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# https://aimstack.io/
# example usage in lightning module:
# https://github.com/aimhubio/aim/blob/main/examples/pytorch_lightning_track.py
# open the Aim UI with the following command (run in the folder containing the `.aim` folder):
# `aim up`
aim:
_target_: aim.pytorch_lightning.AimLogger
repo: ${paths.root_dir} # .aim folder will be created here
# repo: "aim://ip_address:port" # can instead provide IP address pointing to Aim remote tracking server which manages the repo, see https://aimstack.readthedocs.io/en/latest/using/remote_tracking.html#
# aim allows to group runs under experiment name
experiment: null # any string, set to "default" if not specified
train_metric_prefix: "train/"
val_metric_prefix: "val/"
test_metric_prefix: "test/"
# sets the tracking interval in seconds for system usage metrics (CPU, GPU, memory, etc.)
system_tracking_interval: 10 # set to null to disable system metrics tracking
# enable/disable logging of system params such as installed packages, git info, env vars, etc.
log_system_params: true
# enable/disable tracking console logs (default value is true)
capture_terminal_logs: false # set to false to avoid infinite console log loop issue https://github.com/aimhubio/aim/issues/2550
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