Lightning-AI / Lightning-AI/pytorch-lightning
Group the metrics in Tensorboard
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Description
### Bug description
I cannot understand what needs to be done to group the graphs for the same metric:
```python
self.log_dict(
dictionary={'losses/a': 0.1, 'losses/b': 0.2},
batch_size=1,
add_dataloader_idx=False,
prog_bar=False,
on_step=True,
on_epoch=False,
sync_dist=False,
rank_zero_only=True,
)
self.log(
name='losses/c',
value=0.3,
batch_size=1,
add_dataloader_idx=False,
prog_bar=False,
on_step=True,
on_epoch=False,
sync_dist=False,
rank_zero_only=True,
)
self.log(
name='losses/d',
value=0.3,
batch_size=1,
add_dataloader_idx=False,
prog_bar=False,
on_step=True,
on_epoch=False,
sync_dist=False,
rank_zero_only=True,
)
```
Result in:
I would really like to see all 4 lines on the same plot.
version: 2.6.1
### What version are you seeing the problem on?
v2.5
### Reproduced in studio
_No response_
### How to reproduce the bug
```python
self.log_dict(
dictionary={'losses/a': 0.1, 'losses/b': 0.2},
batch_size=1,
add_dataloader_idx=False,
prog_bar=False,
on_step=True,
on_epoch=False,
sync_dist=False,
rank_zero_only=True,
)
self.log(
name='losses/c',
value=0.3,
batch_size=1,
add_dataloader_idx=False,
prog_bar=False,
on_step=True,
on_epoch=False,
sync_dist=False,
rank_zero_only=True,
)
self.log(
name='losses/d',
value=0.3,
batch_size=1,
add_dataloader_idx=False,
prog_bar=False,
on_step=True,
on_epoch=False,
sync_dist=False,
rank_zero_only=True,
)
```
### Error messages and logs
```
# Error messages and logs here please
```
### Environment
Current environment
```
#- PyTorch Lightning Version: 2.6.1
#- PyTorch Version: 2.9.1
#- Python version: 3.12
#- OS: Linux
#- CUDA/cuDNN version: 13.0
#- How you installed Lightning: poetry
```
### More info
_No response_
cc @ethanwharris @lantiga
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The report does not name a file or test. Start by reproducing the behavior with the provided self.log_dict and self.log calls, then trace the TensorBoard logging entry points; done means the four losses series appear together on one plot without changing the reported metric names.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- data-visualization, observability
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100