Skip to main content

HSML: An environment independent client to interact with the Hopsworks Model Registry

Project description

Hopsworks Model Management

Hopsworks Community Hopsworks Model Management Documentation PyPiStatus Scala/Java Artifacts Downloads CodeStyle License

HSML is the library to interact with the Hopsworks Model Registry and Model Serving. The library makes it easy to export, manage and deploy models.

The library automatically configures itself based on the environment it is run. However, to connect from an external Python environment additional connection information, such as host and port, is required. For more information about the setup from external environments, see the setup section.

Getting Started On Hopsworks

Instantiate a connection and get the project model registry and serving handles

import hsml

# Create a connection
connection = hsml.connection()

# Get the model registry handle for the project's model registry
mr = connection.get_model_registry()

# Get the model serving handle for the current model registry
ms = connection.get_model_serving()

Create a new model

model = mr.tensorflow.create_model(name="mnist",
                                   version=1,
                                   metrics={"accuracy": 0.94},
                                   description="mnist model description")
model.save("/tmp/model_directory") # or /tmp/model_file

Download a model

model = mr.get_model("mnist", version=1)

model_path = model.download()

Delete a model

model.delete()

Get best performing model

best_model = mr.get_best_model('mnist', 'accuracy', 'max')

Deploy a model

deployment = model.deploy()

Start a deployment

deployment.start()

Make predictions with a deployed model

data = { "instances": [ model.input_example ] }

predictions = deployment.predict(data)

You can find more examples on how to use the library in examples.hopsworks.ai.

Documentation

Documentation is available at Hopsworks Model Management Documentation.

Issues

For general questions about the usage of Hopsworks Machine Learning please open a topic on Hopsworks Community.

Please report any issue using Github issue tracking.

Contributing

If you would like to contribute to this library, please see the Contribution Guidelines.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hsml-3.4.4.tar.gz (57.4 kB view details)

Uploaded Source

File details

Details for the file hsml-3.4.4.tar.gz.

File metadata

  • Download URL: hsml-3.4.4.tar.gz
  • Upload date:
  • Size: 57.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for hsml-3.4.4.tar.gz
Algorithm Hash digest
SHA256 a9feca4aab6edf0f6a94c947baa659e9bba855940160c28849ac3a647912ff5a
MD5 bcd1fc07d6e5e225dc037d8cb5bd946f
BLAKE2b-256 096cab611e2c72b272e652f24e58b815bec89a34b098494f6c61a75eaf32bd3d

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page