diff options
Diffstat (limited to 'src/armnn/test/OptimizerTests.cpp')
| -rw-r--r-- | src/armnn/test/OptimizerTests.cpp | 22 |
1 files changed, 13 insertions, 9 deletions
diff --git a/src/armnn/test/OptimizerTests.cpp b/src/armnn/test/OptimizerTests.cpp index 3cea1b540e..750e6967ad 100644 --- a/src/armnn/test/OptimizerTests.cpp +++ b/src/armnn/test/OptimizerTests.cpp @@ -405,7 +405,9 @@ void CreateConvolution2dGraph(Graph &graph, const unsigned int* inputShape, armnn::TensorInfo outputInfo(4, outputShape, DataType::Float32); std::vector<float> weightsVector(90); - armnn::ConstTensor weights(armnn::TensorInfo(4, weightsShape, armnn::DataType::Float32), weightsVector); + armnn::ConstTensor weights( + armnn::TensorInfo(4, weightsShape, armnn::DataType::Float32, 0.0f, 0, true), + weightsVector); Convolution2dDescriptor desc; desc.m_BiasEnabled = false; @@ -455,7 +457,9 @@ void CreateDepthwiseConvolution2dGraph(Graph &graph, const unsigned int* inputSh armnn::TensorInfo outputInfo(4, outputShape, DataType::Float32); std::vector<float> weightsVector(18); - armnn::ConstTensor weights(armnn::TensorInfo(4, weightsShape, armnn::DataType::Float32), weightsVector); + armnn::ConstTensor weights( + armnn::TensorInfo(4, weightsShape, armnn::DataType::Float32, 0.0f, 0, true), + weightsVector); DepthwiseConvolution2dDescriptor desc; desc.m_BiasEnabled = false; @@ -653,7 +657,7 @@ TEST_CASE("DetectionPostProcessValidateTensorShapes") armnn::TensorInfo boxEncodingsInfo({1, 10, 4}, DataType::QAsymmU8); armnn::TensorInfo scoresInfo({1, 10, 4}, DataType::QAsymmU8); std::vector<uint8_t> anchorsVector(40); - armnn::ConstTensor anchors(armnn::TensorInfo({10, 4}, armnn::DataType::QAsymmU8), anchorsVector); + armnn::ConstTensor anchors(armnn::TensorInfo({10, 4}, armnn::DataType::QAsymmU8, 0.0f, 0, true), anchorsVector); armnn::TensorInfo detectionBoxesInfo({1, 3, 4}, DataType::QAsymmU8); armnn::TensorInfo detectionScoresInfo({1, 3}, DataType::QAsymmU8); @@ -833,16 +837,16 @@ TEST_CASE("OptimizeForExclusiveConnectionsFuseTest") TensorInfo outputInfo(4, outputDimensionSizes, DataType::Float32); std::vector<float> weightsVector = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }; - ConstTensor weights(TensorInfo(4, weightsDimensionSizes, DataType::Float32), weightsVector); + ConstTensor weights(TensorInfo(4, weightsDimensionSizes, DataType::Float32, 0.0f, 0, true), weightsVector); std::vector<float> betaVector = { 0.1f }; std::vector<float> gammaVector = { 0.5f }; std::vector<float> meanVector = { 0 }; std::vector<float> varianceVector = { 1 }; - ConstTensor beta(TensorInfo(1, outputChannelSize, DataType::Float32), betaVector); - ConstTensor gamma(TensorInfo(1, outputChannelSize, DataType::Float32), gammaVector); - ConstTensor mean(TensorInfo(1, outputChannelSize, DataType::Float32), meanVector); - ConstTensor variance(TensorInfo(1, outputChannelSize, DataType::Float32), varianceVector); + ConstTensor beta(TensorInfo(1, outputChannelSize, DataType::Float32, 0.0f, 0, true), betaVector); + ConstTensor gamma(TensorInfo(1, outputChannelSize, DataType::Float32, 0.0f, 0, true), gammaVector); + ConstTensor mean(TensorInfo(1, outputChannelSize, DataType::Float32, 0.0f, 0, true), meanVector); + ConstTensor variance(TensorInfo(1, outputChannelSize, DataType::Float32, 0.0f, 0, true), varianceVector); // Define the network Graph graph; @@ -863,7 +867,7 @@ TEST_CASE("OptimizeForExclusiveConnectionsFuseTest") if (convolution2dDescriptor.m_BiasEnabled) { std::vector<float> biasVector = { 11 }; - ConstTensor bias(TensorInfo(1, outputChannelSize, DataType::Float32), biasVector); + ConstTensor bias(TensorInfo(1, outputChannelSize, DataType::Float32, 0.0f, 0, true), biasVector); conv->m_Bias = std::make_unique<ScopedTensorHandle>(bias); } |