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@@ -3144,16 +3144,25 @@ <h2>Create a GPU instance<a class="headerlink" href="#create-a-gpu-instance" tit
 </div>
 <div class="section" id="environment-setup">
 <h2>Environment Setup<a class="headerlink" href="#environment-setup" title="Permalink to this headline">¶</a></h2>
+<p>Make sure you have cuda driver installed on the host.</p>
 <div class="section" id="id21">
 <h3>Docker<a class="headerlink" href="#id21" title="Permalink to this headline">¶</a></h3>
-<p>Pytorch/XLA currently publish prebuilt docker images and wheels with cuda11.7/8 and python 3.8. We recommend users to create a docker container with corresponding config. For a full list of docker images and wheels, please refer to <a class="reference external" href="https://github.com/pytorch/xla#available-docker-images-and-wheels">this doc</a>.</p>
+<p>Pytorch/XLA currently publish prebuilt docker images and wheels with cuda11.8/12.1 and python 3.8. We recommend users to create a docker container with corresponding config. For a full list of docker images and wheels, please refer to <a class="reference external" href="https://github.com/pytorch/xla#available-docker-images-and-wheels">this doc</a>.</p>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span>sudo docker pull us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.8_cuda_12.1
-sudo apt-get install -y apt-transport-https ca-certificates curl gnupg-agent    software-properties-common
-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 &amp;&amp; sudo apt-get install -y nvidia-container-toolkit
+
+# Installing the NVIDIA Container Toolkit per https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
+# For example
+curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
+  &amp;&amp; curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
+    sed &#39;s#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g&#39; | \
+    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
+sudo apt-get update
+sudo apt-get install -y nvidia-container-toolkit
+
+# Configuring the NVIDIA Container Toolkit
+sudo nvidia-ctk runtime configure --runtime=docker
 sudo systemctl restart docker
+
 sudo docker run --shm-size=16g --net=host --gpus all -it -d us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:nightly_3.8_cuda_12.1 bin/bash
 sudo docker exec -it $(sudo docker ps | awk &#39;NR==2 { print $1 }&#39;) /bin/bash
 </pre></div>
@@ -3228,12 +3237,20 @@ <h2>Develop PyTorch/XLA on a GPU instance (build PyTorch/XLA from source with GP
 <li><p>Inside a GPU VM, create a docker container from a development docker image. For example:</p></li>
 </ol>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span>sudo docker pull us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/development:3.8_cuda_12.1
-sudo apt-get install -y apt-transport-https ca-certificates curl gnupg-agent    software-properties-common
-distribution=$(. /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 &amp;&amp; sudo apt-get install -y nvidia-container-toolkit
+
+# Installing the NVIDIA Container Toolkit per https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
+# For example
+curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
+  &amp;&amp; curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
+    sed &#39;s#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g&#39; | \
+    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
+sudo apt-get update
+sudo apt-get install -y nvidia-container-toolkit
+
+# Configuring the NVIDIA Container Toolkit
+sudo nvidia-ctk runtime configure --runtime=docker
 sudo systemctl restart docker
+
 sudo docker run --shm-size=16g --net=host --gpus all -it -d us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/development:3.8_cuda_12.1
 sudo docker exec -it $(sudo docker ps | awk &#39;NR==2 { print $1 }&#39;) /bin/bash
 </pre></div>

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