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

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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

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frontend

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models

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static

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

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templates

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

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__init__.py

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

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manage.py

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

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README.md

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

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run.py

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settings.py

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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