Thanks, this is a massive lifesaver. I think there would definitely be a benefit to rewriting the PyTorch Tensorboard interface to make it more intuitive and increasing the detail of documentation. It shouldn’t be that hard to be able to log metrics on a per-epoch basis with hyperparameters.
“Something that I’m not sure if it’s a bug or not is that in the original code, any scalars are logged to the log_dir whilst hyper parameters are logged in their own directory and given a run_name.” As for this part, this also seems to be a weird default behavior of the add_hyperparameters option to use the log_dir along with the current timestamp (time.time()). See pytorch/writer.py at bf88a4dad5b3c06f43a9ce07a51ec0ab0dbfe2d3 · pytorch/pytorch · GitHub 23. A quick fix is to just delete those lines and just use the original log_dir.