def update_hyperopt_params_with_defaults(hyperopt_params):
set_default_value(hyperopt_params, STRATEGY, {})
set_default_value(hyperopt_params, EXECUTOR, {})
set_default_value(hyperopt_params, "split", VALIDATION)
set_default_value(hyperopt_params, "output_feature", COMBINED)
set_default_value(hyperopt_params, "metric", LOSS)
set_default_value(hyperopt_params, "goal", MINIMIZE)
set_default_values(hyperopt_params[STRATEGY], {TYPE: "random"})
strategy = get_from_registry(hyperopt_params[STRATEGY][TYPE],
sampler_registry)
strategy_defaults = {
k: v
for k, v in strategy.__dict__.items()
if k in get_class_attributes(strategy)
}
set_default_values(
hyperopt_params[STRATEGY],
strategy_defaults,
)
set_default_values(hyperopt_params[EXECUTOR], {TYPE: "serial"})
executor = get_from_registry(hyperopt_params[EXECUTOR][TYPE],
executor_registry)
executor_defaults = {
k: v
for k, v in executor.__dict__.items()
if k in get_class_attributes(executor)
}
set_default_values(
hyperopt_params[EXECUTOR],
executor_defaults,
)
def update_hyperopt_params_with_defaults(hyperopt_params):
from ludwig.hyperopt.execution import executor_registry
set_default_value(hyperopt_params, EXECUTOR, {})
set_default_value(hyperopt_params, "split", VALIDATION)
set_default_value(hyperopt_params, "output_feature", COMBINED)
set_default_value(hyperopt_params, "metric", LOSS)
set_default_value(hyperopt_params, "goal", MINIMIZE)
set_default_values(hyperopt_params[EXECUTOR], {TYPE: "ray"})
executor = get_from_registry(hyperopt_params[EXECUTOR][TYPE],
executor_registry)
executor_defaults = {
k: v
for k, v in executor.__dict__.items()
if k in get_class_attributes(executor)
}
set_default_values(
hyperopt_params[EXECUTOR],
executor_defaults,
)