnectableLayer* const convLayer =
- network->AddConvolution2dLayer(descriptor,
- weights,
- armnn::Optional<armnn::ConstTensor>(biases),
- layerName.c_str());
- ARMNN_NO_DEPRECATE_WARN_END
+ armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights, "weights");
+ armnn::IConnectableLayer* const biasLayer = network->AddConstantLayer(biases, "bias");
+ armnn::IConnectableLayer* const convLayer = network->AddConvolution2dLayer(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));
+ biasLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2));
convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
+ biasLayer->GetOutputSlot(0).SetTensorInfo(biasesInfo);
convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
@@ -458,7 +458,7 @@
deserializedNetwork->ExecuteStrategy(verifier);
}
-TEST_CASE("SerializeConvolution2dWithPerAxisParamsTestDeprecatedMethod")
+TEST_CASE("SerializeConvolution2dWithPerAxisParams")
{
using namespace armnn;
@@ -491,19 +491,19 @@
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- armnn::IConnectableLayer* const convLayer =
- network->AddConvolution2dLayer(descriptor,
- weights,
- armnn::Optional<armnn::ConstTensor>(biases),
- layerName.c_str());
- ARMNN_NO_DEPRECATE_WARN_END
+ armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights, "weights");
+ armnn::IConnectableLayer* const biasLayer = network->AddConstantLayer(weights, "bias");
+ armnn::IConnectableLayer* const convLayer = network->AddConvolution2dLayer(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));
+ biasLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2));
convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ weightsLayer->GetOutputSlot(0).SetTensorInfo(kernelInfo);
+ biasLayer->GetOutputSlot(0).SetTensorInfo(biasInfo);
convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp
index f4afbd9..753fe06 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -1596,54 +1596,6 @@
ValidateTensorDataTypesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output");
}
-
-void ResizeBilinearQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
-{
- const std::string descriptorName{"ResizeBilinearQueueDescriptor"};
-
- ValidateNumInputs(workloadInfo, descriptorName, 1);
- ValidateNumOutputs(workloadInfo, descriptorName, 1);
-
- const TensorInfo& inputTensorInfo = workloadInfo.m_InputTensorInfos[0];
- const TensorInfo& outputTensorInfo = workloadInfo.m_OutputTensorInfos[0];
-
- ValidateTensorNumDimensions(inputTensorInfo, descriptorName, 4, "input");
- ValidateTensorNumDimensions(outputTensorInfo, descriptorName, 4, "output");
-
- std::vector<DataType> supportedTypes =
- {
- DataType::BFloat16,
- DataType::Float16,
- DataType::Float32,
- DataType::QAsymmS8,
- DataType::QAsymmU8,
- DataType::QSymmS16
- };
-
- ValidateDataTypes(inputTensorInfo, supportedTypes, descriptorName);
- ValidateTensorDataTypesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output");
-
- // ResizeBilinear only changes width and height: batch and channel count must match.
- const unsigned int inputBatchSize = inputTensorInfo.GetShape()[0];
- const unsigned int outputBatchSize = outputTensorInfo.GetShape()[0];
- if (inputBatchSize != outputBatchSize)
- {
- throw InvalidArgumentException(
- fmt::format("{}: Input batch size ({}) does not match output batch size ({})",
- descriptorName, inputBatchSize, outputBatchSize));
- }
-
- DataLayoutIndexed dimensionIndices(m_Parameters.m_DataLayout);
- const unsigned int inputChannelCount = inputTensorInfo.GetShape()[dimensionIndices.GetChannelsIndex()];
- const unsigned int outputChannelCount = outputTensorInfo.GetShape()[dimensionIndices.GetChannelsIndex()];
- if (inputChannelCount != outputChannelCount)
- {
- throw InvalidArgumentException(
- fmt::format("{}: Input channel count ({}) does not match output channel count ({})",
- descriptorName, inputChannelCount, outputChannelCount));
- }
-}
-
void ResizeQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const
{
const std::string descriptorName{"ResizeQueueDescriptor"};