detector = trainFasterRCNNObjectDetector(trainData, layers, options, ... 'NegativeOverlapRange', [0 0.3], ... 'PositiveOverlapRange', [0.6 1], ... 'BoxPyramidScale', 1.2);
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Error: parallel.gpu.CUDADevice.hBuild
An unexpected error occurred trying to retrieve CUDA device properties. The CUDA error was:
CUDA_ERROR_UNKNOWN
Error: parallel.gpu.GPUDevice.getDevice (line 76)
d = parallel.gpu.CUDADevice.hBuild( idx );
Error: parallel.gpu.GPUDevice.isAvailable (line 146)
device = parallel.gpu.GPUDevice.getDevice( index );
Error: nnet.internal.cnn.util.isGPUCompatible (line 9)
if(iCanUsePCT() && parallel.gpu.GPUDevice.isAvailable())
Error: nnet.internal.cnn.util.GPUShouldBeUsed (line 17)
tf = nnet.internal.cnn.util.isGPUCompatible();
Error: vision.internal.cnn.trainNetwork>iSetupExecutionEnvironment (line 134)
GPUShouldBeUsed = nnet.internal.cnn.util.GPUShouldBeUsed( ...
Error: vision.internal.cnn.trainNetwork (line 43)
executionSettings = iSetupExecutionEnvironment( opts );
Error: fasterRCNNObjectDetector.trainRPN (line 175)
[rpn, info] = vision.internal.cnn.trainNetwork(dispatcher, layers, opts,
checkpointSaver);
Error: trainFasterRCNNObjectDetector (line 289)
[stage1Detector, rpn, info] = fasterRCNNObjectDetector.trainRPN(trainingData, rpn,
options(1), iStageOneParams(params), checkpointSaver);
Error: rcnn_car_object_detection (line 84)
detector = trainFasterRCNNObjectDetector(trainData, layers, options, ...
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回答(1 个)
Vidip
2024-6-7
I understand that you are getting the following error: error using parallel.gpu.CUDADevice.hBuild, with a CUDA runtime error of CUDA_ERROR_UNKNOWN. Try setting the "high performance NVIDIA Processor" option for MATLAB on NVIDIA control panel. You can find it at 3D Settings -> Manage 3D Settings -> Select a program to customize. This should alleviate the CUDA errors.
For more information regarding CUDA errors while training a network on GPU, you can refer to the below MATLAB Answers thread-
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