我遇到了这个问题，其中tensorflow似乎无法找到我的GPU。我收到以下错误：
failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error
总体输出如下：
>>> import tensorflow as tf
>>> from tensorflow.python.client import device_lib
>>> print(device_lib.list_local_devices())
2019-12-24 14:01:50.256937: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-12-24 14:01:50.434484: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2208000000 Hz
2019-12-24 14:01:50.447526: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55891e48e550 executing computations on platform Host. Devices:
2019-12-24 14:01:50.447601: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): Host, Default Version
2019-12-24 14:01:50.485013: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-24 14:01:50.531812: E tensorflow/stream_executor/cuda/cuda_driver.cc:318] failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error
2019-12-24 14:01:50.531869: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: blahablah
2019-12-24 14:01:50.531880: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: blablah
2019-12-24 14:01:50.531970: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: 440.33.1
2019-12-24 14:01:50.532006: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 440.33.1
2019-12-24 14:01:50.532016: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:310] kernel version seems to match DSO: 440.33.1
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 15977328373534175709
, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 11314831794072701371
physical_device_desc: "device: XLA_CPU device"
]
有人有什么错的想法吗？
当我做dpkg --list | grep nvidia时，我得到：
ii libnvidia-compute-435:amd64 435.21-0ubuntu0.18.04.2 amd64 NVIDIA libcompute package
ii nvidia-340 340.107-0ubuntu0.18.04.4 amd64 NVIDIA binary driver - version 340.107
ii nvidia-cuda-dev 9.1.85-3ubuntu1 amd64 NVIDIA CUDA development files
ii nvidia-cuda-doc 9.1.85-3ubuntu1 all NVIDIA CUDA and OpenCL documentation
ii nvidia-cuda-gdb 9.1.85-3ubuntu1 amd64 NVIDIA CUDA Debugger (GDB)
ii nvidia-cuda-toolkit 9.1.85-3ubuntu1 amd64 NVIDIA CUDA development toolkit
ii nvidia-modprobe 384.111-2 amd64 utility to load NVIDIA kernel modules and create device nodes
ii nvidia-opencl-dev:amd64 9.1.85-3ubuntu1 amd64 NVIDIA OpenCL development files
ii nvidia-profiler 9.1.85-3ubuntu1 amd64 NVIDIA Profiler for CUDA and OpenCL
ii nvidia-visual-profiler 9.1.85-3ubuntu1 amd64 NVIDIA Visual Profiler for CUDA and OpenCL
此外，nvidia-smi给出：
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 1060 Off | 00000000:01:00.0 Off | N/A |
| N/A 53C P0 24W / N/A | 357MiB / 6078MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1824 G /usr/lib/xorg/Xorg 160MiB |
| 0 1989 G /usr/bin/gnome-shell 118MiB |
| 0 11974 G /usr/lib/firefox/firefox 1MiB |
| 0 24077 G ...uest-channel-token=10867623928441435609 72MiB |
+-----------------------------------------------------------------------------+
我们将不胜感激。