Include run_name in training logs for better run traceability #101
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Description
Previously, during training, the
on_policy_runnerlogging output did not display the current run name, making it harder to distinguish logs between different training sessions when multiple runs were launched in succession or in parallel.To improve the training log clarity and traceability, I added support to display the configured
run_namein the logging output ofrsl_rl/runners/on_policy_runner.py.If the
run_namefield is specified in the configuration—such as in the Isaac Lab training example:./isaaclab.sh -p scripts/reinforcement_learning/rsl_rl/train.py \ --task Isaac-Cartpole-v0 --run_name cartpole_rsl_rl—the run name will now appear in each log update under the label "Run name:":
This enhancement helps users quickly identify the corresponding training session, which is especially useful when monitoring multiple or long-running experiments.
This addition is optional and non-intrusive: if
run_nameis not set, the log display remains unchanged.What’s Changed
run_nameadded to training logs inon_policy_runner.py.run_nameis conditionally fetched fromself.cfgand formatted neatly using the same padded alignment style as other log fields.run_nameis not defined.Type of Change
Checklist
pre-commit run --all-filesand all pre-commit checks passrun_namewhen providedrun_nameis not set)