Hi,
after running a hyperparameter search with PyTorch and visualizing the results in Tensorboard, I want to read out the hyperparameters from Tensorboard programatically.
My folder structure is
- all_runs
- run1
- Loss_trainingloss
- 1634168941.9091413 (or some other timestamp) events.out.tfevents.1634168941
- events.out.tfevents.1634135651
- run2
- run3
- run1
and I can easily read tensorboard time-series like e.g. the loss curve with code like this:
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
def read_eventfile(filepath, tag):
event_accumulator = EventAccumulator(filepath)
event_accumulator.Reload()
events = event_accumulator.Scalars(tag)
y = [x.value for x in events]
return y
train_loss_curve = read_eventfile(path_to_event_folder, "Loss_trainingloss")
However I struggle to find an access to the hparams of each run, which are correctly displayed in tensorboard. Anybody knows how this can be done?
Thanks!