def save(self, dirpath=None):
""" Saves picked automaton object into dirpath.
Parameters
----------
dirpath : str
path to directory where model will be saved
Returns
-------
None
"""
if self.model_ is None:
raise ValueError(
"No model found, use fit() to train or load() pretrained.")
if not os.path.exists(dirpath):
os.makedirs(dirpath)
log.info("Saving model...")
model_file = os.path.join(dirpath, "dictionary-ner.pkl")
joblib.dump(self.model_, model_file)
write_param_file(self.get_params(),
os.path.join(dirpath, "params.yaml"))
def save(self, dirpath):
""" Saves model to local disk, given a dirpath
Parameters
-----------
dirpath : str
a directory where model artifacts will be saved. Model saves a
weights.h5 weights file, a params.json parameter file, and a
preprocessor.pkl preprocessor file.
Returns
-------
None
"""
if self.model_ is None or self.preprocessor_ is None:
raise ValueError(
"No model artifacts to save, either run fit() to train or load() a trained model"
)
if not os.path.exists(dirpath):
os.makedirs(dirpath)
weights_file = os.path.join(dirpath, "weights.h5")
params_file = os.path.join(dirpath, "params.json")
preprocessor_file = os.path.join(dirpath, "preprocessor.pkl")
save_model(self.model_, weights_file, params_file)
self.preprocessor_.save(preprocessor_file)
write_param_file(self.get_params(),
os.path.join(dirpath, "params.yaml"))
def save(self, dirpath):
""" Save trained FLAIR NER model at dirpath.
Parameters
----------
dirpath : str
path to model directory.
Returns
-------
None
"""
if self.model_ is None:
raise ValueError("Cannot save empty model, run fit() to train or load() pretrained model.")
if not(os.path.exists(dirpath) and os.path.isdir(dirpath)):
os.makedirs(dirpath)
self.model_.save(os.path.join(dirpath, "final-model.pt"))
write_param_file(self.get_params(), os.path.join(dirpath, "params.yaml"))
def save(self, dirpath):
""" Save trained SpaCy NER model at dirpath.
Parameters
----------
dirpath : str
path to model directory.
Returns
-------
None
"""
if self.model_ is None:
raise ValueError(
"Cannot save empty model, run fit() to train or load() pretrained model"
)
log.info("Saving model...")
if not os.path.exists(dirpath):
os.makedirs(dirpath)
self.model_.to_disk(dirpath)
write_param_file(self.get_params(),
os.path.join(dirpath, "params.yaml"))
def save(dirpath):
write_param_file(self.get_params(),
os.path.join(dirpath, "params.yaml"))