aup.Proposer.HyperoptProposer

This is converted from Hyperopt repo commit 762e89f

Configuration

General parameters

Name	Default value	Explanation
proposer		hyperopt
random_seed	0	[Optional] seed for random generator
engine	tpe	engine to generate configurations for HyperOpt
n_samples		max_evals in hyperopt

Specific parameters for parameter_config

Name	Explanation
name	name of the variable, will be used in the job config, i.e. training code
type	type of the parameter to be sampled: choose from “float”,”int”,”choice”
range	range of the parameter. For “choice”, list all the feasible values

APIs

class HyperoptProposer(config, random_seed=0)

Bases: aup.Proposer.AbstractProposer.AbstractProposer

failed(job)

Failed jobs unsupported by Hyperopt Proposer.

Parameters

job (Job) – Failed job, containing job id

get_param(**kwargs)

Restructure of hyperopt.fmin run(), serial_evaluate().

reload(path)

Reload Proposer state from path

Parameters

path (str) – path to reload

save(path)

Save Proposer state to path.

Some proposer can not generate new parameters after saving.

Parameters

path (str) – path to save

static setup_config()

update(score, job)

Restructure of hyperopt.fmin serial_evaluation.

Parameters

• score – score returned from the training script

• job – job object contains tid for hyperopt internal update

verify_config(config)

Verify the input configuration is enough for the proposer

Parameters

config (dict) – Experiment configuration of parameter_config

Returns

config

Return type

dict