Files
katib/sdk/python/v1beta1/docs/V1beta1TrialAssignment.md
a9pandGitHub 3fd8502567 Population based training (#1833)
* docs: update new algorithm service details

* feat: trial augmentation strategy

* feat: pbt suggestion service

* feat: PbtTemplate and associated test image

* feat: introduce annotation field to trial specifications

* feat: trial assignment changes to support annotations from suggestion

- Add new Annotation types to suggestion_types.go
- Add Annotation object and update Trial parser in trial.py

* feat: update pbt suggestion to use new Annotation api

- Suggestion uses exact match to track spawned trials
- Trials that get transmitted, but not created (or added to experiment) are added back to the respawn pool (population_size consistency)

* chore: gofmt and black run across PBT changes

* feedback: remove tf summary export, change default print unit, reduce range to be percentage compatible.

* feedback: move PBT template to example.

* feedback: changes to inject_webhook and utils.

- Rename mutateVolume to mutateMetricsCollectorVolume
- Add addContainerVolumeMount
- Add getPrimaryContainerIndex

* feedback: change suggestion mutation mount variable name and add to consts

* feedback: Add trial_names to GetSuggestionsReply and change suggestion path to <experiment>/<trial>

* feedback: removed unnecessary checks and moved to async pbt implementation

* feedback: update trial name override location and change annotations override to labels.

* feedback: add pbt to github workflow

* feedback: move labels to ParameterAssignments in GetSuggestionsReply and cleanup pbt.yaml.

* feedback: remove operator changes

* feedback: GHA updates

* feedback: new formatting changes

* feedback: add suggestion-pbt to gh-actions build-load.sh.

* fix: missing pbt->simple-pbt name changes, add simple-pbt to update-images.sh update yaml function (causing failing gha).

* feedback: add pointer to website from main readme for pbt
2022-06-21 15:35:34 +00:00

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V1beta1TrialAssignment

TrialAssignment is the assignment for one trial.

Properties

Name Type Description Notes
early_stopping_rules list[V1beta1EarlyStoppingRule] Rules for early stopping techniques Contains rule name, value and comparison type [optional]
labels dict(str, str) Suggestion label metadata to attach to Trial job [optional]
name str Name of the suggestion [optional]
parameter_assignments list[V1beta1ParameterAssignment] Suggestion results with Trial parameters [optional]

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