def merge(self, *others: "TrainingData") -> "TrainingData":
"""Return merged instance of this data with other training data."""
training_examples = deepcopy(self.training_examples)
entity_synonyms = self.entity_synonyms.copy()
regex_features = deepcopy(self.regex_features)
lookup_tables = deepcopy(self.lookup_tables)
nlg_stories = deepcopy(self.nlg_stories)
others = [other for other in others if other]
for o in others:
training_examples.extend(deepcopy(o.training_examples))
regex_features.extend(deepcopy(o.regex_features))
lookup_tables.extend(deepcopy(o.lookup_tables))
for text, syn in o.entity_synonyms.items():
check_duplicate_synonym(entity_synonyms, text, syn,
"merging training data")
entity_synonyms.update(o.entity_synonyms)
nlg_stories.update(o.nlg_stories)
return TrainingData(
training_examples,
entity_synonyms,
regex_features,
lookup_tables,
nlg_stories,
)
def add_synonym(synonym_value: Text, synonym_name: Text,
existing_synonyms: Dict) -> None:
"""Adds a new synonym mapping to the provided list of synonyms.
Args:
synonym_value: Value of the synonym.
synonym_name: Name of the synonym.
existing_synonyms: Dictionary will synonym mappings that will be extended.
"""
import rasa.nlu.training_data.util as training_data_util
training_data_util.check_duplicate_synonym(existing_synonyms,
synonym_value, synonym_name,
"reading markdown")
existing_synonyms[synonym_value] = synonym_name
def _add_synonym(self, text: Text, value: Text) -> None:
from rasa.nlu.training_data.util import check_duplicate_synonym
check_duplicate_synonym(self.entity_synonyms, text, value,
"reading markdown")
self.entity_synonyms[text] = value
