Tensorflow CUDA 失败并出现错误 "failed to enqueue convolution on stream: CUDNN_STATUS_EXECUTION_FAILED"
Tensorflow CUDA fails with error "failed to enqueue convolution on stream: CUDNN_STATUS_EXECUTION_FAILED"
这是我的一些控制台输出。我不确定实际问题是什么。显示时,我收到 windows 提示,提示 Python.exe 已停止工作,原因是 ucrtbase.dll,但我已尝试更新它,但它仍然发生,所以我认为这就是结果的真正问题。另外,任务栏消息通知我我的 Nvidia 内核驱动程序崩溃了,但已恢复。
2017-11-04 17:48:17.363024: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-11-04 17:48:17.375024: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-04 17:48:19.995174: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\gpu\gpu_device.cc:955
Found device 0 with properties:
name: Quadro K1100M
major: 3 minor: 0 memoryClockRate (GHz) 0.7055
pciBusID 0000:01:00.0
Total memory: 2.00GiB
Free memory: 1.93GiB
2017-11-04 17:48:19.995174: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\gpu\gpu_device.cc:976] DMA: 0
2017-11-04 17:48:19.995174: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\gpu\gpu_device.cc:986] 0: Y
2017-11-04 17:48:20.018175: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\gpu\gpu_device.cc:1045]
Creating TensorFlow device (/gpu:0) -> (device: 0, name: Quadro K1100M, pci bus id: 0000:01:00.0)
2017-11-04 17:49:35.796510: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.93GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2017-11-04 17:49:41.811854: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\stream_executor\cuda\cuda_driver.cc:1068] failed to synchronize the stop event: CUDA_ERROR_UNKNOWN
2017-11-04 17:49:41.811854: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\stream_executor\cuda\cuda_timer.cc:54] Internal: error destroying CUDA event in context 0000000026CFBE70: CUDA_ERROR_UNKNOWN
2017-11-04 17:49:41.811854: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\stream_executor\cuda\cuda_timer.cc:59] Internal: error destroying CUDA event in context 0000000026CFBE70: CUDA_ERROR_UNKNOWN
2017-11-04 17:49:41.811854: F C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\stream_executor\cuda\cuda_dnn.cc:2045] failed to enqueue convolution on stream: CUDNN_STATUS_EXECUTION_FAILED
如果您仍在寻找答案,请尝试减小批量大小。我不完全确定错误是怎么回事(github 也没有解释),但减少批量大小对我有帮助
这是我的一些控制台输出。我不确定实际问题是什么。显示时,我收到 windows 提示,提示 Python.exe 已停止工作,原因是 ucrtbase.dll,但我已尝试更新它,但它仍然发生,所以我认为这就是结果的真正问题。另外,任务栏消息通知我我的 Nvidia 内核驱动程序崩溃了,但已恢复。
2017-11-04 17:48:17.363024: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-11-04 17:48:17.375024: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-04 17:48:19.995174: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\gpu\gpu_device.cc:955
Found device 0 with properties:
name: Quadro K1100M
major: 3 minor: 0 memoryClockRate (GHz) 0.7055
pciBusID 0000:01:00.0
Total memory: 2.00GiB
Free memory: 1.93GiB
2017-11-04 17:48:19.995174: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\gpu\gpu_device.cc:976] DMA: 0
2017-11-04 17:48:19.995174: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\gpu\gpu_device.cc:986] 0: Y
2017-11-04 17:48:20.018175: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\gpu\gpu_device.cc:1045]
Creating TensorFlow device (/gpu:0) -> (device: 0, name: Quadro K1100M, pci bus id: 0000:01:00.0)
2017-11-04 17:49:35.796510: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\core\common_runtime\bfc_allocator.cc:217] Allocator (GPU_0_bfc) ran out of memory trying to allocate 1.93GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available.
2017-11-04 17:49:41.811854: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\stream_executor\cuda\cuda_driver.cc:1068] failed to synchronize the stop event: CUDA_ERROR_UNKNOWN
2017-11-04 17:49:41.811854: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\stream_executor\cuda\cuda_timer.cc:54] Internal: error destroying CUDA event in context 0000000026CFBE70: CUDA_ERROR_UNKNOWN
2017-11-04 17:49:41.811854: E C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\stream_executor\cuda\cuda_timer.cc:59] Internal: error destroying CUDA event in context 0000000026CFBE70: CUDA_ERROR_UNKNOWN
2017-11-04 17:49:41.811854: F C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\tensorflow\stream_executor\cuda\cuda_dnn.cc:2045] failed to enqueue convolution on stream: CUDNN_STATUS_EXECUTION_FAILED
如果您仍在寻找答案,请尝试减小批量大小。我不完全确定错误是怎么回事(github 也没有解释),但减少批量大小对我有帮助