def get_required_resources(self):
required_resources = self.tfidf_vectorizer_config \
.get_required_resources()
if self.cooccurrence_vectorizer_config:
required_resources = merge_required_resources(
required_resources,
self.cooccurrence_vectorizer_config.get_required_resources())
return required_resources
def get_required_resources(self):
# Resolving custom slot values must be done without stemming
resources = {
CUSTOM_ENTITY_PARSER_USAGE: CustomEntityParserUsage.WITHOUT_STEMS
}
for config in self.intent_parsers_configs:
resources = merge_required_resources(
resources, config.get_required_resources())
return resources
def get_required_resources(self):
# Import here to avoid circular imports
from snips_nlu.slot_filler.feature_factory import get_feature_factory
resources = self.data_augmentation_config.get_required_resources()
for config in self.feature_factory_configs:
factory = get_feature_factory(config)
resources = merge_required_resources(
resources, factory.get_required_resources())
return resources
def get_required_resources(self):
resources = self.intent_classifier_config.get_required_resources()
resources = merge_required_resources(
resources, self.slot_filler_config.get_required_resources())
return resources
def get_required_resources(self):
resources = self.data_augmentation_config.get_required_resources()
resources = merge_required_resources(
resources, self.featurizer_config.get_required_resources())
return resources
def get_required_resources(self):
resources = dict()
for config in self.intent_parsers_configs:
resources = merge_required_resources(
resources, config.get_required_resources())
return resources