From 7e4dc4729d2af8b554be52206fc89bbe1dc21882 Mon Sep 17 00:00:00 2001 From: Cathal Corbett Date: Wed, 10 Nov 2021 12:50:57 +0000 Subject: Fix typo errors from ticket IVGCVSW-6420 * Typo errors from ticket 'Constant flag in tensor info is not set correctly'. Not fixed due to code freeze deadline. Signed-off-by: Cathal Corbett Change-Id: Id80ba60647d1970115a8cf200f0d71e4fada9b30 --- .../src/pyarmnn/swig/modules/armnn_tensor.i | 2 +- .../test/LstmSerializationTests.cpp | 72 ++++++++++++++-------- .../backendsCommon/test/QLstmEndToEndTestImpl.cpp | 21 ++++--- .../test/QuantizedLstmEndToEndTestImpl.cpp | 6 +- src/backends/cl/test/ClFallbackTests.cpp | 1 - src/backends/neon/test/NeonTensorHandleTests.cpp | 2 +- 6 files changed, 68 insertions(+), 36 deletions(-) diff --git a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i index d8ef37d762..892b8e4f08 100644 --- a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i +++ b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i @@ -237,7 +237,7 @@ public: %feature("docstring", " Sets the tensor info to be constant. - + Args: IsConstant (bool): Sets tensor info to constant. diff --git a/src/armnnSerializer/test/LstmSerializationTests.cpp b/src/armnnSerializer/test/LstmSerializationTests.cpp index 3178bc990e..d8f8967bcd 100644 --- a/src/armnnSerializer/test/LstmSerializationTests.cpp +++ b/src/armnnSerializer/test/LstmSerializationTests.cpp @@ -1454,7 +1454,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo inputToInputWeightsInfo(inputToInputWeightsShape, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::ConstTensor inputToInputWeights(inputToInputWeightsInfo, inputToInputWeightsData); armnn::TensorShape inputToForgetWeightsShape = {4, 2}; @@ -1462,7 +1463,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo inputToForgetWeightsInfo(inputToForgetWeightsShape, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::ConstTensor inputToForgetWeights(inputToForgetWeightsInfo, inputToForgetWeightsData); armnn::TensorShape inputToCellWeightsShape = {4, 2}; @@ -1470,7 +1472,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo inputToCellWeightsInfo(inputToCellWeightsShape, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::ConstTensor inputToCellWeights(inputToCellWeightsInfo, inputToCellWeightsData); armnn::TensorShape inputToOutputWeightsShape = {4, 2}; @@ -1478,7 +1481,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo inputToOutputWeightsInfo(inputToOutputWeightsShape, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::ConstTensor inputToOutputWeights(inputToOutputWeightsInfo, inputToOutputWeightsData); // The shape of recurrent weight data is {outputSize, outputSize} = {4, 4} @@ -1487,7 +1491,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo recurrentToInputWeightsInfo(recurrentToInputWeightsShape, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::ConstTensor recurrentToInputWeights(recurrentToInputWeightsInfo, recurrentToInputWeightsData); armnn::TensorShape recurrentToForgetWeightsShape = {4, 4}; @@ -1495,7 +1500,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo recurrentToForgetWeightsInfo(recurrentToForgetWeightsShape, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::ConstTensor recurrentToForgetWeights(recurrentToForgetWeightsInfo, recurrentToForgetWeightsData); armnn::TensorShape recurrentToCellWeightsShape = {4, 4}; @@ -1503,7 +1509,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo recurrentToCellWeightsInfo(recurrentToCellWeightsShape, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::ConstTensor recurrentToCellWeights(recurrentToCellWeightsInfo, recurrentToCellWeightsData); armnn::TensorShape recurrentToOutputWeightsShape = {4, 4}; @@ -1511,7 +1518,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo recurrentToOutputWeightsInfo(recurrentToOutputWeightsShape, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::ConstTensor recurrentToOutputWeights(recurrentToOutputWeightsInfo, recurrentToOutputWeightsData); // The shape of bias data is {outputSize} = {4} @@ -1520,7 +1528,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo inputGateBiasInfo(inputGateBiasShape, armnn::DataType::Signed32, biasScale, - biasOffset, true); + biasOffset, + true); armnn::ConstTensor inputGateBias(inputGateBiasInfo, inputGateBiasData); armnn::TensorShape forgetGateBiasShape = {4}; @@ -1528,7 +1537,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo forgetGateBiasInfo(forgetGateBiasShape, armnn::DataType::Signed32, biasScale, - biasOffset, true); + biasOffset, + true); armnn::ConstTensor forgetGateBias(forgetGateBiasInfo, forgetGateBiasData); armnn::TensorShape cellBiasShape = {4}; @@ -1536,7 +1546,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo cellBiasInfo(cellBiasShape, armnn::DataType::Signed32, biasScale, - biasOffset, true); + biasOffset, + true); armnn::ConstTensor cellBias(cellBiasInfo, cellBiasData); armnn::TensorShape outputGateBiasShape = {4}; @@ -1544,7 +1555,8 @@ TEST_CASE("SerializeDeserializeQuantizedLstm") armnn::TensorInfo outputGateBiasInfo(outputGateBiasShape, armnn::DataType::Signed32, biasScale, - biasOffset, true); + biasOffset, + true); armnn::ConstTensor outputGateBias(outputGateBiasInfo, outputGateBiasData); armnn::QuantizedLstmInputParams params; @@ -1655,12 +1667,14 @@ TEST_CASE("SerializeDeserializeQLstmBasic") armnn::TensorInfo inputWeightsInfo({numUnits, inputSize}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo biasInfo({numUnits}, armnn::DataType::Signed32, biasScale, biasOffset, true); @@ -1816,22 +1830,26 @@ TEST_CASE("SerializeDeserializeQLstmCifgLayerNorm") armnn::TensorInfo inputWeightsInfo({numUnits, inputSize}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo biasInfo({numUnits}, armnn::DataType::Signed32, biasScale, - biasOffset, true); + biasOffset, + true); armnn::TensorInfo layerNormWeightsInfo({numUnits}, armnn::DataType::QSymmS16, layerNormScale, - layerNormOffset, true); + layerNormOffset, + true); // Mandatory params std::vector inputToForgetWeightsData = GenerateRandomData(inputWeightsInfo.GetNumElements()); @@ -2003,32 +2021,38 @@ TEST_CASE("SerializeDeserializeQLstmAdvanced") armnn::TensorInfo inputWeightsInfo({numUnits, inputSize}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo biasInfo({numUnits}, armnn::DataType::Signed32, biasScale, - biasOffset, true); + biasOffset, + true); armnn::TensorInfo peepholeWeightsInfo({numUnits}, armnn::DataType::QSymmS16, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo layerNormWeightsInfo({numUnits}, armnn::DataType::QSymmS16, layerNormScale, - layerNormOffset, true); + layerNormOffset, + true); armnn::TensorInfo projectionWeightsInfo({outputSize, numUnits}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); // Mandatory params std::vector inputToForgetWeightsData = GenerateRandomData(inputWeightsInfo.GetNumElements()); diff --git a/src/backends/backendsCommon/test/QLstmEndToEndTestImpl.cpp b/src/backends/backendsCommon/test/QLstmEndToEndTestImpl.cpp index e2147fc59b..7c87f358d6 100644 --- a/src/backends/backendsCommon/test/QLstmEndToEndTestImpl.cpp +++ b/src/backends/backendsCommon/test/QLstmEndToEndTestImpl.cpp @@ -80,22 +80,26 @@ void QLstmEndToEnd(const std::vector& backends) const armnn::TensorInfo inputWeightsInfo({outputSize, inputSize}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); const armnn::TensorInfo recurrentWeightsInfo({outputSize, outputSize}, armnn::DataType::QSymmS8, weightsScale, - weightsOffset, true); + weightsOffset, + true); const armnn::TensorInfo biasInfo({outputSize}, armnn::DataType::Signed32, biasScale, - biasOffset, true); + biasOffset, + true); const armnn::TensorInfo layerNormWeightsInfo({numUnits}, armnn::DataType::QSymmS16, layerNormScale, - layerNormOffset, true); + layerNormOffset, + true); // Mandatory params const std::vector inputToForgetWeightsVector = @@ -179,17 +183,20 @@ void QLstmEndToEnd(const std::vector& backends) const armnn::TensorInfo inputInfo({numBatches , inputSize}, armnn::DataType::QAsymmS8, inputScale, - inputOffset, true); + inputOffset, + true); const armnn::TensorInfo cellStateInfo({numBatches , numUnits}, armnn::DataType::QSymmS16, cellStateScale, - cellStateOffset, true); + cellStateOffset, + true); const armnn::TensorInfo outputStateInfo({numBatches , outputSize}, armnn::DataType::QAsymmS8, outputScale, - outputOffset, true); + outputOffset, + true); // Input tensor data const std::vector inputVector = {90, 102, 13, 26, 38, 102, 13, 26, 51, 64}; diff --git a/src/backends/backendsCommon/test/QuantizedLstmEndToEndTestImpl.cpp b/src/backends/backendsCommon/test/QuantizedLstmEndToEndTestImpl.cpp index f178951873..d481404f92 100644 --- a/src/backends/backendsCommon/test/QuantizedLstmEndToEndTestImpl.cpp +++ b/src/backends/backendsCommon/test/QuantizedLstmEndToEndTestImpl.cpp @@ -46,12 +46,14 @@ armnn::INetworkPtr CreateQuantizedLstmNetwork(armnn::TensorShape& inputShape, armnn::TensorInfo inputWeightsInfo({outputSize, inputSize}, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo recurrentWeightsInfo({outputSize, outputSize}, armnn::DataType::QAsymmU8, weightsScale, - weightsOffset, true); + weightsOffset, + true); armnn::TensorInfo biasInfo({outputSize}, armnn::DataType::Signed32, biasScale, biasOffset, true); diff --git a/src/backends/cl/test/ClFallbackTests.cpp b/src/backends/cl/test/ClFallbackTests.cpp index 7cd05d193b..cfe2b369ac 100644 --- a/src/backends/cl/test/ClFallbackTests.cpp +++ b/src/backends/cl/test/ClFallbackTests.cpp @@ -540,7 +540,6 @@ TEST_CASE("ClImportDisableFallbackSubgraphToNeon") std::vector expectedOutput{ 11.0f, -1.0f }; - InputTensors inputTensors { { 0, armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) }, diff --git a/src/backends/neon/test/NeonTensorHandleTests.cpp b/src/backends/neon/test/NeonTensorHandleTests.cpp index 2e6854a331..685a0744e7 100644 --- a/src/backends/neon/test/NeonTensorHandleTests.cpp +++ b/src/backends/neon/test/NeonTensorHandleTests.cpp @@ -422,7 +422,7 @@ TEST_CASE("SplitteronXorYNoPaddingRequiredTest") TensorInfo inputTensorInfo = runtime->GetInputTensorInfo(networkIdentifier, it.first); inputTensorInfo.SetConstant(true); inputTensors.push_back({it.first, - ConstTensor(inputTensorInfo, it.second.data())}); + ConstTensor(inputTensorInfo, it.second.data())}); } OutputTensors outputTensors; outputTensors.reserve(expectedOutputData.size()); -- cgit v1.2.1