commit | 246ecee0706cad8cfa6a66006a7005c67ae235da | [log] [tgz] |
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author | cdmikechen <cdmikechen@apache.org> | Sat Nov 25 11:49:55 2023 +0800 |
committer | cdmikechen <cdmikechen@apache.org> | Sat Dec 02 16:01:24 2023 +0800 |
tree | fe64141adb878e6c9efe9f026dae297efe6b516f | |
parent | 56ca90997faf16ea9e122cea91dfd92541e1f86d [diff] |
SUBMARINE-1387. Update Jupyter(4.0.8) and Conda(23.10.0) version ### What is this PR for? miniconda repo: https://repo.anaconda.com/miniconda/ jupyterlab release: https://github.com/jupyterlab/jupyterlab/releases Jupyterlab has been upgraded to version 4.0. Link: https://blog.jupyter.org/jupyterlab-4-0-is-here-388d05e03442 ### What type of PR is it? Improvement ### Todos * [x] - Update jupyter to 4.0.8 * [x] - Update conda to 23.10.0 * [x] - Remove pyqlib (to fix python3.9+ compatibility issues, pyqlib does not support 3.9+) * [x] - Add jupyter image building test ### What is the Jira issue? https://issues.apache.org/jira/browse/SUBMARINE-1387 ### How should this be tested? We have created a new CI test for jupyter docker image building ### Screenshots (if appropriate) ### Questions: * Do the license files need updating? YNo * Are there breaking changes for older versions? No * Does this need new documentation? No Author: cdmikechen <cdmikechen@apache.org> Signed-off-by: cdmikechen <cdmikechen@apache.org> Closes #1117 from cdmikechen/SUBMARINE-1387 and squashes the following commits: d38925d2 [cdmikechen] remove import 98ac7305 [cdmikechen] change container command version c1e491a5 [cdmikechen] update jupyterlab-git to latest(0.5.0) 4f8c716f [cdmikechen] Add license 3b084bb1 [cdmikechen] fix path error 053570c2 [cdmikechen] move to local submarine dic 820feb3d [cdmikechen] use git pysubmarine 27fcf537 [cdmikechen] fix jupyter-gpu f71605da [cdmikechen] remove pyqlib c521e539 [cdmikechen] update jupyterlab-git to 0.50.0rc0 8ad46e3c [cdmikechen] update jupyter version c2bd43bc [cdmikechen] change name f4b8d58f [cdmikechen] update jupyter-gpu conda d398f736 [cdmikechen] fix workflow config 36ed34d9 [cdmikechen] add test build workflow 64d7a0d2 [cdmikechen] update conda
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 0.5.0, 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
Login Submarine slack channel: https://join.slack.com/t/asf-submarine/shared_invite
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
From here, you can know the changelog and the issue tracker of different version of Apache Submarine.
Apache submarine: a unified machine learning platform made simple at EuroMLSys '22
The Apache Submarine project is licensed under the Apache 2.0 License. See the LICENSE file for details.