clearml-agent/trains_agent/backend_api/config/default/agent.conf

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