Start a Google Cloud Deep Learning machine with PyTorch 1.4 and Debian 9 and run the next command (the hostname of the machine will be used to tag the experiment):
TAG=$(hostname) bash <(curl -s "https://raw.githubusercontent.com/linhd-postdata/alberti-template/master/run.sh")
Parameters (as envornment variables):
TAG
. How to tag the experiments. e.g.,alberti-roberta-base-es
. If should default to the hostname.NFS
. Network filesystem to mount and save all the experiment runs and data to. If not given, local filesystem will be used, so be careful with the volumes termination policy.NODEPS
. When set, no dependencies will be installed. This is useful for debugging.SCRIPT
. The script to execute. It must be defined inrun.sh
. Parameters to the script must be passed in with a prefix. For example, if theSCRIPT
isstanzas
, all paremeters passed in must be prefixed withST_
by convention. An examplestanzas-evaluation.py
is added to fill in the blanks.