def _real_parameters_only_entry_point(main_method: Callable[[Parameters],
None],
usage_message: str = None,
*,
parameters: Optional[Parameters] = None,
program_name: Optional[str] = None,
args: Sequence[str]) -> None:
if not program_name:
# Get original script name for use in the usage message.
import __main__ as main # pylint:disable=import-outside-toplevel
program_name = os.path.basename(main.__file__)
arg_parser = ArgumentParser(prog=program_name, description=usage_message)
if not parameters:
arg_parser.add_argument("param_file", type=Path)
arg_parser.add_argument("-p", action="append", nargs=2, required=False)
parsed_args = arg_parser.parse_args(args)
params = YAMLParametersLoader().load(parsed_args.param_file)
if parsed_args.p:
params = params.unify(params.from_key_value_pairs(parsed_args.p))
configure_logging_from(params)
log.info("Ran with parameters:\n%s", params)
main_method(params)
def main(params: Parameters):
adam_root = params.existing_directory("adam_root")
m13_experiments_dir = adam_root / "parameters" / "experiments" / "m13"
use_pegasus = params.boolean("use_pegasus", default=False)
if use_pegasus:
initialize_vista_pegasus_wrapper(params)
param_files: List[Path] = []
if params.boolean("include_objects", default=True):
param_files.append(m13_experiments_dir / "objects.params")
if params.boolean("include_imprecise_size", default=True):
param_files.append(m13_experiments_dir / "imprecise_size.params")
if params.boolean("include_imprecise_temporal", default=True):
param_files.append(m13_experiments_dir / "imprecise_temporal.params")
if params.boolean("include_subtle_verb", default=True):
param_files.append(m13_experiments_dir / "subtle_verb.params")
if params.boolean("include_object_restrictions", default=True):
param_files.append(m13_experiments_dir / "object_restrictions.params")
if params.boolean("include_functionally_defined_objects", default=True):
param_files.append(m13_experiments_dir / "functionally_defined_objects.params")
if params.boolean("include_relations", default=True):
param_files.append(m13_experiments_dir / "relations.params")
if params.boolean("include_generics", default=True):
param_files.append(m13_experiments_dir / "generics.params")
if params.boolean("include_verbs_with_dynamic_prepositions", default=True):
param_files.append(
m13_experiments_dir / "events_with_dynamic_prepositions.params"
)
if params.boolean("include_m9_complete", default=False):
param_files.append(m13_experiments_dir / "m9_complete.params")
if params.boolean("include_m13_complete", default=False):
param_files.append(m13_experiments_dir / "m13_complete.params")
if params.boolean("include_m13_shuffled", default=False):
param_files.append(m13_experiments_dir / "m13_shuffled.params")
# This activates a special "debug" curriculum,
# which is meant to be edited in the code by a developer to do fine-grained debugging.
if params.boolean("include_debug", default=False):
param_files.append(m13_experiments_dir / "debug.params")
# If any of the param files don't exist, bail out earlier instead of making the user
# wait for the error.
for param_file in param_files:
if not param_file.exists():
raise RuntimeError(f"Expected param file {param_file} does not exist")
for param_file in param_files:
logging.info("Running %s", param_file)
experiment_params = YAMLParametersLoader().load(param_file)
if not use_pegasus:
log_experiment_entry_point(experiment_params)
else:
experiment_name = Locator(experiment_params.string("experiment"))
experiment_params = experiment_params.unify(
{
"experiment_group_dir": directory_for(experiment_name) / "output",
"hypothesis_log_dir": directory_for(experiment_name) / "hypotheses",
# State pickles will go under experiment_name/learner_state
"learner_logging_path": directory_for(experiment_name),
"log_learner_state": True,
"resume_from_latest_logged_state": True,
"log_hypothesis_every_n_steps": params.integer(
"save_state_every_n_steps"
),
"debug_learner_pickling": params.boolean(
"debug_learner_pickling", default=False
),
}
)
run_python_on_parameters(
experiment_name, log_experiment_script, experiment_params, depends_on=[]
)
if use_pegasus:
write_workflow_description()