Adopt or not to adopt tensorboard native hyperparameters recording #184
Description
Problem Description
The current way of adding hyperparameters is to do it via markdown text:
writer = SummaryWriter(f"runs/{run_name}")
writer.add_text(
"hyperparameters",
"|param|value|\n|-|-|\n%s" % ("\n".join([f"|{key}|{value}|" for key, value in vars(args).items()])),
)It is however to use the tensorboard native hyperparameters plugin, which unfortunately also has ugly code... see pytorch/pytorch#37738 (comment)
writer = SummaryWriter(f"runs/{run_name}")
from torch.utils.tensorboard.summary import hparams
exp, ssi, sei = hparams(vars(args), metric_dict={"charts/episodic_return": 0})
writer.file_writer.add_summary(exp)
writer.file_writer.add_summary(ssi)
writer.file_writer.add_summary(sei) produces the following demo, which I guess is pretty cool
Screen.Recording.2022-05-11.at.11.45.43.PM.mov
Checklist
- I have installed dependencies via
poetry install(see CleanRL's installation guideline. - I have checked that there is no similar issue in the repo (required)
CC @araffin and @Miffyli and who might be interested in this hidden feature.