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Usage instructions for experiment manager
This document describes to how use the experiment manager.
Overview
The experiment manager is a CLI tool that helps keep track of and annotate training runs. It works by maintaining the following directory structure:
out/
|_____current_run.txt
|_____run1/
|_____run2/
|_____run3/
.
.
.
where runN
contains the results and logs for a single training run. The folder names are sortable timestamps to aid navigation and are suffixed by the training run's title. The timestamp for each folder is also the run's ID. The folder name for the current/active run is stored in current_run.txt
.
Each training run folder contains a YAML file with name, description and experiment group name. The experiment manager can:
- Show run metadata
- Create a new run
- Edit/delete an existing run
- Pick an existing run to be the active run
Each run can be annotated with a title, description and group name. The group name is used to group together runs when displaying a list of all runs.
Run python -m exp_manager -h
to see a list of commands:
usage: exp_manager.py [-h] [--exp_dir EXP_DIR] {show,new,edit,delete,set} ...
positional arguments:
{show,new,edit,delete,set}
show show run(s)
new create new run
edit edit existing run
delete delete a run
set set a run as the current run
optional arguments:
-h, --help show this help message and exit
--exp_dir EXP_DIR parent directory containing all runs
Each command has a help option as well. e.g. run python -m exp_manager -h
usage: exp_manager.py show [-h] [--all | --current | --id ID]
optional arguments:
-h, --help show this help message and exit
--all, -a show all runs
--current, -c show current run
--id ID run ID
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