def _fallback_model(self):
meta = Metadata(
{
"pipeline": [{
"name":
"intent_classifier_keyword",
"class":
utils.module_path_from_object(KeywordIntentClassifier())
}]
}, "")
return Interpreter.create(meta, self._component_builder)
def persist(self,
path,
persistor=None,
project_name=None,
fixed_model_name=None):
# type: (Text, Optional[Persistor], Text) -> Text
"""Persist all components of the pipeline to the passed path.
Returns the directory of the persisted model."""
timestamp = datetime.datetime.now().strftime('%Y%m%d-%H%M%S')
metadata = {
"language":
self.config["language"],
"pipeline": [
utils.module_path_from_object(component)
for component in self.pipeline
],
"model_fasttext":
self.config["model_fasttext"],
}
if project_name is None:
project_name = "default"
if fixed_model_name:
model_name = fixed_model_name
else:
model_name = "model_" + timestamp
dir_name = os.path.join(path, project_name, model_name)
create_dir(dir_name)
if self.training_data:
metadata.update(self.training_data.persist(dir_name))
for component in self.pipeline:
update = component.persist(dir_name)
if update:
metadata.update(update)
Metadata(metadata, dir_name).persist(dir_name)
if persistor is not None:
persistor.persist(dir_name, model_name, project_name)
logger.info("Successfully saved model into "
"'{}'".format(os.path.abspath(dir_name)))
return dir_name
def persist(self,
path: Text,
persistor: Optional[Persistor] = None,
project_name: Text = None,
fixed_model_name: Text = None) -> Text:
"""Persist all components of the pipeline to the passed path.
Returns the directory of the persisted model."""
timestamp = datetime.datetime.now().strftime('%Y%m%d-%H%M%S')
metadata = {
"language": self.config["language"],
"pipeline": [],
}
if project_name is None:
project_name = "default"
if fixed_model_name:
model_name = fixed_model_name
else:
model_name = "model_" + timestamp
path = make_path_absolute(path)
dir_name = os.path.join(path, project_name, model_name)
create_dir(dir_name)
if self.training_data:
metadata.update(self.training_data.persist(dir_name))
for i, component in enumerate(self.pipeline):
file_name = self._file_name(i, component.name)
update = component.persist(file_name, dir_name)
component_meta = component.component_config
if update:
component_meta.update(update)
component_meta["class"] = utils.module_path_from_object(component)
metadata["pipeline"].append(component_meta)
Metadata(metadata, dir_name).persist(dir_name)
if persistor is not None:
persistor.persist(dir_name, model_name, project_name)
logger.info("Successfully saved model into "
"'{}'".format(os.path.abspath(dir_name)))
return dir_name
def persist(self, path, persistor=None, project_name=None,
fixed_model_name=None):
# type: (Text, Optional[Persistor], Text) -> Text
"""Persist all components of the pipeline to the passed path.
Returns the directory of the persisted model."""
timestamp = datetime.datetime.now().strftime('%Y%m%d-%H%M%S')
metadata = {
"language": self.config["language"],
"pipeline": [],
}
if project_name is None:
project_name = "default"
if fixed_model_name:
model_name = fixed_model_name
else:
model_name = "model_" + timestamp
path = config.make_path_absolute(path)
dir_name = os.path.join(path, project_name, model_name)
create_dir(dir_name)
if self.training_data:
metadata.update(self.training_data.persist(dir_name))
for component in self.pipeline:
update = component.persist(dir_name)
component_meta = component.component_config
if update:
component_meta.update(update)
component_meta["class"] = utils.module_path_from_object(component)
metadata["pipeline"].append(component_meta)
Metadata(metadata, dir_name).persist(dir_name)
if persistor is not None:
persistor.persist(dir_name, model_name, project_name)
logger.info("Successfully saved model into "
"'{}'".format(os.path.abspath(dir_name)))
return dir_name
def _fallback_model(self):
meta = Metadata({"pipeline": [{
"name": "KeywordIntentClassifier",
"class": utils.module_path_from_object(KeywordIntentClassifier())
}]}, "")
return Interpreter.create(meta, self._component_builder)
