Resume a run#
To access or update an existing run, you can reinitialize it by passing its ID to the
This lets you:
- Add new data (such as visualizations or evaluation metrics) to a previously closed run
- Do multi-stage training more easily
- Overwrite a field with a new value
- Delete data from the run
- Fetch metadata in read-only mode
Good to know
- There is no limit to the number of times you can resume a run.
The Python file from which a run is resumed is not snapshotted by default.
However, you can upload it by providing the path to the
source_filesargument of the
init_run()call. For details, see Logging source code.
To resume a run:
Obtain the Neptune ID of the run.
If the run is already initialized in the code, you can obtain it programmatically with:
Initialize the run with the ID:
Interact with the run as you normally would.
You can overwrite existing fields, delete fields, or create new ones.
Continue logging to an existing run#
You can update an existing run with new metadata by creating new namespace and fields.
Start by reinitializing the run in your code:
Then use the
run object to continue logging metadata as needed.
Editing existing metadata#
To edit the value of an existing field, you overwrite it with different data of the same type.
The value of the
"learning_rate" field has been changed to
0.02 instead of
- Learn more: Overwriting logged metadata
Deleting metadata from a run#
Accessing a run in read only mode#
If you're just fetching metadata and not logging anything new, you can reinitialize the run in read only mode. This ensures that the run's metadata won't be modified.