ray/python/ray/tune/automlboard at cf16b2f0c42d36d4b652f0acf8ed4b8422f569ce - ray

mirror of https://github.com/wassname/ray.git synced 2026-07-06 04:44:08 +08:00

Files

T

Noah Golmant 1ef9c0729d [tune] Initial track integration (#4362 )

Introduces a minimally invasive utility for logging experiment results. A broad requirement for this tool is that it should integrate seamlessly with Tune execution.

2019-05-17 11:34:05 -07:00

backend

[tune] Initial track integration (#4362 )

2019-05-17 11:34:05 -07:00

common

Enforce quoting style in Travis. (#4589 )

2019-04-11 14:24:26 -07:00

frontend

Enforce quoting style in Travis. (#4589 )

2019-04-11 14:24:26 -07:00

models

Enforce quoting style in Travis. (#4589 )

2019-04-11 14:24:26 -07:00

static

[tune] Add AutoMLBoard: Monitoring UI (experimental) (#2574 )

2018-08-31 00:26:44 -07:00

templates

[tune] Add AutoMLBoard: Monitoring UI (experimental) (#2574 )

2018-08-31 00:26:44 -07:00

__init__.py

[tune] Add AutoMLBoard: Monitoring UI (experimental) (#2574 )

2018-08-31 00:26:44 -07:00

manage.py

[tune] Add AutoMLBoard: Monitoring UI (experimental) (#2574 )

2018-08-31 00:26:44 -07:00

README.md

[tune] Add AutoMLBoard: Monitoring UI (experimental) (#2574 )

2018-08-31 00:26:44 -07:00

run.py

Enforce quoting style in Travis. (#4589 )

2019-04-11 14:24:26 -07:00

settings.py

Enforce quoting style in Travis. (#4589 )

2019-04-11 14:24:26 -07:00

README.md

About AutoMLBoard

AutoMLBoard can be used as a monitor who collect information about Tune jobs and show the trial information to the frontend.

Install

Install django before start AutoMLBoard. run:

pip install django==1.11.14

Usage

Please refer to run.py -h for more help