neptune-sacred 1.0.0

Neptune.ai sacred integration library

Neptune + Sacred Integration

Neptune is a tool used for experiment tracking, model registry, data versioning, and live model monitoring. This integration lets you use it as a UI (frontend) for the experiments you track in Sacred.

What will you get with this integration?

• Log, display, organize, and compare ML experiments in a single place
• Version, store, manage, and query trained models, and model building metadata
• Record and monitor model training, evaluation, or production runs live

What will be logged to Neptune?

• Hyper-parameters
• Losses & metrics
• Training code(Python scripts or Jupyter notebooks) and git information
• Dataset version
• Model Configuration
• Other metadata

Example custom dashboard in the Neptune UI

Resources

• Documentation
• Code example on GitHub
• Example dashboard in the Neptune app
• Run example in Google Colab

Example

# On the command line:
pip install neptune-client[sacred] sacred torch torchvision

# In Python:
import neptune.new as neptune


# Start a run
run = neptune.init(project = "common/sacred-integration",
                   api_token = "ANONYMOUS")

# Create a sacred experiment
experiment = Experiment("image_classification", interactive=True)

# Add NeptuneObserver and run the experiment
experiment.observers.append(NeptuneObserver(run=neptune_run))
experiment.run()

Support

If you got stuck or simply want to talk to us, here are your options:

• Check our FAQ page
• You can submit bug reports, feature requests, or contributions directly to the repository.
• Chat! When in the Neptune application click on the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP),
• You can just shoot us an email at [e-mail]