commit | 99430913d41cf315b3920bf93b9684d0a303fb5c | [log] [tgz] |
---|---|---|
author | KUAN-HSUN-LI <b06209027@ntu.edu.tw> | Thu Sep 16 23:01:25 2021 +0800 |
committer | Kevin <pingsutw@apache.org> | Fri Sep 17 21:11:45 2021 +0000 |
tree | 8fb8da8be5744fa153b307db1288be80deaa6771 | |
parent | a2cf0dc848cf1f15fd07b77a93c6e9d0353bd453 [diff] |
SUBMARINE-1028. Extend timeout for integration tests ### What is this PR for? Sometimes GitHub Actions' server is not stable, then it will take around 20 minutes and lead to timeout of integration tests. ### What type of PR is it? [Improvement] ### Todos ### What is the Jira issue? https://issues.apache.org/jira/browse/SUBMARINE-1028 ### How should this be tested? ### Screenshots (if appropriate) ### Questions: * Do the license files need updating? No * Are there breaking changes for older versions? No * Does this need new documentation? No Author: KUAN-HSUN-LI <b06209027@ntu.edu.tw> Signed-off-by: Kevin <pingsutw@apache.org> Closes #753 from KUAN-HSUN-LI/SUBMARINE-1028 and squashes the following commits: fbdbc29c [KUAN-HSUN-LI] SUBMARINE-1028. Extend timeout for integration tests
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.