From 5b8093c17044e8eaaaa42d96ba4902dee5791be4 Mon Sep 17 00:00:00 2001 From: Cathal Corbett Date: Fri, 22 Oct 2021 11:12:07 +0100 Subject: IVGCVSW-6420: Constant flag in tensor info is not set correctly !android-nn-driver:6532 !armnn-internal-tests:372451 * Made fix to 2 out of 3 ConstTensor() constructors in Tensor.hpp to throw InvalidArgumentException when TensorInfo isConstant parameter is false. * Added new ConstTensor() constructor in Tensor.cpp to accept vector<>.data() using template. * Fixed runtime->GetOutputTensorInfo()/GetInputTensorInfo() methods and called submethods to return TensorInfo& rather than TensorInfo. * Fixed all failing unit tests for CpuRef/CpuAcc/GpuAcc to ensure any ConstTensor created has it's TensorInfo isConstant set to true. * Added unit tests in TensorTest.cpp to ensure ConstTensor constructors throw InvalidArgumentException when TensorInfo isConstat parameter is false. * Added unit test to ensure an empty ConstTensor constructor will set TensorInfo isConatant to true. * Indentation fixes. * Fix to arm_tensor.i to add isConstant parameter to TensorInfo constructor. Added methods IsConstant() and SetConstant(). * Fix to const_tensor.py to throw ValueError when TensorInfo isConstant is set to false when constructing a ConstTensor. * Fixed PyArmnn unit tests to set TensorInfo isConstant to True when ConstTensor is used. * Added unit tests in test_const_tensor.py to ensure ConstTensor constructors throw ValueError when TensorInfo isConstat parameter is false. Signed-off-by: Cathal Corbett Change-Id: I44e440dd0422c366d31bbdbc77ad2b4db0bde148 --- .../backendsCommon/test/EndToEndTestImpl.hpp | 23 +++++++++++++--------- 1 file changed, 14 insertions(+), 9 deletions(-) (limited to 'src/backends/backendsCommon/test/EndToEndTestImpl.hpp') diff --git a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp index 2d268f8ea1..269a46077e 100644 --- a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp +++ b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp @@ -79,7 +79,8 @@ bool ConstantUsageTest(const std::vector& computeDevice, inline bool ConstantUsageFloat32Test(const std::vector& backends) { - const TensorInfo commonTensorInfo({ 2, 3 }, DataType::Float32); + TensorInfo commonTensorInfo({ 2, 3 }, DataType::Float32); + commonTensorInfo.SetConstant(true); return ConstantUsageTest(backends, commonTensorInfo, @@ -98,6 +99,7 @@ inline bool ConstantUsageUint8Test(const std::vector& backends) commonTensorInfo.SetQuantizationScale(scale); commonTensorInfo.SetQuantizationOffset(offset); + commonTensorInfo.SetConstant(true); return ConstantUsageTest(backends, commonTensorInfo, @@ -198,7 +200,7 @@ inline void ImportNonAlignedInputPointerTest(std::vector backends) input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0)); - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32, 0.0f, 0, true)); pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); // Optimize the network @@ -263,7 +265,7 @@ inline void ExportNonAlignedOutputPointerTest(std::vector backends) input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0)); - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32, 0.0f, 0, true)); pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); // Optimize the network @@ -334,7 +336,7 @@ inline void ImportAlignedPointerTest(std::vector backends) input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0)); - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32, 0.0f, 0, true)); pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); // Optimize the network @@ -418,7 +420,7 @@ inline void ImportOnlyWorkload(std::vector backends) input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0)); - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32, 0.0f, 0, true)); pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); // optimize the network @@ -449,6 +451,7 @@ inline void ImportOnlyWorkload(std::vector backends) }; INFO("Create Network"); + InputTensors inputTensors { {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData.data())}, @@ -507,7 +510,7 @@ inline void ExportOnlyWorkload(std::vector backends) input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0)); - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32, 0.0f, 0, true)); pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); // optimize the network @@ -536,6 +539,7 @@ inline void ExportOnlyWorkload(std::vector backends) }; INFO("Create Network"); + InputTensors inputTensors { {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData.data())}, @@ -594,7 +598,7 @@ inline void ImportAndExportWorkload(std::vector backends) input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0)); pooling->GetOutputSlot(0).Connect(output->GetInputSlot(0)); - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32, 0.0f, 0, true)); pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32)); IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec()); @@ -624,6 +628,7 @@ inline void ImportAndExportWorkload(std::vector backends) }; INFO("Create Network"); + InputTensors inputTensors { {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData.data())}, @@ -685,7 +690,7 @@ inline void ExportOutputWithSeveralOutputSlotConnectionsTest(std::vectorGetOutputSlot(0).Connect(output0->GetInputSlot(0)); activation->GetOutputSlot(0).Connect(output1->GetInputSlot(0)); - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32)); + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32, 0.0f, 0, true)); activation->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32)); // Optimize the network @@ -794,7 +799,7 @@ inline void StridedSliceInvalidSliceEndToEndTest(std::vector backends input->GetOutputSlot(0).Connect(stridedSlice->GetInputSlot(0)); stridedSlice->GetOutputSlot(0).Connect(output0->GetInputSlot(0)); - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 2, 3 }, DataType::Float32)); + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 2, 3 }, DataType::Float32, 0.0f, 0, true)); stridedSlice->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 3 }, DataType::Float32)); // Attempt to optimize the network and check that the correct exception is thrown -- cgit v1.2.1