mirror of
https://github.com/clearml/clearml-agent
synced 2025-01-31 17:16:51 +00:00
117 lines
4.6 KiB
Plaintext
117 lines
4.6 KiB
Plaintext
{
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# unique name of this worker, if None, created based on hostname:process_id
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# Override with os environment: TRAINS_WORKER_ID
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# worker_id: "trains-agent-machine1:gpu0"
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worker_id: ""
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# worker name, replaces the hostname when creating a unique name for this worker
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# Override with os environment: TRAINS_WORKER_NAME
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# worker_name: "trains-agent-machine1"
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worker_name: ""
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# Set GIT user/pass credentials (if user/pass are set, GIT protocol will be set to https)
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# leave blank for GIT SSH credentials (set force_git_ssh_protocol=true to force SSH protocol)
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# git_user: ""
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# git_pass: ""
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# Force GIT protocol to use SSH regardless of the git url (Assumes GIT user/pass are blank)
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force_git_ssh_protocol: false
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# Set the python version to use when creating the virtual environment and launching the experiment
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# Example values: "/usr/bin/python3" or "/usr/local/bin/python3.6"
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# The default is the python executing the trains_agent
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python_binary: ""
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# select python package manager:
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# currently supported pip and conda
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# poetry is used if pip selected and repository contains poetry.lock file
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package_manager: {
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# supported options: pip, conda, poetry
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type: pip,
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# specify pip version to use (examples "<20", "==19.3.1", "", empty string will install the latest version)
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pip_version: "<20.2",
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# virtual environment inheres packages from system
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system_site_packages: false,
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# install with --upgrade
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force_upgrade: false,
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# additional artifact repositories to use when installing python packages
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# extra_index_url: ["https://allegroai.jfrog.io/trainsai/api/pypi/public/simple"]
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# additional conda channels to use when installing with conda package manager
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conda_channels: ["defaults", "conda-forge", "pytorch", ]
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# set to True to support torch nightly build installation,
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# notice: torch nightly builds are ephemeral and are deleted from time to time
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torch_nightly: false,
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},
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# target folder for virtual environments builds, created when executing experiment
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venvs_dir = ~/.trains/venvs-builds
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# cached git clone folder
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vcs_cache: {
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enabled: true,
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path: ~/.trains/vcs-cache
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},
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# use venv-update in order to accelerate python virtual environment building
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# Still in beta, turned off by default
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venv_update: {
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enabled: false,
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},
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# cached folder for specific python package download (used for pytorch package caching)
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pip_download_cache {
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enabled: true,
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path: ~/.trains/pip-download-cache
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},
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translate_ssh: true,
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# reload configuration file every daemon execution
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reload_config: false,
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# pip cache folder mapped into docker, used for python package caching
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docker_pip_cache = ~/.trains/pip-cache
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# apt cache folder mapped into docker, used for ubuntu package caching
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docker_apt_cache = ~/.trains/apt-cache
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# optional arguments to pass to docker image
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# these are local for this agent and will not be updated in the experiment's docker_cmd section
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# extra_docker_arguments: ["--ipc=host", ]
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# optional shell script to run in docker when started before the experiment is started
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# extra_docker_shell_script: ["apt-get install -y bindfs", ]
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# set to true in order to force "docker pull" before running an experiment using a docker image.
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# This makes sure the docker image is updated.
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docker_force_pull: false
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default_docker: {
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# default docker image to use when running in docker mode
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image: "nvidia/cuda:10.1-runtime-ubuntu18.04"
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# optional arguments to pass to docker image
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# arguments: ["--ipc=host", ]
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}
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# set the initial bash script to execute at the startup of any docker.
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# all lines will be executed regardless of their exit code.
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# {python_single_digit} is translated to 'python3' or 'python2' according to requested python version
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# docker_init_bash_script = [
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# "echo 'Binary::apt::APT::Keep-Downloaded-Packages \"true\";' > /etc/apt/apt.conf.d/docker-clean",
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# "chown -R root /root/.cache/pip",
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# "apt-get update",
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# "apt-get install -y git libsm6 libxext6 libxrender-dev libglib2.0-0",
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# "(which {python_single_digit} && {python_single_digit} -m pip --version) || apt-get install -y {python_single_digit}-pip",
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# ]
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# cuda versions used for solving pytorch wheel packages
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# should be detected automatically. Override with os environment CUDA_VERSION / CUDNN_VERSION
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# cuda_version: 10.1
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# cudnn_version: 7.6
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}
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