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authorJames Conroy <james.conroy@arm.com>2021-04-27 17:13:27 +0100
committerNarumol Prangnawarat <narumol.prangnawarat@arm.com>2021-05-06 14:40:40 +0000
commit1f58f03d82c482626b1b4673b6c0e25da4338fb5 (patch)
treee92451e00d459a2fc0d870694460f482aa4c77ae /src/backends/backendsCommon/test
parenta7a12f5c3654da554ad6197beff0f0fc54681c92 (diff)
downloadarmnn-1f58f03d82c482626b1b4673b6c0e25da4338fb5.tar.gz
IVGCVSW-5815 Generalise ConstCpuTensorHandle
* Generalises ConstCpuTensorHandle and inherited classes by removing 'Cpu' from aliases. * New renamed classes: ConstTensorHandle, TensorHandle, ScopedTensorHandle, PassthroughTensorHandle, ConstPassthroughTensorHandle. Signed-off-by: James Conroy <james.conroy@arm.com> Change-Id: I1824e0e134202735fb77051f20a7252f161dfe16
Diffstat (limited to 'src/backends/backendsCommon/test')
-rw-r--r--src/backends/backendsCommon/test/CommonTestUtils.hpp6
-rw-r--r--src/backends/backendsCommon/test/DefaultAsyncExecuteTest.cpp30
-rw-r--r--src/backends/backendsCommon/test/DynamicBackendTests.hpp4
-rw-r--r--src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp106
-rw-r--r--src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp22
-rw-r--r--src/backends/backendsCommon/test/WorkloadDataValidation.cpp58
-rw-r--r--src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp26
-rw-r--r--src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp4
-rw-r--r--src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp46
-rw-r--r--src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp4
-rw-r--r--src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp4
-rw-r--r--src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp6
-rw-r--r--src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp2
-rw-r--r--src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp2
-rw-r--r--src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp244
-rw-r--r--src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp6
-rw-r--r--src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp2
-rw-r--r--src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp12
18 files changed, 292 insertions, 292 deletions
diff --git a/src/backends/backendsCommon/test/CommonTestUtils.hpp b/src/backends/backendsCommon/test/CommonTestUtils.hpp
index 8c4da621ed..99412b9694 100644
--- a/src/backends/backendsCommon/test/CommonTestUtils.hpp
+++ b/src/backends/backendsCommon/test/CommonTestUtils.hpp
@@ -13,7 +13,7 @@
#include <armnn/BackendRegistry.hpp>
#include <armnn/Types.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <test/TestUtils.hpp>
@@ -72,8 +72,8 @@ bool Compare(T a, T b, float tolerance = 0.000001f)
template <typename ConvolutionLayer>
void SetWeightAndBias(ConvolutionLayer* layer, const armnn::TensorInfo& weightInfo, const armnn::TensorInfo& biasInfo)
{
- layer->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weightInfo);
- layer->m_Bias = std::make_unique<armnn::ScopedCpuTensorHandle>(biasInfo);
+ layer->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weightInfo);
+ layer->m_Bias = std::make_unique<armnn::ScopedTensorHandle>(biasInfo);
layer->m_Weight->Allocate();
layer->m_Bias->Allocate();
diff --git a/src/backends/backendsCommon/test/DefaultAsyncExecuteTest.cpp b/src/backends/backendsCommon/test/DefaultAsyncExecuteTest.cpp
index 56a794e77c..2dd5298059 100644
--- a/src/backends/backendsCommon/test/DefaultAsyncExecuteTest.cpp
+++ b/src/backends/backendsCommon/test/DefaultAsyncExecuteTest.cpp
@@ -5,7 +5,7 @@
#include <armnn/Exceptions.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/Workload.hpp>
#include <boost/test/unit_test.hpp>
@@ -121,15 +121,15 @@ BOOST_AUTO_TEST_CASE(TestAsyncExecute)
ConstTensor constInputTensor(info, inVals);
ConstTensor constOutputTensor(info, outVals);
- ScopedCpuTensorHandle syncInput0(constInputTensor);
- ScopedCpuTensorHandle syncOutput0(constOutputTensor);
+ ScopedTensorHandle syncInput0(constInputTensor);
+ ScopedTensorHandle syncOutput0(constOutputTensor);
std::unique_ptr<Workload0> workload0 = CreateWorkload<Workload0>(info, &syncInput0, &syncOutput0);
workload0.get()->Execute();
- ScopedCpuTensorHandle asyncInput0(constInputTensor);
- ScopedCpuTensorHandle asyncOutput0(constOutputTensor);
+ ScopedTensorHandle asyncInput0(constInputTensor);
+ ScopedTensorHandle asyncOutput0(constOutputTensor);
WorkingMemDescriptor workingMemDescriptor0;
workingMemDescriptor0.m_Inputs = std::vector<ITensorHandle*>{&asyncInput0};
@@ -159,13 +159,13 @@ BOOST_AUTO_TEST_CASE(TestDefaultAsyncExecute)
ConstTensor constOutputTensor(info, outVals);
ConstTensor defaultTensor(info, &defaultVals);
- ScopedCpuTensorHandle defaultInput = ScopedCpuTensorHandle(defaultTensor);
- ScopedCpuTensorHandle defaultOutput = ScopedCpuTensorHandle(defaultTensor);
+ ScopedTensorHandle defaultInput = ScopedTensorHandle(defaultTensor);
+ ScopedTensorHandle defaultOutput = ScopedTensorHandle(defaultTensor);
std::unique_ptr<Workload1> workload1 = CreateWorkload<Workload1>(info, &defaultInput, &defaultOutput);
- ScopedCpuTensorHandle asyncInput(constInputTensor);
- ScopedCpuTensorHandle asyncOutput(constOutputTensor);
+ ScopedTensorHandle asyncInput(constInputTensor);
+ ScopedTensorHandle asyncOutput(constOutputTensor);
WorkingMemDescriptor workingMemDescriptor;
workingMemDescriptor.m_Inputs = std::vector<ITensorHandle*>{&asyncInput};
@@ -202,20 +202,20 @@ BOOST_AUTO_TEST_CASE(TestDefaultAsyncExeuteWithThreads)
ConstTensor defaultTensor(info, &defaultVals);
- ScopedCpuTensorHandle defaultInput = ScopedCpuTensorHandle(defaultTensor);
- ScopedCpuTensorHandle defaultOutput = ScopedCpuTensorHandle(defaultTensor);
+ ScopedTensorHandle defaultInput = ScopedTensorHandle(defaultTensor);
+ ScopedTensorHandle defaultOutput = ScopedTensorHandle(defaultTensor);
std::unique_ptr<Workload1> workload = CreateWorkload<Workload1>(info, &defaultInput, &defaultOutput);
- ScopedCpuTensorHandle asyncInput1(constInputTensor1);
- ScopedCpuTensorHandle asyncOutput1(constOutputTensor1);
+ ScopedTensorHandle asyncInput1(constInputTensor1);
+ ScopedTensorHandle asyncOutput1(constOutputTensor1);
WorkingMemDescriptor workingMemDescriptor1;
workingMemDescriptor1.m_Inputs = std::vector<ITensorHandle*>{&asyncInput1};
workingMemDescriptor1.m_Outputs = std::vector<ITensorHandle*>{&asyncOutput1};
- ScopedCpuTensorHandle asyncInput2(constInputTensor2);
- ScopedCpuTensorHandle asyncOutput2(constOutputTensor2);
+ ScopedTensorHandle asyncInput2(constInputTensor2);
+ ScopedTensorHandle asyncOutput2(constOutputTensor2);
WorkingMemDescriptor workingMemDescriptor2;
workingMemDescriptor2.m_Inputs = std::vector<ITensorHandle*>{&asyncInput2};
diff --git a/src/backends/backendsCommon/test/DynamicBackendTests.hpp b/src/backends/backendsCommon/test/DynamicBackendTests.hpp
index 8302bfd57d..a4f1613a58 100644
--- a/src/backends/backendsCommon/test/DynamicBackendTests.hpp
+++ b/src/backends/backendsCommon/test/DynamicBackendTests.hpp
@@ -9,8 +9,8 @@
#include <armnn/backends/DynamicBackend.hpp>
#include <armnn/backends/ILayerSupport.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
#include <backendsCommon/DynamicBackendUtils.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <Filesystem.hpp>
#include <reference/workloads/RefConvolution2dWorkload.hpp>
#include <Runtime.hpp>
@@ -1473,7 +1473,7 @@ void CreateReferenceDynamicBackendTestImpl()
{ outputInfo }
};
convolution2dQueueDescriptor.m_Inputs.push_back(nullptr);
- auto weights = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
+ auto weights = std::make_unique<ScopedTensorHandle>(weightInfo);
convolution2dQueueDescriptor.m_Weight = weights.get();
// Create a convolution workload with the dummy settings
diff --git a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
index b73efbe26c..4240bb1061 100644
--- a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
+++ b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp
@@ -83,13 +83,13 @@ struct DummyLayer<armnn::BatchNormalizationLayer>
DummyLayer()
{
m_Layer = dummyGraph.AddLayer<armnn::BatchNormalizationLayer>(armnn::BatchNormalizationDescriptor(), "");
- m_Layer->m_Mean = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_Mean = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_Variance = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_Variance = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_Beta = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_Beta = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_Gamma = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_Gamma = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
}
@@ -240,9 +240,9 @@ struct DummyConvolutionLayer
desc.m_StrideX = 1;
desc.m_StrideY = 1;
m_Layer = dummyGraph.AddLayer<ConvolutionLayerType>(desc, "");
- m_Layer->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_Bias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_Bias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
}
@@ -278,7 +278,7 @@ struct DummyLayer<armnn::DetectionPostProcessLayer>
DummyLayer()
{
m_Layer = dummyGraph.AddLayer<armnn::DetectionPostProcessLayer>(armnn::DetectionPostProcessDescriptor(), "");
- m_Layer->m_Anchors = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_Anchors = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
}
@@ -299,30 +299,30 @@ struct DummyLstmLayer
desc.m_CifgEnabled = false;
m_Layer = dummyGraph.AddLayer<LstmLayerType>(armnn::LstmDescriptor(), "");
- m_Layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_BasicParameters.m_CellBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_CellBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_BasicParameters.m_OutputGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_OutputGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_CifgParameters.m_InputToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_CifgParameters.m_InputToInputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_CifgParameters.m_RecurrentToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_CifgParameters.m_RecurrentToInputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
- m_Layer->m_CifgParameters.m_InputGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_CifgParameters.m_InputGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
}
@@ -354,57 +354,57 @@ struct DummyQLstmLayer
m_Layer = dummyGraph.AddLayer<QLstmLayerType>(armnn::QLstmDescriptor(), "qLstm");
// Basic params
- m_Layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
- m_Layer->m_BasicParameters.m_CellBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_CellBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
- m_Layer->m_BasicParameters.m_OutputGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_BasicParameters.m_OutputGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
// CIFG optional params
- m_Layer->m_CifgParameters.m_InputToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_CifgParameters.m_InputToInputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_CifgParameters.m_RecurrentToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_CifgParameters.m_RecurrentToInputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_CifgParameters.m_InputGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_CifgParameters.m_InputGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
// Projection optional params
- m_Layer->m_ProjectionParameters.m_ProjectionWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_ProjectionParameters.m_ProjectionWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS8));
- m_Layer->m_ProjectionParameters.m_ProjectionBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_ProjectionParameters.m_ProjectionBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
// Peephole optional params
- m_Layer->m_PeepholeParameters.m_CellToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_PeepholeParameters.m_CellToInputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS16));
- m_Layer->m_PeepholeParameters.m_CellToForgetWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_PeepholeParameters.m_CellToForgetWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS16));
- m_Layer->m_PeepholeParameters.m_CellToOutputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_PeepholeParameters.m_CellToOutputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS16));
// Layer normalization optional params
- m_Layer->m_LayerNormParameters.m_InputLayerNormWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_LayerNormParameters.m_InputLayerNormWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS16));
- m_Layer->m_LayerNormParameters.m_ForgetLayerNormWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_LayerNormParameters.m_ForgetLayerNormWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS16));
- m_Layer->m_LayerNormParameters.m_CellLayerNormWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_LayerNormParameters.m_CellLayerNormWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS16));
- m_Layer->m_LayerNormParameters.m_OutputLayerNormWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_LayerNormParameters.m_OutputLayerNormWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QSymmS16));
}
@@ -423,31 +423,31 @@ struct DummyLayer<armnn::QuantizedLstmLayer, void>
{
m_Layer = dummyGraph.AddLayer<armnn::QuantizedLstmLayer>("");
- m_Layer->m_QuantizedLstmParameters.m_InputToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_InputToInputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QAsymmU8));
- m_Layer->m_QuantizedLstmParameters.m_InputToForgetWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_InputToForgetWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QAsymmU8));
- m_Layer->m_QuantizedLstmParameters.m_InputToCellWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_InputToCellWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QAsymmU8));
- m_Layer->m_QuantizedLstmParameters.m_InputToOutputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_InputToOutputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QAsymmU8));
- m_Layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QAsymmU8));
- m_Layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QAsymmU8));
- m_Layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QAsymmU8));
- m_Layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::QAsymmU8));
- m_Layer->m_QuantizedLstmParameters.m_InputGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_InputGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
- m_Layer->m_QuantizedLstmParameters.m_ForgetGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_ForgetGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
- m_Layer->m_QuantizedLstmParameters.m_CellBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_CellBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
- m_Layer->m_QuantizedLstmParameters.m_OutputGateBias = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_QuantizedLstmParameters.m_OutputGateBias = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Signed32));
}
@@ -466,7 +466,7 @@ struct DummyLayer<armnn::FullyConnectedLayer>
{
armnn::FullyConnectedLayer::DescriptorType desc;
m_Layer = dummyGraph.AddLayer<armnn::FullyConnectedLayer>(desc, "");
- m_Layer->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(
+ m_Layer->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(
armnn::TensorInfo(armnn::TensorShape({1,1,1,1}), armnn::DataType::Float32));
}
diff --git a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
index 817cdeed79..0ca4b0a7f9 100644
--- a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
+++ b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
@@ -7,7 +7,7 @@
#include <Graph.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/WorkloadData.hpp>
#include <boost/test/unit_test.hpp>
@@ -35,10 +35,10 @@ BOOST_AUTO_TEST_CASE(ReleaseBatchNormalizationLayerConstantDataTest)
BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer");
armnn::TensorInfo weightInfo({3}, armnn::DataType::Float32);
- layer->m_Mean = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
- layer->m_Variance = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
- layer->m_Beta = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
- layer->m_Gamma = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
+ layer->m_Mean = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Variance = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Beta = std::make_unique<ScopedTensorHandle>(weightInfo);
+ layer->m_Gamma = std::make_unique<ScopedTensorHandle>(weightInfo);
layer->m_Mean->Allocate();
layer->m_Variance->Allocate();
layer->m_Beta->Allocate();
@@ -87,9 +87,9 @@ BOOST_AUTO_TEST_CASE(ReleaseBatchNormalizationLayerConstantDataTest)
Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
- layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({2, 3, 5, 3},
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({2, 3, 5, 3},
armnn::DataType::Float32));
- layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>
+ layer->m_Bias = std::make_unique<ScopedTensorHandle>
(TensorInfo({2}, GetBiasDataType(armnn::DataType::Float32)));
layer->m_Weight->Allocate();
@@ -131,8 +131,8 @@ BOOST_AUTO_TEST_CASE(ReleaseDepthwiseConvolution2dLayerConstantDataTest)
DepthwiseConvolution2dLayer* const layer = graph.AddLayer<DepthwiseConvolution2dLayer>(layerDesc, "layer");
- layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({3, 3, 5, 3}, DataType::Float32));
- layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({9}, DataType::Float32));
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({3, 3, 5, 3}, DataType::Float32));
+ layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({9}, DataType::Float32));
layer->m_Weight->Allocate();
layer->m_Bias->Allocate();
@@ -170,9 +170,9 @@ BOOST_AUTO_TEST_CASE(ReleaseFullyConnectedLayerConstantDataTest)
float inputsQScale = 1.0f;
float outputQScale = 2.0f;
- layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({7, 20},
+ layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({7, 20},
DataType::QAsymmU8, inputsQScale, 0));
- layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({7},
+ layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({7},
GetBiasDataType(DataType::QAsymmU8), inputsQScale));
layer->m_Weight->Allocate();
layer->m_Bias->Allocate();
diff --git a/src/backends/backendsCommon/test/WorkloadDataValidation.cpp b/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
index 5ac548f42a..182c913777 100644
--- a/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
+++ b/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
@@ -7,7 +7,7 @@
#include <armnn/Exceptions.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/Workload.hpp>
#include <reference/workloads/RefWorkloads.hpp>
@@ -32,7 +32,7 @@ BOOST_AUTO_TEST_CASE(BatchNormalizationQueueDescriptor_Validate_DifferentQuantiz
unsigned int sameShape[] = { 10 };
TensorInfo sameInfo = armnn::TensorInfo(1, sameShape, armnn::DataType::QAsymmU8);
- ScopedCpuTensorHandle sameTensor(sameInfo);
+ ScopedTensorHandle sameTensor(sameInfo);
AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
@@ -136,8 +136,8 @@ BOOST_AUTO_TEST_CASE(FullyConnectedQueueDescriptor_Validate_RequiredDataMissing)
FullyConnectedQueueDescriptor invalidData;
WorkloadInfo invalidInfo;
- ScopedCpuTensorHandle weightTensor(weightsDesc);
- ScopedCpuTensorHandle biasTensor(biasesDesc);
+ ScopedTensorHandle weightTensor(weightsDesc);
+ ScopedTensorHandle biasTensor(biasesDesc);
AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
@@ -515,27 +515,27 @@ BOOST_AUTO_TEST_CASE(LstmQueueDescriptor_Validate)
AddOutputToWorkload(data, info, cellStateOutTensorInfo, nullptr);
// AddOutputToWorkload(data, info, outputTensorInfo, nullptr); is left out
- armnn::ScopedCpuTensorHandle inputToInputWeightsTensor(tensorInfo4x5);
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(tensorInfo4x5);
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(tensorInfo4x5);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(tensorInfo4x5);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(tensorInfo4x3);
- armnn::ScopedCpuTensorHandle recurrentToInputWeightsTensor(tensorInfo4x3);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(tensorInfo4x3);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(tensorInfo4x3);
- armnn::ScopedCpuTensorHandle cellToInputWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle inputGateBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellToForgetWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellToOutputWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle projectionWeightsTensor(tensorInfo3x4);
- armnn::ScopedCpuTensorHandle projectionBiasTensor(tensorInfo3);
- armnn::ScopedCpuTensorHandle inputLayerNormWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle forgetLayerNormWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellLayerNormWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle outputLayerNormWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle inputToInputWeightsTensor(tensorInfo4x5);
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(tensorInfo4x5);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(tensorInfo4x5);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(tensorInfo4x5);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(tensorInfo4x3);
+ armnn::ScopedTensorHandle recurrentToInputWeightsTensor(tensorInfo4x3);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(tensorInfo4x3);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(tensorInfo4x3);
+ armnn::ScopedTensorHandle cellToInputWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle inputGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle outputGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellToForgetWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellToOutputWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle projectionWeightsTensor(tensorInfo3x4);
+ armnn::ScopedTensorHandle projectionBiasTensor(tensorInfo3);
+ armnn::ScopedTensorHandle inputLayerNormWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle forgetLayerNormWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellLayerNormWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle outputLayerNormWeightsTensor(tensorInfo4);
data.m_InputToInputWeights = &inputToInputWeightsTensor;
data.m_InputToForgetWeights = &inputToForgetWeightsTensor;
@@ -657,14 +657,14 @@ BOOST_AUTO_TEST_CASE(BiasPerAxisQuantization_Validate)
AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, nullptr);
AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, nullptr);
- ScopedCpuTensorHandle weightTensor(weightInfo);
+ ScopedTensorHandle weightTensor(weightInfo);
queueDescriptor.m_Weight = &weightTensor;
// Test 1: correct per-axis quantization values
const std::vector<float> biasPerAxisScales1 = { 3.75f, 5.25f };
const TensorInfo biasInfo1(biasShape, biasType, biasPerAxisScales1, 0);
- ScopedCpuTensorHandle biasHandle1(biasInfo1);
+ ScopedTensorHandle biasHandle1(biasInfo1);
queueDescriptor.m_Bias = &biasHandle1;
BOOST_CHECK_NO_THROW(queueDescriptor.Validate(workloadInfo));
@@ -673,7 +673,7 @@ BOOST_AUTO_TEST_CASE(BiasPerAxisQuantization_Validate)
const std::vector<float> biasPerAxisScales2 = { 4.00f, 5.00f };
const TensorInfo biasInfo2(biasShape, biasType, biasPerAxisScales2, 0);
- ScopedCpuTensorHandle biasHandle2(biasInfo2);
+ ScopedTensorHandle biasHandle2(biasInfo2);
queueDescriptor.m_Bias = &biasHandle2;
BOOST_CHECK_NO_THROW(queueDescriptor.Validate(workloadInfo));
@@ -682,7 +682,7 @@ BOOST_AUTO_TEST_CASE(BiasPerAxisQuantization_Validate)
const std::vector<float> biasPerAxisScales3 = { 3.75f, 5.25f, 5.25f };
const TensorInfo biasInfo3(biasShape, biasType, biasPerAxisScales3, 0);
- ScopedCpuTensorHandle biasHandle3(biasInfo3);
+ ScopedTensorHandle biasHandle3(biasInfo3);
queueDescriptor.m_Bias = &biasHandle3;
BOOST_CHECK_THROW(queueDescriptor.Validate(workloadInfo), InvalidArgumentException);
diff --git a/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp
index eb4f461eb9..969d5dbcd1 100644
--- a/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/BatchNormalizationTestImpl.cpp
@@ -11,7 +11,7 @@
#include <armnn/utility/IgnoreUnused.hpp>
#include <armnnUtils/DataLayoutIndexed.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
#include <reference/test/RefWorkloadFactoryHelper.hpp>
@@ -74,10 +74,10 @@ LayerTestResult<T, 4> BatchNormTestImpl(
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
- armnn::ScopedCpuTensorHandle meanTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle betaTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo);
+ armnn::ScopedTensorHandle meanTensor(tensorInfo);
+ armnn::ScopedTensorHandle varianceTensor(tensorInfo);
+ armnn::ScopedTensorHandle betaTensor(tensorInfo);
+ armnn::ScopedTensorHandle gammaTensor(tensorInfo);
armnn::BatchNormalizationQueueDescriptor descriptor;
descriptor.m_Mean = &meanTensor;
@@ -160,10 +160,10 @@ LayerTestResult<T,4> BatchNormTestNhwcImpl(
armnn::BatchNormalizationQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle meanTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle betaTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo);
+ armnn::ScopedTensorHandle meanTensor(tensorInfo);
+ armnn::ScopedTensorHandle varianceTensor(tensorInfo);
+ armnn::ScopedTensorHandle betaTensor(tensorInfo);
+ armnn::ScopedTensorHandle gammaTensor(tensorInfo);
AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]);
AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]);
@@ -644,10 +644,10 @@ LayerTestResult<float,4> CompareBatchNormTest(
armnn::BatchNormalizationQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle meanTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle betaTensor(tensorInfo);
- armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo);
+ armnn::ScopedTensorHandle meanTensor(tensorInfo);
+ armnn::ScopedTensorHandle varianceTensor(tensorInfo);
+ armnn::ScopedTensorHandle betaTensor(tensorInfo);
+ armnn::ScopedTensorHandle gammaTensor(tensorInfo);
AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]);
AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]);
diff --git a/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp
index 45c94d345b..c28ef40b45 100644
--- a/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp
@@ -11,7 +11,7 @@
#include <armnnUtils/Permute.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadTestUtils.hpp>
@@ -101,7 +101,7 @@ LayerTestResult<T, 4> ConstantTestImpl(
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
- armnn::ScopedCpuTensorHandle constantTensor(inputTensorInfo);
+ armnn::ScopedTensorHandle constantTensor(inputTensorInfo);
AllocateAndCopyDataToITensorHandle(&constantTensor, &input[0][0][0][0]);
armnn::ConstantQueueDescriptor descriptor;
diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
index 4641e67aad..8f60415a66 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
@@ -13,7 +13,7 @@
#include <armnnUtils/DataLayoutIndexed.hpp>
#include <armnnUtils/Permute.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/test/DataLayoutUtils.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
@@ -318,8 +318,8 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
armnn::Convolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
// Permute the kernel if necessary
boost::multi_array<T, 4> kernel = boost::multi_array<T, 4>(originalKernel);
if (layout == armnn::DataLayout::NHWC)
@@ -423,10 +423,10 @@ LayerTestResult<O, 4> SimpleConvolution2dNhwcTestImpl(
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
- armnn::ScopedCpuTensorHandle weightsTensor(kernelDesc);
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
AllocateAndCopyDataToITensorHandle(&weightsTensor, &kernel[0][0][0][0]);
- armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
armnn::Convolution2dQueueDescriptor data;
@@ -547,8 +547,8 @@ LayerTestResult<T,4> Convolution1dTestImpl(
armnn::Convolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(kernelInfo);
- armnn::ScopedCpuTensorHandle biasTensor(biasInfo);
+ armnn::ScopedTensorHandle weightsTensor(kernelInfo);
+ armnn::ScopedTensorHandle biasTensor(biasInfo);
AllocateAndCopyDataToITensorHandle(&weightsTensor, kernelData.data());
AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data());
@@ -1349,8 +1349,8 @@ LayerTestResult<T,4> CompareConvolution2dTestImpl(
armnn::Convolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
AllocateAndCopyDataToITensorHandle(&weightsTensor, &kernel[0][0][0][0]);
AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
@@ -1722,11 +1722,11 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
- armnn::ScopedCpuTensorHandle weightsTensor(kernelDesc);
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
AllocateAndCopyDataToITensorHandle(&weightsTensor, &kernel[0][0][0][0]);
- armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
if (biasEnabled)
{
AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
@@ -1882,8 +1882,8 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl(
armnn::DepthwiseConvolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
AllocateAndCopyDataToITensorHandle(&weightsTensor, &kernel[0][0][0][0]);
AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
@@ -2095,8 +2095,8 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
armnn::DepthwiseConvolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
AllocateAndCopyDataToITensorHandle(&weightsTensor, &kernel[0][0][0][0]);
AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
@@ -2252,8 +2252,8 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
armnn::DepthwiseConvolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
boost::multi_array<T, 4> kernel = boost::multi_array<T, 4>(originalKernel);
AllocateAndCopyDataToITensorHandle(&weightsTensor, &kernel[0][0][0][0]);
@@ -3007,8 +3007,8 @@ LayerTestResult<T, 4> CompareDepthwiseConvolution2dTestImpl(
armnn::DepthwiseConvolution2dQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(kernelDesc);
- armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
+ armnn::ScopedTensorHandle weightsTensor(kernelDesc);
+ armnn::ScopedTensorHandle biasTensor(biasDesc);
AllocateAndCopyDataToITensorHandle(&weightsTensor, &kernel[0][0][0][0]);
AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
@@ -3502,8 +3502,8 @@ LayerTestResult<uint8_t, 4> Convolution2dPerAxisQuantTest(
WorkloadInfo workloadInfo;
- ScopedCpuTensorHandle weightTensor(kernelInfo);
- ScopedCpuTensorHandle biasTensor(biasInfo);
+ ScopedTensorHandle weightTensor(kernelInfo);
+ ScopedTensorHandle biasTensor(biasInfo);
AllocateAndCopyDataToITensorHandle(&weightTensor, kernelData.data());
AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data());
@@ -3756,8 +3756,8 @@ LayerTestResult<uint8_t, 4> DepthwiseConvolution2dPerAxisQuantTest(
std::unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo);
WorkloadInfo workloadInfo;
- ScopedCpuTensorHandle weightTensor(kernelInfo);
- ScopedCpuTensorHandle biasTensor(biasInfo);
+ ScopedTensorHandle weightTensor(kernelInfo);
+ ScopedTensorHandle biasTensor(biasInfo);
AllocateAndCopyDataToITensorHandle(&weightTensor, kernelData.data());
AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data());
diff --git a/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp
index 3ee1fadd81..f68082762c 100644
--- a/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp
@@ -8,7 +8,7 @@
#include <armnn/Types.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
@@ -181,7 +181,7 @@ void DetectionPostProcessImpl(const armnn::TensorInfo& boxEncodingsInfo,
auto outputScoresHandle = tensorHandleFactory.CreateTensorHandle(detectionScoresInfo);
auto numDetectionHandle = tensorHandleFactory.CreateTensorHandle(numDetectionInfo);
- armnn::ScopedCpuTensorHandle anchorsTensor(anchorsInfo);
+ armnn::ScopedTensorHandle anchorsTensor(anchorsInfo);
AllocateAndCopyDataToITensorHandle(&anchorsTensor, &anchors[0][0]);
armnn::DetectionPostProcessQueueDescriptor data;
diff --git a/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp
index f8644007f2..157df99d64 100644
--- a/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/FakeQuantizationTestImpl.cpp
@@ -6,7 +6,7 @@
#include "FakeQuantizationTestImpl.hpp"
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadTestUtils.hpp>
@@ -48,7 +48,7 @@ LayerTestResult<float, 2> FakeQuantizationTest(
data.m_Parameters.m_Min = min;
data.m_Parameters.m_Max = max;
- armnn::PassthroughCpuTensorHandle refHandle(tensorInfo, &ret.outputExpected[0][0]);
+ armnn::PassthroughTensorHandle refHandle(tensorInfo, &ret.outputExpected[0][0]);
armnn::FakeQuantizationQueueDescriptor refData = data;
armnn::WorkloadInfo refInfo = info;
SetWorkloadOutput(refData, refInfo, 0, tensorInfo, &refHandle);
diff --git a/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
index 9176094eb2..cd7f4efe31 100644
--- a/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp
@@ -8,7 +8,7 @@
#include <QuantizeHelper.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/test/DataTypeUtils.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
@@ -40,8 +40,8 @@ LayerTestResult<T, 2> SimpleFullyConnectedTestImpl(
armnn::FullyConnectedQueueDescriptor data;
armnn::WorkloadInfo info;
- armnn::ScopedCpuTensorHandle weightsTensor(weightsDesc);
- armnn::ScopedCpuTensorHandle biasTensor(biasesDesc);
+ armnn::ScopedTensorHandle weightsTensor(weightsDesc);
+ armnn::ScopedTensorHandle biasTensor(biasesDesc);
AllocateAndCopyDataToITensorHandle(&weightsTensor, &weights[0][0]);
AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
diff --git a/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp
index 2e205dd58e..24a4dc4789 100644
--- a/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp
@@ -9,7 +9,7 @@
#include <ResolveType.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp
index 7ee7a3465b..f32d367d37 100644
--- a/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/LogSoftmaxTestImpl.cpp
@@ -10,7 +10,7 @@
#include <ResolveType.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
index 07a1f1e879..7a9652a8ea 100644
--- a/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
@@ -9,7 +9,7 @@
#include <armnn/utility/NumericCast.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadTestUtils.hpp>
@@ -269,19 +269,19 @@ LstmNoCifgNoPeepholeNoProjectionTestImpl(
auto outputGateBias = MakeTensor<float, 1>(tensorInfo4, {0., 0., 0., 0.});
- armnn::ScopedCpuTensorHandle inputToInputWeightsTensor(tensorInfo8);
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(tensorInfo8);
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(tensorInfo8);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(tensorInfo8);
- armnn::ScopedCpuTensorHandle recurrentToInputWeightsTensor(tensorInfo16);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(tensorInfo16);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(tensorInfo16);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(tensorInfo16);
- armnn::ScopedCpuTensorHandle cellToInputWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle inputGateBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle inputToInputWeightsTensor(tensorInfo8);
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(tensorInfo8);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(tensorInfo8);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(tensorInfo8);
+ armnn::ScopedTensorHandle recurrentToInputWeightsTensor(tensorInfo16);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(tensorInfo16);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(tensorInfo16);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(tensorInfo16);
+ armnn::ScopedTensorHandle cellToInputWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle inputGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle outputGateBiasTensor(tensorInfo4);
AllocateAndCopyDataToITensorHandle(&inputToInputWeightsTensor, &inputToInputWeights[0][0]);
AllocateAndCopyDataToITensorHandle(&inputToForgetWeightsTensor, &inputToForgetWeights[0][0]);
@@ -971,23 +971,23 @@ LstmLayerNoCifgWithPeepholeWithProjectionTestImpl(armnn::IWorkloadFactory& workl
std::vector<float> projectionBiasVector(outputSize, 0.f);
auto projectionBias = MakeTensor<float,1>(tensorInfo16, projectionBiasVector);
- armnn::ScopedCpuTensorHandle inputToInputWeightsTensor(tensorInfo20x5);
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(tensorInfo20x5);
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(tensorInfo20x5);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(tensorInfo20x5);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(tensorInfo20x16);
- armnn::ScopedCpuTensorHandle recurrentToInputWeightsTensor(tensorInfo20x16);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(tensorInfo20x16);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(tensorInfo20x16);
- armnn::ScopedCpuTensorHandle cellToInputWeightsTensor(tensorInfo20);
- armnn::ScopedCpuTensorHandle inputGateBiasTensor(tensorInfo20);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(tensorInfo20);
- armnn::ScopedCpuTensorHandle cellBiasTensor(tensorInfo20);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(tensorInfo20);
- armnn::ScopedCpuTensorHandle cellToForgetWeightsTensor(tensorInfo20);
- armnn::ScopedCpuTensorHandle cellToOutputWeightsTensor(tensorInfo20);
- armnn::ScopedCpuTensorHandle projectionWeightsTensor(tensorInfo16x20);
- armnn::ScopedCpuTensorHandle projectionBiasTensor(tensorInfo16);
+ armnn::ScopedTensorHandle inputToInputWeightsTensor(tensorInfo20x5);
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(tensorInfo20x5);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(tensorInfo20x5);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(tensorInfo20x5);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(tensorInfo20x16);
+ armnn::ScopedTensorHandle recurrentToInputWeightsTensor(tensorInfo20x16);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(tensorInfo20x16);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(tensorInfo20x16);
+ armnn::ScopedTensorHandle cellToInputWeightsTensor(tensorInfo20);
+ armnn::ScopedTensorHandle inputGateBiasTensor(tensorInfo20);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(tensorInfo20);
+ armnn::ScopedTensorHandle cellBiasTensor(tensorInfo20);
+ armnn::ScopedTensorHandle outputGateBiasTensor(tensorInfo20);
+ armnn::ScopedTensorHandle cellToForgetWeightsTensor(tensorInfo20);
+ armnn::ScopedTensorHandle cellToOutputWeightsTensor(tensorInfo20);
+ armnn::ScopedTensorHandle projectionWeightsTensor(tensorInfo16x20);
+ armnn::ScopedTensorHandle projectionBiasTensor(tensorInfo16);
AllocateAndCopyDataToITensorHandle(&inputToInputWeightsTensor, &inputToInputWeights[0][0]);
AllocateAndCopyDataToITensorHandle(&inputToForgetWeightsTensor, &inputToForgetWeights[0][0]);
@@ -1142,21 +1142,21 @@ LayerTestResult<T, 2> LstmLayerWithCifgWithPeepholeNoProjectionTestImpl(
auto cellToOutputWeights = MakeTensor<float, 1>(tensorInfoNumUnits,
{-0.17135078f, 0.82760304f, 0.85573703f, -0.77109635f});
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(tensorInfoInput);
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(tensorInfoInput);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(tensorInfoInput);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(tensorInfoInput);
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(tensorInfoInput);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(tensorInfoInput);
- armnn::ScopedCpuTensorHandle cellBiasTensor(tensorInfoNumUnits);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(tensorInfoNumUnits);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(tensorInfoNumUnits);
+ armnn::ScopedTensorHandle cellBiasTensor(tensorInfoNumUnits);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(tensorInfoNumUnits);
+ armnn::ScopedTensorHandle outputGateBiasTensor(tensorInfoNumUnits);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(tensorInfoOutput);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(tensorInfoOutput);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(tensorInfoOutput);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(tensorInfoOutput);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(tensorInfoOutput);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(tensorInfoOutput);
- armnn::ScopedCpuTensorHandle cellToForgetWeightsTensor(tensorInfoNumUnits);
- armnn::ScopedCpuTensorHandle cellToOutputWeightsTensor(tensorInfoNumUnits);
+ armnn::ScopedTensorHandle cellToForgetWeightsTensor(tensorInfoNumUnits);
+ armnn::ScopedTensorHandle cellToOutputWeightsTensor(tensorInfoNumUnits);
AllocateAndCopyDataToITensorHandle(&inputToCellWeightsTensor, &inputToCellWeights[0][0]);
AllocateAndCopyDataToITensorHandle(&inputToForgetWeightsTensor, &inputToForgetWeights[0][0]);
@@ -1455,28 +1455,28 @@ LstmLayerNoCifgWithPeepholeWithProjectionWithLayerNormTestImpl(armnn::IWorkloadF
MakeTensor<float, 1>(tensorInfo4, {0.6f, 0.2f, 0.2f, 0.5f}); //{numUnits}
- armnn::ScopedCpuTensorHandle inputToInputWeightsTensor(tensorInfo4x5);
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(tensorInfo4x5);
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(tensorInfo4x5);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(tensorInfo4x5);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(tensorInfo4x3);
- armnn::ScopedCpuTensorHandle recurrentToInputWeightsTensor(tensorInfo4x3);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(tensorInfo4x3);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(tensorInfo4x3);
- armnn::ScopedCpuTensorHandle cellToInputWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle inputGateBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellToForgetWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellToOutputWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle projectionWeightsTensor(tensorInfo3x4);
- armnn::ScopedCpuTensorHandle projectionBiasTensor(tensorInfo3);
-
- armnn::ScopedCpuTensorHandle inputLayerNormWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle forgetLayerNormWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle cellLayerNormWeightsTensor(tensorInfo4);
- armnn::ScopedCpuTensorHandle outputLayerNormWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle inputToInputWeightsTensor(tensorInfo4x5);
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(tensorInfo4x5);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(tensorInfo4x5);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(tensorInfo4x5);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(tensorInfo4x3);
+ armnn::ScopedTensorHandle recurrentToInputWeightsTensor(tensorInfo4x3);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(tensorInfo4x3);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(tensorInfo4x3);
+ armnn::ScopedTensorHandle cellToInputWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle inputGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle outputGateBiasTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellToForgetWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellToOutputWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle projectionWeightsTensor(tensorInfo3x4);
+ armnn::ScopedTensorHandle projectionBiasTensor(tensorInfo3);
+
+ armnn::ScopedTensorHandle inputLayerNormWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle forgetLayerNormWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle cellLayerNormWeightsTensor(tensorInfo4);
+ armnn::ScopedTensorHandle outputLayerNormWeightsTensor(tensorInfo4);
AllocateAndCopyDataToITensorHandle(&inputToInputWeightsTensor, &inputToInputWeights[0][0]);
AllocateAndCopyDataToITensorHandle(&inputToForgetWeightsTensor, &inputToForgetWeights[0][0]);
@@ -1673,21 +1673,21 @@ LayerTestResult<uint8_t, 2> QuantizedLstmTestImpl(
auto cellBias = MakeTensor<int32_t, 1>(biasInfo, {39481, 48624, 48976, -21419});
auto outputGateBias = MakeTensor<int32_t, 1>(biasInfo, {-58999, -17050, -41852, -40538});
- // ScopedCpuTensorHandles
- armnn::ScopedCpuTensorHandle inputToInputWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(inputWeightsInfo);
+ // ScopedTensorHandles
+ armnn::ScopedTensorHandle inputToInputWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToInputWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToInputWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle inputGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle cellBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle inputGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle cellBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle outputGateBiasTensor(biasInfo);
// Allocate and copy data
AllocateAndCopyDataToITensorHandle(&inputToInputWeightsTensor, &inputToInputWeights[0][0]);
@@ -1891,22 +1891,22 @@ LayerTestResult<int8_t, 2> QLstmTestImpl(
auto cellLayerNormWeights = MakeTensor<int16_t, 1>(layerNormWeightsInfo, {22937, 6553, 9830, 26214});
auto outputLayerNormWeights = MakeTensor<int16_t, 1>(layerNormWeightsInfo, {19660, 6553, 6553, 16384});
- // ScopedCpuTensorHandles
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(inputWeightsInfo);
+ // ScopedTensorHandles
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle cellBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle cellBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle outputGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle forgetLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle cellLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle outputLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle forgetLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle cellLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle outputLayerNormWeightsTensor(layerNormWeightsInfo);
// Allocate and copy data
AllocateAndCopyDataToITensorHandle(&inputToForgetWeightsTensor, &inputToForgetWeights[0][0]);
@@ -2145,28 +2145,28 @@ LayerTestResult<int8_t, 2> QLstmTestImpl1(
auto projectionWeights = MakeTensor<int8_t, 2>(projectionWeightsInfo,
{-25, 51, 3, -51, 25, 127, 77, 20, 18, 51, -102, 51});
- // ScopedCpuTensorHandles
- armnn::ScopedCpuTensorHandle inputToInputWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(inputWeightsInfo);
+ // ScopedTensorHandles
+ armnn::ScopedTensorHandle inputToInputWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToInputWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToInputWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle inputGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle cellBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle inputGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle cellBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle outputGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle inputLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle forgetLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle cellLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle outputLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle inputLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle forgetLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle cellLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle outputLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle projectionWeightsTensor(projectionWeightsInfo);
+ armnn::ScopedTensorHandle projectionWeightsTensor(projectionWeightsInfo);
// Allocate and copy data
AllocateAndCopyDataToITensorHandle(&inputToInputWeightsTensor, &inputToInputWeights[0][0]);
@@ -2411,24 +2411,24 @@ LayerTestResult<int8_t, 2> QLstmTestImpl2(
auto projectionWeights = MakeTensor<int8_t, 2>(projectionWeightsInfo,
{-25, 51, 3, -51, 25, 127, 77, 20, 18, 51, -102, 51});
- // ScopedCpuTensorHandles
- armnn::ScopedCpuTensorHandle inputToForgetWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToCellWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle inputToOutputWeightsTensor(inputWeightsInfo);
+ // ScopedTensorHandles
+ armnn::ScopedTensorHandle inputToForgetWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToCellWeightsTensor(inputWeightsInfo);
+ armnn::ScopedTensorHandle inputToOutputWeightsTensor(inputWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToForgetWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToCellWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle recurrentToOutputWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToForgetWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToCellWeightsTensor(recurrentWeightsInfo);
+ armnn::ScopedTensorHandle recurrentToOutputWeightsTensor(recurrentWeightsInfo);
- armnn::ScopedCpuTensorHandle forgetGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle cellBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle outputGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle forgetGateBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle cellBiasTensor(biasInfo);
+ armnn::ScopedTensorHandle outputGateBiasTensor(biasInfo);
- armnn::ScopedCpuTensorHandle forgetLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle cellLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle outputLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle forgetLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle cellLayerNormWeightsTensor(layerNormWeightsInfo);
+ armnn::ScopedTensorHandle outputLayerNormWeightsTensor(layerNormWeightsInfo);
- armnn::ScopedCpuTensorHandle projectionWeightsTensor(projectionWeightsInfo);
+ armnn::ScopedTensorHandle projectionWeightsTensor(projectionWeightsInfo);
// Allocate and copy data
AllocateAndCopyDataToITensorHandle(&inputToForgetWeightsTensor, &inputToForgetWeights[0][0]);
diff --git a/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp
index 2e8e16f0c2..b52dcd5303 100644
--- a/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/NormalizationTestImpl.cpp
@@ -10,7 +10,7 @@
#include <armnn/utility/NumericCast.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadTestUtils.hpp>
@@ -75,7 +75,7 @@ LayerTestResult<float,4> SimpleNormalizationTestImpl(
data.m_Parameters.m_K = kappa;
data.m_Parameters.m_DataLayout = armnn::DataLayout::NCHW;
- armnn::PassthroughCpuTensorHandle refHandle(outputTensorInfo, &ret.outputExpected[0][0][0][0]);
+ armnn::PassthroughTensorHandle refHandle(outputTensorInfo, &ret.outputExpected[0][0][0][0]);
armnn::NormalizationQueueDescriptor refData = data;
armnn::WorkloadInfo refInfo = info;
SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, &refHandle);
@@ -219,7 +219,7 @@ LayerTestResult<float,4> SimpleNormalizationNhwcTestImpl(
data.m_Parameters.m_K = kappa;
data.m_Parameters.m_DataLayout = armnn::DataLayout::NHWC;
- armnn::PassthroughCpuTensorHandle refHandle(outputTensorInfo, &ret.outputExpected[0][0][0][0]);
+ armnn::PassthroughTensorHandle refHandle(outputTensorInfo, &ret.outputExpected[0][0][0][0]);
armnn::NormalizationQueueDescriptor refData = data;
armnn::WorkloadInfo refInfo = info;
SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, &refHandle);
diff --git a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
index c4cc914115..9688ce49f2 100644
--- a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
@@ -9,7 +9,7 @@
#include <ResolveType.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadTestUtils.hpp>
diff --git a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
index 328e724b54..85ce7e5e6f 100644
--- a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
@@ -10,7 +10,7 @@
#include <armnnUtils/Permute.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
#include <backendsCommon/test/DataLayoutUtils.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
@@ -68,7 +68,7 @@ void TransposeConvolution2dTestImpl(armnn::IWorkloadFactory& workloadFactory,
}
// set up weights
- ScopedCpuTensorHandle weightsTensor(weights.first);
+ ScopedTensorHandle weightsTensor(weights.first);
TransposeConvolution2dQueueDescriptor queueDescriptor;
queueDescriptor.m_Parameters = descriptor;
@@ -76,11 +76,11 @@ void TransposeConvolution2dTestImpl(armnn::IWorkloadFactory& workloadFactory,
AllocateAndCopyDataToITensorHandle(&weightsTensor, weights.second.data());
- std::unique_ptr<ScopedCpuTensorHandle> biasesTensor;
+ std::unique_ptr<ScopedTensorHandle> biasesTensor;
if (descriptor.m_BiasEnabled)
{
// set up biases
- biasesTensor = std::make_unique<ScopedCpuTensorHandle>(biases.value().first);
+ biasesTensor = std::make_unique<ScopedTensorHandle>(biases.value().first);
queueDescriptor.m_Bias = biasesTensor.get();
AllocateAndCopyDataToITensorHandle(biasesTensor.get(), biases.value().second.data());
@@ -643,8 +643,8 @@ LayerTestResult<uint8_t, 4> TransposeConvolution2dPerAxisQuantTest(
std::unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo);
WorkloadInfo workloadInfo;
- ScopedCpuTensorHandle weightTensor(kernelInfo);
- ScopedCpuTensorHandle biasTensor(biasInfo);
+ ScopedTensorHandle weightTensor(kernelInfo);
+ ScopedTensorHandle biasTensor(biasInfo);
AllocateAndCopyDataToITensorHandle(&weightTensor, kernelData.data());
AllocateAndCopyDataToITensorHandle(&biasTensor, biasData.data());