aup.Proposer package¶
The proposer is the core component to optimize hyperparameters for model training.
Use aup.Proposer.AbstractProposer.get_proposer() to initialize proposer.
All of them adopt the same interface as described below.
Proposers¶
aup.Proposer.AbstractProposer¶
aup.Proposer.AbstractProposer provide interface for Hyperparameter Optimization Modules.
APIs¶
- 
class 
AbstractProposer(config)[source]¶ Bases:
abc.ABCProposer to generate new values for hyperparameters
- Parameters
 config (BasicConfig) – experiment configuration
- 
get(**kwargs)[source]¶ Wrapper for specific
get_param()to updatecurrent_proposalandcounter.- Parameters
 kwargs (dict) – any arguments to be passed to
get_param()- Returns
 parameter values
- Return type
 dict
- 
static 
parse_param_config(config)[source]¶ Parse the given experiment configuration of
parameter_configIf values are missing, fill in defaults.- Parameters
 config (dict) – config[“param_config”]
- Returns
 updated config
- Return type
 dict
- 
save(path)[source]¶ Save Proposer state to path.
Some proposer can not generate new parameters after saving.
- Parameters
 path (str) – path to save