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Logging to existing object#

You can resume logging to an already existing run or other Neptune object by passing its ID at initialization. This lets you add new data or visualizations to a previously closed run and facilitates multi-stage training.

To resume a run or other object:

  1. Obtain the Neptune ID of the object to resume.

    • Each object's ID is stored in the sys/id field.
    • You can see it displayed in the leftmost column of the table view.
    • If the object has been initialized in the code, you can obtain it programmatically with

      object_id = object["sys/id"].fetch()
  2. Initialize the object with the ID:

    run = neptune.init_run(
    model = neptune.init_model(
    model_version = neptune.init_model_version(
    project = neptune.init_project(
        name="workspace-name/project-name", # (1)
    1. The full project name. For example, "ml-team/classification". To copy it, navigate to the project settingsProperties.
  3. Log metadata to the object as you normally would.

    You can override existing fields, delete fields, or create new ones.


import as neptune

run = neptune.init_run(with_id="CLS-123")

# Download snapshot of model weights

# 450 is the epoch from where you want to resume training process
checkpoint = 450

# Continue training as usual
for epoch in range(checkpoint, 1000):

Good to know

  • There is no limit to the number of times you can resume an object.
  • 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_files argument of the init_run() call. For details, see Logging source code.

See in Neptune