docker - 找不到 docker 镜像

Question

我是 docker 新手，最近正在学习它。当我试图将它用于我的一项任务时。我收到以下错误，我在任何地方都没有找到任何好的解决方案。在尝试链接中给出的以下命令之前，我已经正确安装了 nvidia-docker 并构建了映像。nvidia-docker 版本是：

ii  nvidia-docker  1.0.1-1  amd64  NVIDIA Docker container tools

这是我运行上述命令后得到的错误。

Unable to find image 'retinanet:latest' locallydocker: Error response from 
daemon: pull access denied for retinanet, repository does not exist or may 
require 'docker login': denied: requested access to the resource is denied.

以下是我构建图像后得到的。

$ sudo docker build -t retinanet:latest retinanet/
Sending build context to Docker daemon  208.9kB
Step 1/3 : FROM nvcr.io/nvidia/pytorch:19.05-py3
---> 7e98758d4777
Step 2/3 : COPY . retinanet/
---> Using cache
---> a32277843b1f
Step 3/3 : RUN pip install --no-cache-dir -e retinanet/
---> Using cache
---> a0195cf77814
Successfully built a0195cf77814
Successfully tagged retinanet:latest

以下是我在 docker images 之后得到的结果。

$ sudo docker images
REPOSITORY               TAG                 IMAGE ID            CREATED             SIZE
<none>                   <none>              7cd7d8e7cedc        2 days ago          
7.59GB
nvcr.io/nvidia/pytorch   19.09-py3           9d6f9ccfbe31        6 weeks ago         9.15GB
nvidia/cuda              9.0-base            1443caa429f9        7 weeks ago         137MB
retinanet                latest              a0195cf77814        7 weeks ago         7.59GB
nvcr.io/nvidia/pytorch   19.07-py3           71df86c191f8        3 months ago        8.32GB
nvcr.io/nvidia/pytorch   19.05-py3           7e98758d4777        5 months ago        7.55GB

当我使用命令时

 docker run -ti retinanet:latest

工作区已创建，但我收到以下警告，表明我没有使用 GPU 工具。

WARNING: The NVIDIA Driver was not detected.  GPU functionality will not be available.
Use 'nvidia-docker run' to start this container; see https://github.com/NVIDIA/nvidia-docker/wiki/nvidia-docker .

NOTE: MOFED driver for multi-node communication was not detected.
  Multi-node communication performance may be reduced.

NOTE: The SHMEM allocation limit is set to the default of 64MB.  This may be
insufficient for PyTorch.  NVIDIA recommends the use of the following flags:
nvidia-docker run --ipc=host ...

注意：我按照此链接的解决方案进行操作，但对我的情况没有帮助。任何想法和建议都会非常有帮助。提前致谢。

标签： dockernvidia-dockerretinanet