help="Do not write a new model, just report efficacy.",
)
group.add_argument(
- "--ml_trainer_predicate",
+ "--ml_trainer_persist_threshold",
type=argparse_utils.valid_percentage,
metavar='0..100',
- help="Persist the model if the test set score is >= this predicate.",
+ help="Persist the model if the test set score is >= this threshold.",
)
basename: str
dry_run: Optional[bool]
quiet: Optional[bool]
- persist_predicate: Optional[float]
+ persist_percentage_threshold: Optional[float]
delete_bad_inputs: Optional[bool]
@staticmethod
return InputSpec(
dry_run = config.config["ml_trainer_dry_run"],
quiet = config.config["ml_trainer_quiet"],
- persist_predicate = config.config["ml_trainer_predicate"],
+ persist_percentage_threshold = config.config["ml_trainer_persist_threshold"],
delete_bad_inputs = config.config["ml_trainer_delete"],
)
model: Any) -> Tuple[Optional[str], Optional[str], Optional[str]]:
if not self.spec.dry_run:
if (
- (self.spec.persist_predicate is not None and
- test_score > self.spec.persist_predicate)
+ (self.spec.persist_percentage_threshold is not None and
+ test_score > self.spec.persist_percentage_threshold)
or
(not self.spec.quiet
and input_utils.yn_response("Write the model? [y,n]: ") == "y")