tensorflow/stream_executor/cuda/cuda_driver.cc:328] 调用 cuInit 失败：CUDA_ERROR_UNKNOWN：未知错误

Question

我正在尝试将 GPU 与 Tensorflow 结合使用。我的 Tensorflow 版本是 2.4.1，我使用的是 Cuda 版本 11.2。这是 nvidia-smi.

的输出

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.39       Driver Version: 460.39       CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce MX110       Off  | 00000000:01:00.0 Off |                  N/A |
| N/A   52C    P0    N/A /  N/A |    254MiB /  2004MiB |      8%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1151      G   /usr/lib/xorg/Xorg                 37MiB |
|    0   N/A  N/A      1654      G   /usr/lib/xorg/Xorg                136MiB |
|    0   N/A  N/A      1830      G   /usr/bin/gnome-shell               68MiB |
|    0   N/A  N/A      5443      G   /usr/lib/firefox/firefox            0MiB |
|    0   N/A  N/A      5659      G   /usr/lib/firefox/firefox            0MiB |
+-----------------------------------------------------------------------------+

我遇到了一个奇怪的问题。以前，当我尝试使用 tf.config.list_physical_devices() 列出所有物理设备时，它识别了一个 cpu 和一个 gpu。之后我尝试在 GPU 上做一个简单的矩阵乘法。它失败并出现此错误：failed to synchronize cuda stream CUDA_LAUNCH_ERROR（错误代码是这样的，我忘了记录它）。但在那之后，当我再次从另一个终端尝试同样的事情时，它无法识别任何 GPU。这次，列出物理设备会产生以下结果：

>>> tf.config.list_physical_devices()
2021-04-11 18:56:47.504776: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-11 18:56:47.507646: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-04-11 18:56:47.534189: E tensorflow/stream_executor/cuda/cuda_driver.cc:328] failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error
2021-04-11 18:56:47.534233: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: debadri-HP-Laptop-15g-dr0xxx
2021-04-11 18:56:47.534244: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: debadri-HP-Laptop-15g-dr0xxx
2021-04-11 18:56:47.534356: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: 460.39.0
2021-04-11 18:56:47.534393: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 460.39.0
2021-04-11 18:56:47.534404: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:310] kernel version seems to match DSO: 460.39.0
[PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU')]

我的 OS 是 Ubuntu 20.04，Python 版本 3.8.5 和 Tensorflow，如前所述 2.4.1 和 Cuda 版本 11.2。我根据 these 说明安装了 cuda。一条附加信息；当我导入 tensorflow 时，它显示以下输出：

import tensorflow as tf
2021-04-11 18:56:07.716683: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0

我错过了什么？为什么之前能识别GPU却无法识别？

Answer 1

tldr：在安装 Nvidia 驱动程序之前禁用安全启动。

我有 exact 相同的错误，我花了很多时间试图弄清楚我是否错误地安装了 Tensorflow 相关的东西。经过数小时的问题解决后，我发现我的 NVIDIA 驱动程序出现了一些问题，因为我在设置 Ubuntu 20.4 时从未在 BIOS 中禁用安全启动。这是我的建议（我选择使用 Docker w/ Tensorflow，这样可以避免安装所有与 Cuda 相关的东西）——我希望它对你有用！

在您的 BIOS 中禁用安全启动
在 Ubuntu 20.4
根据nvidia-container-toolkit's page安装Docker。

curl https://get.docker.com | sh \
  && sudo systemctl --now enable docker

从同一页面安装 nvidia-container-toolkit。

distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
   && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
   && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

sudo apt-get update

sudo apt-get install -y nvidia-docker2

sudo systemctl restart docker

测试以确保它与

sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi

最后，在 Docker 支持 GPU 的情况下使用 Tensorflow！

docker run --gpus all -u $(id -u):$(id -g) -it -p 8888:8888 tensorflow/tensorflow:latest-gpu-jupyter jupyter notebook --ip=0.0.0.0

Answer 2

我刚刚创建了一个帐户，表示@Nate 的回答对我有用。我的设置和你一模一样，试了两天

我最后做的是

重新启动 - F10 到设置 - 安全 - BIOS 安全启动（或类似的东西，我记不太清了） - 禁用

然后有一些额外的确认步骤，但效果很好。我没有重新安装整个 Unbuntu。这对我来说在技术上有点太冒险了。

然后我尝试了 tf.config 行，我得到了这个：

2021-06-14 17:12:19.546509: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.1

2021-06-14 17:12:26.754680: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE4.1 SSE4.2 AVX AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2021-06-14 17:12:26.909679: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 3593460000 Hz

2021-06-14 17:12:26.910016: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55a8352501c0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:

2021-06-14 17:12:26.910040: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version

2021-06-14 17:12:26.972350: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1

2021-06-14 17:12:27.074861: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero

2021-06-14 17:12:27.075289: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: 
pciBusID: 0000:0c:00.0 name: GeForce GTX 1650 computeCapability: 7.5
coreClock: 1.665GHz coreCount: 14 deviceMemorySize: 3.81GiB deviceMemoryBandwidth: 119.24GiB/s

最后设备属性上有更多红线，但我得到了

Default GPU Device: /device:GPU:0

不知道为什么会这样，但确实有效。只需更改安全启动设置。

我没有足够的经验值来支持 Nate 的回答。我晚点回来。但是 he/she 确实提供了一个很好的解决方案。

Answer 3

禁用安全启动立即解决。无需重新安装任何东西。

> import tensorflow as tf
> tf.config.list_physical_devices("GPU")
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

tensorflow/stream_executor/cuda/cuda_driver.cc:328] 调用 cuInit 失败：CUDA_ERROR_UNKNOWN：未知错误

tensorflow/stream_executor/cuda/cuda_driver.cc:328] failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error

gpu

nvidia

python-3.x

tensorflow2.0