Skip to content

Document how to use TensorBoardLogger with fsspec #16320

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 5 commits into from
Mar 27, 2023
Merged

Document how to use TensorBoardLogger with fsspec #16320

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
21e9dc3
Document how to use TensorBoardLogger with fsspec
leoleoasd Jan 10, 2023
26d6189
Link to loggers api reference
leoleoasd Jan 11, 2023
ce0d9ad
add documents for tensorboard and csv logger
leoleoasd Mar 24, 2023
5711fb6
Merge branch 'master' into master
Borda Mar 24, 2023
e17f08b
Merge branch 'master' into master
Borda Mar 27, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 2 additions & 0 deletions docs/source-pytorch/api_references.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -81,6 +81,8 @@ core
~optimizer.LightningOptimizer


.. _loggers-api-references:

loggers
-------

Expand Down
3 changes: 2 additions & 1 deletion docs/source-pytorch/common/remote_fs.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,8 @@ Working with different filesystems can be accomplished by appending a protocol l
trainer = Trainer(default_root_dir="s3://my_bucket/data/")
trainer.fit(model)

You could pass custom paths to loggers for logging data.

For logging, remote filesystem support depends on the particular logger integration being used. Consult :ref:`the documentation of the individual logger <loggers-api-references>` for more details.

.. code-block:: python

Expand Down
2 changes: 2 additions & 0 deletions src/lightning/pytorch/loggers/csv_logs.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -42,6 +42,8 @@ class ExperimentWriter(_FabricExperimentWriter):
Currently, supports to log hyperparameters and metrics in YAML and CSV
format, respectively.

This logger supports logging to remote filesystems via ``fsspec``. Make sure you have it installed.

Args:
log_dir: Directory for the experiment logs
"""
Expand Down
5 changes: 4 additions & 1 deletion src/lightning/pytorch/loggers/tensorboard.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -46,12 +46,15 @@

class TensorBoardLogger(Logger, FabricTensorBoardLogger):
r"""
Log to local file system in `TensorBoard <https://www.tensorflow.org/tensorboard>`_ format.
Log to local or remote file system in `TensorBoard <https://www.tensorflow.org/tensorboard>`_ format.

Implemented using :class:`~tensorboardX.SummaryWriter`. Logs are saved to
``os.path.join(save_dir, name, version)``. This is the default logger in Lightning, it comes
preinstalled.

This logger supports logging to remote filesystems via ``fsspec``. Make sure you have it installed
and you don't have tensorflow (otherwise it will use tf.io.gfile instead of fsspec).

Example:

.. testcode::
Expand Down