diff options
Diffstat (limited to 'src/armnn/test/optimizations/FuseBatchNormTests.cpp')
| -rw-r--r-- | src/armnn/test/optimizations/FuseBatchNormTests.cpp | 21 |
1 files changed, 13 insertions, 8 deletions
diff --git a/src/armnn/test/optimizations/FuseBatchNormTests.cpp b/src/armnn/test/optimizations/FuseBatchNormTests.cpp index 20d2940b81..0e969c1a5c 100644 --- a/src/armnn/test/optimizations/FuseBatchNormTests.cpp +++ b/src/armnn/test/optimizations/FuseBatchNormTests.cpp @@ -107,11 +107,11 @@ INetworkPtr CreatNetwork(bool depthwise, bool preventFusing) 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42}; std::vector<T> weightsVector(begin(weightsIntVector), end(weightsIntVector)); - TensorInfo weightsInfo(4, weightsDimensionSizes, ArmnnType); + TensorInfo weightsInfo(4, weightsDimensionSizes, ArmnnType, 0.0f, 0, true); ConstTensor weights(weightsInfo, weightsVector); std::vector<T> biasVector = GetVector<T>(outputDimensionSizes[3], 3.3f, 0.1f); - TensorInfo biasInfo(1, outputChannelSize, ArmnnType); + TensorInfo biasInfo(1, outputChannelSize, ArmnnType, 0.0f, 0, true); ConstTensor bias(biasInfo, biasVector); Optional<ConstTensor> optionalBias = Optional<ConstTensor>(bias); @@ -120,10 +120,10 @@ INetworkPtr CreatNetwork(bool depthwise, bool preventFusing) std::vector<T> meanVector = GetVector<T>(outputDimensionSizes[3], 0.1f, 0.1f); std::vector<T> varianceVector = GetVector<T>(outputDimensionSizes[3], 1.0f, 0.1f); - ConstTensor beta (TensorInfo(1, outputChannelSize, ArmnnType), betaVector); - ConstTensor gamma (TensorInfo(1, outputChannelSize, ArmnnType), gammaVector); - ConstTensor mean (TensorInfo(1, outputChannelSize, ArmnnType), meanVector); - ConstTensor variance(TensorInfo(1, outputChannelSize, ArmnnType), varianceVector); + ConstTensor beta (TensorInfo(1, outputChannelSize, ArmnnType, 0.0f, 0, true), betaVector); + ConstTensor gamma (TensorInfo(1, outputChannelSize, ArmnnType, 0.0f, 0, true), gammaVector); + ConstTensor mean (TensorInfo(1, outputChannelSize, ArmnnType, 0.0f, 0, true), meanVector); + ConstTensor variance(TensorInfo(1, outputChannelSize, ArmnnType, 0.0f, 0, true), varianceVector); // Create a network INetworkPtr network = INetwork::Create(); @@ -215,8 +215,10 @@ void FuseBatchNormIntoConvTest(bool depthwise, float tolerance, armnn::Compute b outputDataFused.resize(108); } + TensorInfo inputTensorInfo = run->GetInputTensorInfo(networkIdentifier, 0); + inputTensorInfo.SetConstant(true); InputTensors inputTensorsFused { - {0, ConstTensor(run->GetInputTensorInfo (networkIdentifier, 0), inputDataFused.data())}}; + {0, ConstTensor(inputTensorInfo, inputDataFused.data())}}; OutputTensors outputTensorsFused{ {0, Tensor(run->GetOutputTensorInfo(networkIdentifier, 0), outputDataFused.data())}}; @@ -259,8 +261,11 @@ void FuseBatchNormIntoConvTest(bool depthwise, float tolerance, armnn::Compute b outputDataNotFused.resize(108); outputData2NotFused.resize(108); } + + TensorInfo inputTensorInfo2 = runNotFused->GetInputTensorInfo(networkIdentifierNotFused, 0); + inputTensorInfo2.SetConstant(true); InputTensors inputTensorsNotFused{ - {0, ConstTensor(runNotFused->GetInputTensorInfo(networkIdentifierNotFused, 0), inputDataNotFused.data())}}; + {0, ConstTensor(inputTensorInfo2, inputDataNotFused.data())}}; OutputTensors outputTensorsNotFused{ {0, Tensor(runNotFused->GetOutputTensorInfo(networkIdentifierNotFused, 0), outputDataNotFused.data())}, {1, Tensor(runNotFused->GetOutputTensorInfo(networkIdentifierNotFused, 1), outputData2NotFused.data())}}; |