* switch to ARM templates for config and VMs
* switch to ARM templates for config and VMs
* auto-formatting
* addressed Scotts comment
* added missing imports
* fixed gpu templates
fixed wheel reference
* added missing reference
* cleanup wording and yamls
* Update doc/source/autoscaling.rst
Co-Authored-By: Scott Graham <5720537+gramhagen@users.noreply.github.com>
Co-authored-by: Ubuntu <marcozo@marcozodev2.zqvgrdyupqrudayw1il1agipig.jx.internal.cloudapp.net>
Co-authored-by: Scott Graham <5720537+gramhagen@users.noreply.github.com>
* adding directory and node_provider entry for azure autoscaler
* adding initial cut at azure autoscaler functionality, needs testing and node_provider methods need updating
* adding todos and switching to auth file for service principal authentication
* adding role / scope to service principal
* resolving issues with app credentials
* adding retry for setting service principal role
* typo and adding retry to nic creation
* adding nsg to config, moving nic/public ip to node provider, cleanup node_provider, leaving in NodeProvider stub for testing
* linting
* updating cleanup and fixing bugs
* adding directory and node_provider entry for azure autoscaler
* adding initial cut at azure autoscaler functionality, needs testing and node_provider methods need updating
* adding todos and switching to auth file for service principal authentication
* adding role / scope to service principal
* resolving issues with app credentials
* adding retry for setting service principal role
* typo and adding retry to nic creation
* adding nsg to config, moving nic/public ip to node provider, cleanup node_provider, leaving in NodeProvider stub for testing
* linting
* updating cleanup and fixing bugs
* minor fixes
* first working version :)
* added tag support
* added msi identity intermediate
* enable MSI through user managed identity
* updated schema
* extend yaml schema
remove service principal code
add re-use of managed user identity
* fix rg_id
* fix logging
* replace manual cluster yaml validation with json schema
- improved error message
- support for intellisense in VSCode (or other IDEs)
* run linting
* updating yaml configs and formatting
* updating yaml configs and formatting
* typo in example config
* pulling default config from example-full
* resetting min, init worker prop
* adding docs for azure autoscaler and fixing status
* add azure to docs, fix config for spot instances, update azure provider to avoid caching issues during deployment
* fix for default subscription in azure node provider
* vm dev image build
* minor change
* keeping example-full.yaml in autoscaler/azure, updating azure example config
* linting azure config
* extending retries on azure config
* lint
* support for internal ips, fix to azure docs, and new azure gpu example config
* linting
* Update python/ray/autoscaler/azure/node_provider.py
Co-Authored-By: Richard Liaw <rliaw@berkeley.edu>
* revert_this
* remove_schema
* updating configs and removing ssh keygen, tweak azure node provider terminate
* minor tweaks
Co-authored-by: Markus Cozowicz <marcozo@microsoft.com>
Co-authored-by: Ubuntu <marcozo@mc-ray-jumpbox.chcbtljllnieveqhw3e4c1ducc.xx.internal.cloudapp.net>
Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
* make starting ray a separate page
* concept
* Apply suggestions from code review
Co-Authored-By: Edward Oakes <ed.nmi.oakes@gmail.com>
* more fics
* Apply suggestions from code review
Co-Authored-By: Edward Oakes <ed.nmi.oakes@gmail.com>
Co-authored-by: Edward Oakes <ed.nmi.oakes@gmail.com>
* add pages about examples on training language models with fairseq and ray autoscaler
* better format
* update ray_train.sh
* Move EFS to the autoscaler file
* nits
* add comments to the code & use a new way to implement checkpoint hook
* small bug fix
* polish the doc
* fix formatting
* yaml
* update docs
* fix the bugs and add preprocess.sh
* fix lint
* Reduce batch size & fix lint
* shorttitle
- Surfaces local cluster usage
- Increases visability of these instructions
- Removes some docker docs (that are really out of scope for Ray
documentation IMO)
Closes#3517.
Adds a tmux flag that can be used to support background execution of experiments. Cannot be used together with screen. Seems to be useful feature that has shown up with different users.
This adds some experimental (undocumented) support for launching Ray on existing nodes. You have to provide the head ip, and the list of worker ips.
There are also a couple additional utils added for rsyncing files and port-forward.
ray exec CLUSTER CMD [--screen] [--start] [--stop]
ray attach CLUSTER [--start]
Example:
ray exec sgd.yaml 'source activate tensorflow_p27 && cd ~/ray/python/ray/rllib && ./train.py --run=PPO --env=CartPole-v0' --screen --start --stop
This will in one command create a cluster and run the command on it in a screen session. The screen can later be attached to via ray attach. After the command finishes, the cluster workers will be terminated and the head node stopped.
* Fri Feb 16 13:53:50 PST 2018
* Sat Feb 17 15:32:08 PST 2018
* Sat Feb 17 15:44:59 PST 2018
* fix
* Sun Feb 18 14:46:24 PST 2018
* Sun Feb 18 14:46:37 PST 2018
* Sun Feb 18 14:55:52 PST 2018
* Sun Feb 18 15:14:32 PST 2018
* Wed Feb 21 17:34:17 PST 2018
* Sun Feb 25 17:51:17 PST 2018
* Sun Feb 25 22:18:40 PST 2018
* Wed Feb 28 13:19:05 PST 2018
* Wed Feb 28 13:22:13 PST 2018
* Wed Feb 28 13:33:29 PST 2018
* Wed Feb 28 13:35:33 PST 2018
* add ex
* Fri Mar 2 12:50:17 PST 2018
* Fri Mar 2 12:54:31 PST 2018
* some autoscaling config tweaks
* Sun Jan 14 13:56:55 PST 2018
* Mon Jan 15 14:21:09 PST 2018
* increase backoff
* Mon Jan 15 14:40:47 PST 2018
* check boto version
