16

我有一个加载 Pytorch 模型的容器。每次我尝试启动它时，我都会收到此错误：

Traceback (most recent call last):
  File "server/start.py", line 166, in <module>
    start()
  File "server/start.py", line 94, in start
    app.register_blueprint(create_api(), url_prefix="/api/1")
  File "/usr/local/src/skiff/app/server/server/api.py", line 30, in create_api
    atomic_demo_model = DemoModel(model_filepath, comet_dir)
  File "/usr/local/src/comet/comet/comet/interactive/atomic_demo.py", line 69, in __init__
    model = interactive.make_model(opt, n_vocab, n_ctx, state_dict)
  File "/usr/local/src/comet/comet/comet/interactive/functions.py", line 98, in make_model
    model.to(cfg.device)
  File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 381, in to
    return self._apply(convert)
  File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 187, in _apply
    module._apply(fn)
  File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 187, in _apply
    module._apply(fn)
  File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 193, in _apply
    param.data = fn(param.data)
  File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 379, in convert
    return t.to(device, dtype if t.is_floating_point() else None, non_blocking)
  File "/usr/local/lib/python3.7/site-packages/torch/cuda/__init__.py", line 161, in _lazy_init
    _check_driver()
  File "/usr/local/lib/python3.7/site-packages/torch/cuda/__init__.py", line 82, in _check_driver
    http://www.nvidia.com/Download/index.aspx""")
AssertionError:
Found no NVIDIA driver on your system. Please check that you
have an NVIDIA GPU and installed a driver from
http://www.nvidia.com/Download/index.aspx

我知道那nvidia-docker2行得通。

$ docker run --runtime=nvidia --rm nvidia/cuda:9.0-base nvidia-smi
Tue Jul 16 22:09:40 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.39       Driver Version: 418.39       CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| 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 RTX 208...  Off  | 00000000:1A:00.0 Off |                  N/A |
|  0%   44C    P0    72W / 260W |      0MiB / 10989MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  GeForce RTX 208...  Off  | 00000000:1B:00.0 Off |                  N/A |
|  0%   44C    P0    66W / 260W |      0MiB / 10989MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  GeForce RTX 208...  Off  | 00000000:1E:00.0 Off |                  N/A |
|  0%   44C    P0    48W / 260W |      0MiB / 10989MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  GeForce RTX 208...  Off  | 00000000:3E:00.0 Off |                  N/A |
|  0%   41C    P0    54W / 260W |      0MiB / 10989MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   4  GeForce RTX 208...  Off  | 00000000:3F:00.0 Off |                  N/A |
|  0%   42C    P0    48W / 260W |      0MiB / 10989MiB |      1%      Default |
+-------------------------------+----------------------+----------------------+
|   5  GeForce RTX 208...  Off  | 00000000:41:00.0 Off |                  N/A |
|  0%   42C    P0     1W / 260W |      0MiB / 10989MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

但是，我不断收到上述错误。

我尝试了以下方法：

  1. 设置"default-runtime": nvidia_/etc/docker/daemon.json

  2. 使用docker run --runtime=nvidia <IMAGE_ID>

  3. 将以下变量添加到我的 Dockerfile 中：

ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
LABEL com.nvidia.volumes.needed="nvidia_driver"

我希望这个容器能够运行——我们有一个没有这些问题的生产版本。而且我知道 Docker 可以找到驱动程序，如上面的输出所示。有任何想法吗？

4

3 回答 3

5

为了让 docker 使用主机 GPU 驱动程序和 GPU，需要执行一些步骤。

  • 确保在主机系统上安装了 nvidia 驱动程序
  • 按照此处的步骤设置 nvidia 容器工具包
  • 确保镜像中安装了cuda、cudnn
  • 运行带有--gpus标志的容器（如上面的链接中所述）

我猜你已经完成了前 3 点，因为nvidia-docker2它正在工作。因此，由于您的运行命令中没有--gpus标志，这可能是问题所在。

我通常使用以下命令运行我的容器

docker run --name <container_name> --gpus all -it <image_name>

-it只是容器是交互式的并启动了一个 bash 环境。

于 2020-01-08T06:48:45.507 回答
4

我得到了同样的错误。在尝试了多种解决方案后，我发现了以下内容

docker run -ti --runtime=nvidia -e NVIDIA_DRIVER_CAPABILITIES=compute,utility -e NVIDIA_VISIBLE_DEVICES=all <image_name>
于 2020-04-24T08:38:03.660 回答
0

对我来说，我是从一个香草ubuntu基础 docker 图像运行的，即

FROM ubuntu

更改为 Nvidia 提供的 Docker 基础映像为我解决了这个问题：

FROM nvidia/cuda:11.2.1-runtime-ubuntu20.04
于 2021-03-11T18:41:38.617 回答