def load(cls,
model_dir=None, # type: Optional[Text]
model_metadata=None, # type: Optional[Metadata]
cached_component=None, # type: Optional[EntitySynonymMapper]
**kwargs # type: **Any
):
# type: (...) -> EntitySynonymMapper
meta = model_metadata.for_component(cls.name)
file_name = meta.get("synonyms_file", ENTITY_SYNONYMS_FILE_NAME)
entity_synonyms_file = os.path.join(model_dir, file_name)
if os.path.isfile(entity_synonyms_file):
synonyms = utils.read_json_file(entity_synonyms_file)
else:
synonyms = None
warnings.warn("Failed to load synonyms file from '{}'"
"".format(entity_synonyms_file))
lookuptables_filename = meta.get("lookup_tables_file", ENTITY_LOOKUPTABLES_FILE_NAME)
entity_lookuptables_file = os.path.join(model_dir, lookuptables_filename)
if os.path.isfile(entity_lookuptables_file):
lookup_tables = utils.read_json_file(entity_lookuptables_file)
else:
lookup_tables = None
warnings.warn("Failed to load lookup_tables file from '{}'"
"".format(entity_lookuptables_file))
return EntitySynonymMapper(meta, synonyms,lookup_tables)
def _read_examples_js(self, fn, language, fformat):
"""Infer and load the example file based on the root filename and root format."""
examples_type = "usersays" if fformat == DIALOGFLOW_INTENT else "entries"
examples_fn_ending = "_{}_{}.json".format(examples_type, language)
examples_fn = fn.replace(".json", examples_fn_ending)
if os.path.isfile(examples_fn):
return utils.read_json_file(examples_fn)
else:
return None
def load(cls,
model_dir: Optional[Text] = None,
model_metadata: Optional['Metadata'] = None,
cached_component: Optional['RegexFeaturizer'] = None,
**kwargs: Any) -> 'RegexFeaturizer':
meta = model_metadata.for_component(cls.name)
file_name = meta.get("regex_file", REGEX_FEATURIZER_FILE_NAME)
regex_file = os.path.join(model_dir, file_name)
if os.path.exists(regex_file):
known_patterns = utils.read_json_file(regex_file)
return RegexFeaturizer(meta, known_patterns=known_patterns)
else:
return RegexFeaturizer(meta)
def load(model_dir):
# type: (Text) -> 'Metadata'
"""Loads the metadata from a models directory.
Args:
model_dir (str): the directory where the model is saved.
Returns:
Metadata: A metadata object describing the model
"""
try:
metadata_file = os.path.join(model_dir, 'metadata.json')
data = utils.read_json_file(metadata_file)
return Metadata(data, model_dir)
except Exception as e:
abspath = os.path.abspath(os.path.join(model_dir, 'metadata.json'))
raise InvalidProjectError("Failed to load model metadata "
"from '{}'. {}".format(abspath, e))
def load(
cls,
model_dir=None, # type: Optional[Text]
model_metadata=None, # type: Optional[Metadata]
cached_component=None, # type: Optional[RegexFeaturizer]
**kwargs # type: **Any
):
# type: (...) -> RegexFeaturizer
meta = model_metadata.for_component(cls.name)
file_name = meta.get("regex_file", REGEX_FEATURIZER_FILE_NAME)
regex_file = os.path.join(model_dir, file_name)
if os.path.exists(regex_file):
known_patterns = utils.read_json_file(regex_file)
return RegexFeaturizer(meta, known_patterns=known_patterns)
else:
return RegexFeaturizer(meta)
def read(self, fn, **kwargs):
# type: ([Text]) -> TrainingData
"""Loads training data stored in the Dialogflow data format."""
language = kwargs["language"]
fformat = kwargs["fformat"]
if fformat not in {DIALOGFLOW_INTENT, DIALOGFLOW_ENTITIES}:
raise ValueError("fformat must be either {}, or {}".format(
DIALOGFLOW_INTENT, DIALOGFLOW_ENTITIES))
root_js = utils.read_json_file(fn)
examples_js = self._read_examples_js(fn, language, fformat)
if not examples_js:
logger.warning(
"No training examples found for dialogflow file {}!".format(
fn))
return TrainingData()
elif fformat == DIALOGFLOW_INTENT:
return self._read_intent(root_js, examples_js)
elif fformat == DIALOGFLOW_ENTITIES:
return self._read_entities(examples_js)