Tensorboard metrics not loaded properly

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
30/100
Issue type
Bug
Clarity
Needs clarification
Activity status
Stale
Tech stack
python, pytorch, typescript
Domain
data-visualization, machine-learning

Research direction

No file or test is named in the report. Start by reproducing the supplied torch.utils.tensorboard example with add_scalar and add_hparams, then trace how TensorBoard loads the recorded validation/min_loss metric. Done means the scalar appears in the TensorBoard metrics column.

Written by the indexing model from the issue text.

Description

I have the problem that in Tensorboard the metrics are not loaded correctly (the column is always empty), although the scalars are saved correctly. I am working with torch.utils.tensorboard.

tensorboard_metrics

Relevant code:

writer = SummaryWriter(log_dir=f'./logs/studies/{study_name}/')

In the training loop:
writer.add_scalar(tag='validation/min_loss', scalar_value=min_val_loss, global_step=trial.number)

Add the hyperparameter to the summary writer (args_dict is a dictionary with all hyperparameters)
writer.add_hparams(hparam_dict=args_dict, metric_dict={'validation/min_loss': min_val_loss}, run_name=run_name)
writer.close()

Dominant language
TypeScript
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Merged PRs (30d)
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