Dockerfile for Cloud ML

Dockerfile

FROM runpod/pytorch:2.2.1-py3.10-cuda12.1.1-devel-ubuntu22.04

RUN    apt-get update -y \
    && apt-get install -y htop jq gh vim git-lfs tmux tree \
    && git lfs install \
    && curl -L 'https://code.visualstudio.com/sha/download?build=stable&os=cli-alpine-x64' --output /tmp/vscode_cli.tar.gz \
    && tar -xf /tmp/vscode_cli.tar.gz -C /usr/bin --no-same-owner \
    && rm /tmp/vscode_cli.tar.gz \
    && curl -L 'https://gist.github.com/wayhoww/8ebbcf31d95ae66c9828e3fba6866dfd/raw' --output /usr/bin/sendmail \
    && chmod +x /usr/bin/sendmail \
    && pip install matplotlib scipy pandas scikit-learn

COPY start /usr/bin/start

ENV VSCODE_CLI_USE_FILE_KEYCHAIN=1 VSCODE_CLI_DISABLE_KEYCHAIN_ENCRYPT=1 TZ="Asia/Shanghai"

WORKDIR /workspace

CMD ["/usr/bin/start"]

start

#!/bin/bash

trap 'bash /workspace/.local/sigterm_callback.sh' SIGTERM

# if RUNPOD_POD_ID is set, then get name from api
if [ -z "$RUNPOD_POD_ID" ]; then
  name='cloud-ml-instance'
else
  name=$(curl --request POST \
    --header 'content-type: application/json' \
    --url 'https://api.runpod.io/graphql?api_key='$RUNPOD_API_KEY \
    --data '{"query": "query Pod { pod(input: {podId: \"'$RUNPOD_POD_ID'\"}) { name } }"}')
  name=$(echo $name | jq -r '.data.pod.name')
fi

export PATH=$PATH:/workspace/.local/bin
export RUNPOD_POD_NAME=$name
echo "$name" > /etc/podname

if [ -f "/workspace/.local/setup-env.sh" ]; then
    source /workspace/.local/setup-env.sh
fi

code tunnel --name $name --cli-data-dir /workspace/.vscode/cli-$name/ --server-data-dir /workspace/.vscode-server --extensions-dir /workspace/.vscode-server --accept-server-license-terms &

if [ -n "$1" ]; then
    echo "Running command: $*"
    echo "$*" > /etc/command
    bash -c "$*" &
fi

wait