# TRAINS-AGENT configuration file
api {
api_server: https://demoapi.trains.allegro.ai
web_server: https://demoapp.trains.allegro.ai
files_server: https://demofiles.trains.allegro.ai
# Credentials are generated in the webapp, https://demoapp.trains.allegro.ai/profile
# Overridden with os environment: TRAINS_API_ACCESS_KEY / TRAINS_API_SECRET_KEY
credentials {"access_key": "EGRTCO8JMSIGI6S39GTP43NFWXDQOW", "secret_key": "x!XTov_G-#vspE*Y(h$Anm&DIc5Ou-F)jsl$PdOyj5wG1&E!Z8"}
# verify host ssl certificate, set to False only if you have a very good reason
verify_certificate: True
}
agent {
# Set GIT user/pass credentials
# leave blank for GIT SSH credentials
git_user=""
git_pass=""
# unique name of this worker, if None, created based on hostname:process_id
# Overridden with os environment: TRAINS_WORKER_NAME
# worker_id: "trains-agent-machine1:gpu0"
worker_id: ""
# worker name, replaces the hostname when creating a unique name for this worker
# Overridden with os environment: TRAINS_WORKER_ID
# worker_name: "trains-agent-machine1"
worker_name: ""
# 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"
# 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/trains/api/pypi/public/simple"]
extra_index_url: []
# additional conda channels to use when installing with conda package manager
conda_channels: ["pytorch", "conda-forge", ]
},
# 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 (mostly pytorch versions)
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 used mapped into docker, for python package caching
docker_pip_cache = ~/.trains/pip-cache
# apt cache folder used mapped into docker, 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"
# optional arguments to pass to docker image
# arguments: ["--ipc=host"]
}
}
sdk {
# TRAINS - default SDK configuration
storage {
cache {
# Defaults to system temp folder / cache
default_base_dir: "~/.trains/cache"
}
direct_access: [
# Objects matching are considered to be available for direct access, i.e. they will not be downloaded
# or cached, and any download request will return a direct reference.
# Objects are specified in glob format, available for url and content_type.
{ url: "file://*" } # file-urls are always directly referenced
]
}
metrics {
# History size for debug files per metric/variant. For each metric/variant combination with an attached file
# (e.g. debug image event), file names for the uploaded files will be recycled in such a way that no more than
# X files are stored in the upload destination for each metric/variant combination.
file_history_size: 100
# Max history size for matplotlib imshow files per plot title.
# File names for the uploaded images will be recycled in such a way that no more than
# X images are stored in the upload destination for each matplotlib plot title.
matplotlib_untitled_history_size: 100
# Settings for generated debug images
images {
format: JPEG
quality: 87
subsampling: 0
}
# Support plot-per-graph fully matching Tensorboard behavior (i.e. if this is set to True, each series should have its own graph)
tensorboard_single_series_per_graph: False
}
network {
metrics {
# Number of threads allocated to uploading files (typically debug images) when transmitting metrics for
# a specific iteration
file_upload_threads: 4
# Warn about upload starvation if no uploads were made in specified period while file-bearing events keep
# being sent for upload
file_upload_starvation_warning_sec: 120
}
iteration {
# Max number of retries when getting frames if the server returned an error (http code 500)
max_retries_on_server_error: 5
# Backoff factory for consecutive retry attempts.
# SDK will wait for {backoff factor} * (2 ^ ({number of total retries} - 1)) between retries.
retry_backoff_factor_sec: 10
}
}
aws {
s3 {
# S3 credentials, used for read/write access by various SDK elements
# default, used for any bucket not specified below
key: ""
secret: ""
region: ""
credentials: [
# specifies key/secret credentials to use when handling s3 urls (read or write)
# {
# bucket: "my-bucket-name"
# key: "my-access-key"
# secret: "my-secret-key"
# },
# {
# # This will apply to all buckets in this host (unless key/value is specifically provided for a given bucket)
# host: "my-minio-host:9000"
# key: "12345678"
# secret: "12345678"
# multipart: false
# secure: false
# }
]
}
boto3 {
pool_connections: 512
max_multipart_concurrency: 16
}
}
google.storage {
# # Default project and credentials file
# # Will be used when no bucket configuration is found
# project: "trains"
# credentials_json: "/path/to/credentials.json"
# # Specific credentials per bucket and sub directory
# credentials = [
# {
# bucket: "my-bucket"
# subdir: "path/in/bucket" # Not required
# project: "trains"
# credentials_json: "/path/to/credentials.json"
# },
# ]
}
azure.storage {
# containers: [
# {
# account_name: "trains"
# account_key: "secret"
# # container_name:
# }
# ]
}
log {
# debugging feature: set this to true to make null log propagate messages to root logger (so they appear in stdout)
null_log_propagate: False
task_log_buffer_capacity: 66
# disable urllib info and lower levels
disable_urllib3_info: True
}
development {
# Development-mode options
# dev task reuse window
task_reuse_time_window_in_hours: 72.0
# Run VCS repository detection asynchronously
vcs_repo_detect_async: True
# Store uncommitted git/hg source code diff in experiment manifest when training in development mode
# This stores "git diff" or "hg diff" into the experiment's "script.requirements.diff" section
store_uncommitted_code_diff_on_train: True
# Support stopping an experiment in case it was externally stopped, status was changed or task was reset
support_stopping: True
# Default Task output_uri. if output_uri is not provided to Task.init, default_output_uri will be used instead.
default_output_uri: ""
# Development mode worker
worker {
# Status report period in seconds
report_period_sec: 2
# ping to the server - check connectivity
ping_period_sec: 30
# Log all stdout & stderr
log_stdout: True
}
}
}