diff options
Diffstat (limited to 'src/armnn/test/optimizations/FuseActivationTests.cpp')
-rw-r--r-- | src/armnn/test/optimizations/FuseActivationTests.cpp | 27 |
1 files changed, 18 insertions, 9 deletions
diff --git a/src/armnn/test/optimizations/FuseActivationTests.cpp b/src/armnn/test/optimizations/FuseActivationTests.cpp index 2352a3c498..54a9d9a189 100644 --- a/src/armnn/test/optimizations/FuseActivationTests.cpp +++ b/src/armnn/test/optimizations/FuseActivationTests.cpp @@ -66,7 +66,7 @@ struct Convolution2dTest 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 = armnnUtils::QuantizedVector<T>(weightsData, scale, offset); - TensorInfo weightsInfo(GetWeightsShape(), ArmnnType, scale, offset); + TensorInfo weightsInfo(GetWeightsShape(), ArmnnType, scale, offset, true); ConstTensor weights(weightsInfo, weightsVector); Optional<ConstTensor> optionalBias; @@ -115,7 +115,7 @@ public: 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 = armnnUtils::QuantizedVector<T>(weightsData, scale, offset); - TensorInfo weightsInfo(GetWeightsShape(), ArmnnType, scale, offset); + TensorInfo weightsInfo(GetWeightsShape(), ArmnnType, scale, offset, true); ConstTensor weights(weightsInfo, weightsVector); Optional<ConstTensor> optionalBias; @@ -212,10 +212,10 @@ public: std::vector<T> varianceVector = GetVector<T>(GetOutputShape()[3], 1.0f, 0.1f); const unsigned int outputChannelSize[] = { GetOutputShape()[3] }; - 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); return network->AddBatchNormalizationLayer(descriptor, mean, variance, beta, gamma, name); } @@ -491,8 +491,11 @@ void FuseActivationIntoPreviousLayerTest(ActivationDescriptor activationDescript std::vector<T> inputDataFused = armnnUtils::QuantizedVector<T>(data, scale, offset); std::vector<T> outputDataFused(LayerTest::outputSize); + armnn::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())}}; @@ -545,8 +548,11 @@ void FuseActivationIntoPreviousLayerTest(ActivationDescriptor activationDescript std::vector<T> outputDataNotFused(LayerTest::outputSize); std::vector<T> outputData2NotFused(LayerTest::outputSize); + TensorInfo inputTensorInfoNotFused = runNotFused->GetInputTensorInfo(networkIdentifierNotFused, 0); + inputTensorInfoNotFused.SetConstant(true); + InputTensors inputTensorsNotFused{ - {0, ConstTensor(runNotFused->GetInputTensorInfo(networkIdentifierNotFused, 0), inputDataNotFused.data())}}; + {0, ConstTensor(inputTensorInfoNotFused, inputDataNotFused.data())}}; OutputTensors outputTensorsNotFused{ {0, Tensor(runNotFused->GetOutputTensorInfo(networkIdentifierNotFused, 0), outputDataNotFused.data())}, {1, Tensor(runNotFused->GetOutputTensorInfo(networkIdentifierNotFused, 1), outputData2NotFused.data())}}; @@ -591,8 +597,11 @@ bool FuseActivationSimpleTest(ActivationDescriptor activationDescriptor, Compute std::vector<T> inputDataFused = armnnUtils::QuantizedVector<T>(data, scale, offset); std::vector<T> outputDataFused(LayerTest::outputSize); + 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())}}; |