tensorflow / tensorflow/tensorboard
Tensorboard metrics not loaded properly
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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.
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()
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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.
Assessment
- Tech stack
- python, pytorch, typescript
- Domain
- data-visualization, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100