def _persist_metadata(self, path, dump_flattened_stories=False):
# type: (Text) -> None
"""Persists the domain specification to storage."""
# make sure the directory we persist to exists
domain_spec_path = os.path.join(path, 'policy_metadata.json')
training_data_path = os.path.join(path, 'stories.md')
utils.create_dir_for_file(domain_spec_path)
policy_names = [utils.module_path_from_instance(p)
for p in self.policies]
training_events = self._training_events_from_trackers(
self.training_trackers)
action_fingerprints = self._create_action_fingerprints(training_events)
metadata = {
"action_fingerprints": action_fingerprints,
"rasa_core": rasa_core.__version__,
"max_histories": self._max_histories(),
"ensemble_name": self.__module__ + "." + self.__class__.__name__,
"policy_names": policy_names
}
utils.dump_obj_as_json_to_file(domain_spec_path, metadata)
# if there are lots of stories, saving flattened stories takes a long
# time, so this is turned off by default
if dump_flattened_stories:
training.persist_data(self.training_trackers, training_data_path)
def _persist_metadata(self, path, dump_flattened_stories=False):
# type: (Text) -> None
"""Persists the domain specification to storage."""
# make sure the directory we persist to exists
domain_spec_path = os.path.join(path, 'policy_metadata.json')
training_data_path = os.path.join(path, 'stories.md')
utils.create_dir_for_file(domain_spec_path)
policy_names = [
utils.module_path_from_instance(p) for p in self.policies
]
training_events = self._training_events_from_trackers(
self.training_trackers)
action_fingerprints = self._create_action_fingerprints(training_events)
metadata = {
"action_fingerprints": action_fingerprints,
"rasa_core": rasa_core.__version__,
"max_histories": self._max_histories(),
"ensemble_name": self.__module__ + "." + self.__class__.__name__,
"policy_names": policy_names
}
utils.dump_obj_as_json_to_file(domain_spec_path, metadata)
# if there are lots of stories, saving flattened stories takes a long
# time, so this is turned off by default
if dump_flattened_stories:
training.persist_data(self.training_trackers, training_data_path)
def _persist_metadata(self,
path: Text,
dump_flattened_stories: bool = False) -> None:
"""Persists the domain specification to storage."""
# make sure the directory we persist exists
domain_spec_path = os.path.join(path, 'metadata.json')
training_data_path = os.path.join(path, 'stories.md')
utils.create_dir_for_file(domain_spec_path)
policy_names = [utils.module_path_from_instance(p)
for p in self.policies]
training_events = self._training_events_from_trackers(
self.training_trackers)
action_fingerprints = self._create_action_fingerprints(training_events)
metadata = {
"action_fingerprints": action_fingerprints,
"python": ".".join([str(s) for s in sys.version_info[:3]]),
"max_histories": self._max_histories(),
"ensemble_name": self.__module__ + "." + self.__class__.__name__,
"policy_names": policy_names,
"trained_at": self.date_trained
}
self._add_package_version_info(metadata)
utils.dump_obj_as_json_to_file(domain_spec_path, metadata)
# if there are lots of stories, saving flattened stories takes a long
# time, so this is turned off by default
if dump_flattened_stories:
training.persist_data(self.training_trackers, training_data_path)
