Get started with Kepler Model Server.
- The main source codes are in src directory.
-
Create related issue with your name assigned first (if not exist).
-
Set required secret and environment for local repository test if needed. Check below table.
Objective | Required Secret | Required Environment |
---|---|---|
Push to private repo | BOT_NAME, BOT_TOKEN | IMAGE_REPO |
Change on base image | BOT_NAME, BOT_TOKEN | IMAGE_REPO |
Save data/models to AWS COS | AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY,AWS_REGION |
Learn more details about Training Pipeline
- Define new feature group name
FeatureGroup
and update metric list mapFeatureGroups
in train types
- Define new energy source map
PowerSourceMap
in train types
- extractor: convert from numerically aggregated metrics to per-second value
- isolator: isolate background (idle) power from the collected power
- trainer: apply learning method to build a model using extracted data and isolated data
Learn more details about model training
The new benchmark must be supported by CPE operator for automation. Find examples.
Benchmark
CR has a dependency on BenchmarkOperator
. Default BechmarkOperator
is to support batch/v1/Job API.
Create workload Task
and provide example Pipeline
to run.
TBD
Any improvement in src
and cmd
.
Any improvement in tests
, dockerfiles
, manifests
and .github/workflows
Detailed documentation should be posted to kepler-doc repository.