title: Unable to find docker image
body: <p>I am new to docker and learning about it recently. When I was trying to use it for one of my assignments. I got the following error of which I did not find any good solution anywhere.
  I have properly installed nvidia-docker and build the image before trying out the following command as given in the <a href="https://github.com/NVIDIA/nvidia-docker" rel="nofollow noreferrer">link</a>.
  The nvidia-docker version is:</p>
  
  <pre><code>ii  nvidia-docker  1.0.1-1  amd64  NVIDIA Docker container tools
  </code></pre>
  
  <p>This is the error I got after running the above command.</p>
  
  <pre><code>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.
  </code></pre>
  
  <p>The following is what I got after building the image.</p>
  
  <pre><code>$ 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
  ---&gt; 7e98758d4777
  Step 2/3 : COPY . retinanet/
  ---&gt; Using cache
  ---&gt; a32277843b1f
  Step 3/3 : RUN pip install --no-cache-dir -e retinanet/
  ---&gt; Using cache
  ---&gt; a0195cf77814
  Successfully built a0195cf77814
  Successfully tagged retinanet:latest
  </code></pre>
  
  <p>The following is the result I got after docker images.</p>
  
  <pre><code>$ sudo docker images
  REPOSITORY               TAG                 IMAGE ID            CREATED             SIZE
  &lt;none&gt;                   &lt;none&gt;              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
  </code></pre>
  
  <p>When I use the command</p>
  
  <pre><code> docker run -ti retinanet:latest
  </code></pre>
  
  <p>The workspace is created but I get the following warnings which indicates that I am not utilizing the GPU facility.</p>
  
  <pre><code>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 ...
  </code></pre>
  
  <p>Note: I followed the solution to this <a href="http://docker%20run%20--rm%20-v%20%22$(pwd)%22:/foo%20busybox" rel="nofollow noreferrer">link</a> but it is not helpful in my case.
  Any ideas and suggestions would be very helpful. Thanks in advance.</p>