IVGCVSW-6399 Remove deprecated code 22.02 (FullyConnected)
* Remove deprecated INetwork::AddFullyconnectedLayer() taking weights
as argument as they are now taken as separate input layers.
* Updated test that was using the deprecated function.
* Remove calls in pyarmnn
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
Change-Id: Ibc52ac7fa57afd9033eb226bbc24a09e88a7d361
diff --git a/include/armnn/INetwork.hpp b/include/armnn/INetwork.hpp
index 505edf8..173e8d5 100644
--- a/include/armnn/INetwork.hpp
+++ b/include/armnn/INetwork.hpp
@@ -392,18 +392,6 @@
IConnectableLayer* AddFullyConnectedLayer(const FullyConnectedDescriptor& fullyConnectedDescriptor,
const char* name = nullptr);
- ARMNN_DEPRECATED_MSG_REMOVAL_DATE("This AddFullyConnectedLayer overload is deprecated", "22.05")
- IConnectableLayer* AddFullyConnectedLayer(const FullyConnectedDescriptor& fullyConnectedDescriptor,
- const Optional<ConstTensor>& weights,
- const Optional<ConstTensor>& biases,
- const char* name = nullptr);
-
- ARMNN_DEPRECATED_MSG_REMOVAL_DATE("This AddFullyConnectedLayer overload is deprecated", "22.05")
- IConnectableLayer* AddFullyConnectedLayer(const FullyConnectedDescriptor& fullyConnectedDescriptor,
- const ConstTensor& weights,
- const Optional<ConstTensor>& biases,
- const char* name = nullptr);
-
/// Adds a permute layer to the network.
/// @param permuteDescriptor - PermuteDescriptor to configure the permute.
/// @param name - Optional name for the layer.
diff --git a/python/pyarmnn/src/pyarmnn/__init__.py b/python/pyarmnn/src/pyarmnn/__init__.py
index 5f95cb0..b994bb7 100644
--- a/python/pyarmnn/src/pyarmnn/__init__.py
+++ b/python/pyarmnn/src/pyarmnn/__init__.py
@@ -38,7 +38,7 @@
from ._generated.pyarmnn_deserializer import IDeserializer
except ImportError as err:
logger = logging.getLogger(__name__)
- message = "Your ArmNN library instance does not have an armnn models parser funcionality. "
+ message = "Your ArmNN library instance does not have ArmNN model (.armnn) parser functionality. "
logger.warning("%s Skipped IDeserializer import.", message)
logger.debug(str(err))
diff --git a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i
index 643f99f..eb8dede 100644
--- a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i
+++ b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i
@@ -1105,35 +1105,6 @@
%feature("docstring",
"
- Adds a Fully Connected layer to the network with input weights and optional bias.
- Also known as a Linear or Dense layer.
-
- Args:
- fullyConnectedDescriptor (FullyConnectedDescriptor): Description of the fully connected layer.
- weights (ConstTensor): Tensor for the weights data.
- biases (ConstTensor): Optional tensor for the bias data.
- name (str): Optional name for the layer.
-
- Returns:
- IConnectableLayer: Interface for configuring the layer.
- ") AddFullyConnectedLayer;
- armnn::IConnectableLayer* AddFullyConnectedLayer(const armnn::FullyConnectedDescriptor& fullyConnectedDescriptor,
- const armnn::ConstTensor& weights,
- armnn::ConstTensor* biases = nullptr,
- const char* name = nullptr) {
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- if (biases) {
- return $self->AddFullyConnectedLayer(fullyConnectedDescriptor, weights,
- armnn::Optional<armnn::ConstTensor>(*biases), name);
- } else {
- return $self->AddFullyConnectedLayer(fullyConnectedDescriptor, weights,
- armnn::Optional<armnn::ConstTensor>(), name);
- }
- ARMNN_NO_DEPRECATE_WARN_END
- }
-
- %feature("docstring",
- "
Adds a 2D Transpose Convolution layer to the network.
Args:
diff --git a/python/pyarmnn/test/test_network.py b/python/pyarmnn/test/test_network.py
index e56621a..27ad70b 100644
--- a/python/pyarmnn/test/test_network.py
+++ b/python/pyarmnn/test/test_network.py
@@ -249,35 +249,6 @@
def test_network_method_exists(method):
assert getattr(ann.INetwork, method, None)
-
-def test_fullyconnected_layer_optional_none():
- net = ann.INetwork()
- layer = net.AddFullyConnectedLayer(ann.FullyConnectedDescriptor(),
- ann.ConstTensor())
-
- assert layer
-
-
-def test_fullyconnected_layer_optional_provided():
- net = ann.INetwork()
- layer = net.AddFullyConnectedLayer(ann.FullyConnectedDescriptor(),
- ann.ConstTensor(),
- ann.ConstTensor())
-
- assert layer
-
-
-def test_fullyconnected_layer_all_args():
- net = ann.INetwork()
- layer = net.AddFullyConnectedLayer(ann.FullyConnectedDescriptor(),
- ann.ConstTensor(),
- ann.ConstTensor(),
- 'NAME1')
-
- assert layer
- assert 'NAME1' == layer.GetName()
-
-
def test_DepthwiseConvolution2d_layer_optional_none():
net = ann.INetwork()
layer = net.AddDepthwiseConvolution2dLayer(convolution2dDescriptor=ann.DepthwiseConvolution2dDescriptor(),
diff --git a/samples/CustomMemoryAllocatorSample.cpp b/samples/CustomMemoryAllocatorSample.cpp
index a1b05d4..da249e0 100644
--- a/samples/CustomMemoryAllocatorSample.cpp
+++ b/samples/CustomMemoryAllocatorSample.cpp
@@ -71,26 +71,27 @@
// Turn on logging to standard output
// This is useful in this sample so that users can learn more about what is going on
- armnn::ConfigureLogging(true, false, LogSeverity::Info);
+ ConfigureLogging(true, false, LogSeverity::Info);
// Construct ArmNN network
- armnn::NetworkId networkIdentifier;
- INetworkPtr myNetwork = INetwork::Create();
- armnn::FullyConnectedDescriptor fullyConnectedDesc;
+ NetworkId networkIdentifier;
+ INetworkPtr network = INetwork::Create();
+ FullyConnectedDescriptor fullyConnectedDesc;
float weightsData[] = {1.0f}; // Identity
TensorInfo weightsInfo(TensorShape({1, 1}), DataType::Float32, 0.0f, 0, true);
weightsInfo.SetConstant(true);
- armnn::ConstTensor weights(weightsInfo, weightsData);
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- IConnectableLayer *fullyConnected = myNetwork->AddFullyConnectedLayer(fullyConnectedDesc,
- weights,
- EmptyOptional(),
- "fully connected");
- ARMNN_NO_DEPRECATE_WARN_END
- IConnectableLayer *InputLayer = myNetwork->AddInputLayer(0);
- IConnectableLayer *OutputLayer = myNetwork->AddOutputLayer(0);
- InputLayer->GetOutputSlot(0).Connect(fullyConnected->GetInputSlot(0));
- fullyConnected->GetOutputSlot(0).Connect(OutputLayer->GetInputSlot(0));
+ ConstTensor weights(weightsInfo, weightsData);
+
+ IConnectableLayer* inputLayer = network->AddInputLayer(0);
+ IConnectableLayer* weightsLayer = network->AddConstantLayer(weights, "Weights");
+ IConnectableLayer* fullyConnectedLayer =
+ network->AddFullyConnectedLayer(fullyConnectedDesc, "fully connected");
+ IConnectableLayer* outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0));
+ weightsLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(1));
+ fullyConnectedLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+ weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
// Create ArmNN runtime:
//
@@ -111,19 +112,19 @@
//Set the tensors in the network.
TensorInfo inputTensorInfo(TensorShape({1, 1}), DataType::Float32);
- InputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
unsigned int numElements = inputTensorInfo.GetNumElements();
size_t totalBytes = numElements * sizeof(float);
TensorInfo outputTensorInfo(TensorShape({1, 1}), DataType::Float32);
- fullyConnected->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+ fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
// Optimise ArmNN network
OptimizerOptions optOptions;
optOptions.m_ImportEnabled = true;
- armnn::IOptimizedNetworkPtr optNet =
- Optimize(*myNetwork, {"GpuAcc"}, runtime->GetDeviceSpec(), optOptions);
+ IOptimizedNetworkPtr optNet =
+ Optimize(*network, {"GpuAcc"}, runtime->GetDeviceSpec(), optOptions);
if (!optNet)
{
// This shouldn't happen for this simple sample, with GpuAcc backend.
@@ -154,13 +155,13 @@
inputTensorInfo = runtime->GetInputTensorInfo(networkIdentifier, 0);
inputTensorInfo.SetConstant(true);
- armnn::InputTensors inputTensors
+ InputTensors inputTensors
{
- {0, armnn::ConstTensor(inputTensorInfo, alignedInputPtr)},
+ {0, ConstTensor(inputTensorInfo, alignedInputPtr)},
};
- armnn::OutputTensors outputTensors
+ OutputTensors outputTensors
{
- {0, armnn::Tensor(runtime->GetOutputTensorInfo(networkIdentifier, 0), alignedOutputPtr)}
+ {0, Tensor(runtime->GetOutputTensorInfo(networkIdentifier, 0), alignedOutputPtr)}
};
// Execute network
diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp
index 8ec8b42..408003e 100644
--- a/src/armnn/Network.cpp
+++ b/src/armnn/Network.cpp
@@ -171,25 +171,6 @@
return pNetworkImpl->AddFullyConnectedLayer(fullyConnectedDescriptor, name);
}
-IConnectableLayer* INetwork::AddFullyConnectedLayer(const FullyConnectedDescriptor& fullyConnectedDescriptor,
- const ConstTensor& weights,
- const Optional<ConstTensor>& biases,
- const char* name)
-{
- return pNetworkImpl->AddFullyConnectedLayer(fullyConnectedDescriptor,
- armnn::Optional<ConstTensor>(weights),
- biases,
- name);
-}
-
-IConnectableLayer* INetwork::AddFullyConnectedLayer(const FullyConnectedDescriptor& fullyConnectedDescriptor,
- const Optional<ConstTensor>& weights,
- const Optional<ConstTensor>& biases,
- const char* name)
-{
- return pNetworkImpl->AddFullyConnectedLayer(fullyConnectedDescriptor, weights, biases, name);
-}
-
IConnectableLayer* INetwork::AddPermuteLayer(const PermuteDescriptor& permuteDescriptor,
const char* name)
{
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index 632a80a..966dc6c 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -927,22 +927,21 @@
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
-
- // Old way of handling constant tensors.
- ARMNN_NO_DEPRECATE_WARN_BEGIN
+ armnn::IConnectableLayer* const weightsInputLayer = network->AddInputLayer(1);
+ armnn::IConnectableLayer* const biasInputLayer = network->AddInputLayer(2);
armnn::IConnectableLayer* const fullyConnectedLayer =
- network->AddFullyConnectedLayer(descriptor,
- weights,
- armnn::Optional<armnn::ConstTensor>(biases),
- layerName.c_str());
- ARMNN_NO_DEPRECATE_WARN_END
-
+ network->AddFullyConnectedLayer(descriptor,
+ layerName.c_str());
armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
inputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0));
+ weightsInputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(1));
+ biasInputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(2));
fullyConnectedLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ weightsInputLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
+ biasInputLayer->GetOutputSlot(0).SetTensorInfo(biasesInfo);
fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
diff --git a/src/backends/cl/test/ClCustomAllocatorTests.cpp b/src/backends/cl/test/ClCustomAllocatorTests.cpp
index c09d0b2..139e688 100644
--- a/src/backends/cl/test/ClCustomAllocatorTests.cpp
+++ b/src/backends/cl/test/ClCustomAllocatorTests.cpp
@@ -40,7 +40,6 @@
}
size_t space = size + alignment + alignment;
auto allocatedMemPtr = std::malloc(space * sizeof(size_t));
-
if (std::align(alignment, size, allocatedMemPtr, space) == nullptr)
{
throw armnn::Exception("SampleClBackendCustomAllocator::Alignment failed");
@@ -63,7 +62,6 @@
armnn::INetworkPtr CreateTestNetwork(armnn::TensorInfo& inputTensorInfo)
{
using namespace armnn;
- INetworkPtr myNetwork = INetwork::Create();
armnn::FullyConnectedDescriptor fullyConnectedDesc;
float weightsData[] = {1.0f}; // Identity
@@ -71,25 +69,27 @@
weightsInfo.SetConstant(true);
armnn::ConstTensor weights(weightsInfo, weightsData);
- ARMNN_NO_DEPRECATE_WARN_BEGIN
- IConnectableLayer* fullyConnected = myNetwork->AddFullyConnectedLayer(fullyConnectedDesc,
- weights,
- EmptyOptional(),
- "fully connected");
- ARMNN_NO_DEPRECATE_WARN_END
- IConnectableLayer* InputLayer = myNetwork->AddInputLayer(0);
- IConnectableLayer* OutputLayer = myNetwork->AddOutputLayer(0);
- InputLayer->GetOutputSlot(0).Connect(fullyConnected->GetInputSlot(0));
- fullyConnected->GetOutputSlot(0).Connect(OutputLayer->GetInputSlot(0));
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights, "Weights");
+ armnn::IConnectableLayer* const fullyConnectedLayer =
+ network->AddFullyConnectedLayer(fullyConnectedDesc, "fully connected");
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0));
+ weightsLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(1));
+ fullyConnectedLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
//Set the tensors in the network.
- InputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
TensorInfo outputTensorInfo(TensorShape({1, 1}), DataType::Float32);
- fullyConnected->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+ fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
- return myNetwork;
+ return network;
}
TEST_SUITE("ClCustomAllocatorTests")
@@ -216,4 +216,4 @@
"Expected exception in RuntimeImpl::RuntimeImpl() as allocator was nullptr.");
}
-} // test suite ClCustomAllocatorTests
\ No newline at end of file
+} // test suite ClCustomAllocatorTests
