commit | 4fc62996842a6ed727007b3e878e9d8d554e9991 | [log] [tgz] |
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author | Chi-Sheng Liu <47914085+MortalHappiness@users.noreply.github.com> | Fri Apr 16 16:54:03 2021 +0800 |
committer | GitHub <noreply@github.com> | Fri Apr 16 16:54:03 2021 +0800 |
tree | 8a7ae12e53476e626a07af8d6746ad3637c81212 | |
parent | c95d7151ba45e743ed75701e6c794a028fa6e45a [diff] |
SUBMARINE-791. Read Submaine CRD spec in controller ### What is this PR for? After defining the spec for Submarine CRD, we need to read the spec in our controller. ### What type of PR is it? [Feature] ### Todos * [x] - Modify types.go to meet the CRD spec. * [x] - Modify controller.go such that it can read the CRD spec. ### What is the Jira issue? https://issues.apache.org/jira/browse/SUBMARINE-791 ### How should this be tested? https://travis-ci.org/github/MortalHappiness/submarine/builds/766867816 ### Screenshots (if appropriate) ![SUBMARINE-791](https://user-images.githubusercontent.com/47914085/114505246-ab52f200-9c62-11eb-9b9b-d13a08503916.png) ### Questions: * Do the license files need updating? No * Are there breaking changes for older versions? No * Does this need new documentation? No
Apache Submarine (Submarine for short) is an End-to-End Machine Learning Platform to allow data scientists to create end-to-end machine learning workflows. On Submarine, data scientists can finish each stage in the ML model lifecycle, including data exploration, data pipeline creation, model training, serving, and monitoring.
Some open-source and commercial projects are trying to build an end-to-end ML platform. What's the vision of Submarine?
Theodore Levitt once said:
“People don’t want to buy a quarter-inch drill. They want a quarter-inch hole.”
experiment
on prem or cloud via easy-to-use UI/API/SDK.experiment
and dependencies of environment
As mentioned above, Submarine attempts to provide Data-Scientist-friendly UI to make data scientists have a good user experience. Here're some examples.
# New a submarine client of the submarine server submarine_client = submarine.ExperimentClient(host='http://localhost:8080') # The experiment's environment, could be Docker image or Conda environment based environment = EnvironmentSpec(image='apache/submarine:tf-dist-mnist-test-1.0') # Specify the experiment's name, framework it's using, namespace it will run in, # the entry point. It can also accept environment variables. etc. # For PyTorch job, the framework should be 'Pytorch'. experiment_meta = ExperimentMeta(name='mnist-dist', namespace='default', framework='Tensorflow', cmd='python /var/tf_dist_mnist/dist_mnist.py --train_steps=100') # 1 PS task of 2 cpu, 1GB ps_spec = ExperimentTaskSpec(resources='cpu=2,memory=1024M', replicas=1) # 1 Worker task worker_spec = ExperimentTaskSpec(resources='cpu=2,memory=1024M', replicas=1) # Wrap up the meta, environment and task specs into an experiment. # For PyTorch job, the specs would be "Master" and "Worker". experiment_spec = ExperimentSpec(meta=experiment_meta, environment=environment, spec={'Ps':ps_spec, 'Worker': worker_spec}) # Submit the experiment to submarine server experiment = submarine_client.create_experiment(experiment_spec=experiment_spec) # Get the experiment ID id = experiment['experimentId']
submarine_client.get_experiment(id)
submarine_client.wait_for_finish(id)
submarine_client.get_log(id)
submarine_client.list_experiments(status='running')
For a quick-start, see Submarine On K8s
(Available on 0.6.0, see Roadmap)
If you want to know more about Submarine's architecture, components, requirements and design doc, they can be found on Architecture-and-requirement
Detailed design documentation, implementation notes can be found at: Implementation notes
Read the Apache Submarine Community Guide
How to contribute Contributing Guide
Issue Tracking: https://issues.apache.org/jira/projects/SUBMARINE
What to know more about what's coming for Submarine? Please check the roadmap out: https://cwiki.apache.org/confluence/display/SUBMARINE/Roadmap
The Apache Submarine project is licensed under the Apache 2.0 License. See the LICENSE file for details.