def load(self, model_path: str, **kwargs):
"""
:param model_path: the path to a pre-trained model to be loaded.
:type model_path: str
"""
with open(pkl(model_path), 'rb') as fin:
self.key = pickle.load(fin)
self.label_map = pickle.load(fin)
self.chunking = pickle.load(fin)
self.feature_windows = pickle.load(fin)
self.input_config = pickle.load(fin)
self.output_config = pickle.load(fin)
self.fuse_conv_config = pickle.load(fin)
self.ngram_conv_config = pickle.load(fin)
self.hidden_configs = pickle.load(fin)
logging.info('{} is loaded'.format(pkl(model_path)))
self.model = CNNModel(input_config=self.input_config,
output_config=self.output_config,
fuse_conv_config=self.fuse_conv_config,
ngram_conv_config=self.ngram_conv_config,
hidden_configs=self.hidden_configs)
# self.model.load_params(params(model_path), self.ctx)
self.model.load_parameters(params(model_path), self.ctx)
logging.info('{} is loaded'.format(params(model_path)))
logging.info(self.__str__())
return self
def save(self, model_path, **kwargs):
"""
:param model_path: the filepath where the model is to be saved.
:type model_path: str
"""
with open(pkl(model_path), 'wb') as fout:
pickle.dump(self.key, fout)
pickle.dump(self.label_map, fout)
pickle.dump(self.chunking, fout)
pickle.dump(self.rnn_config, fout)
pickle.dump(self.output_config, fout)
logging.info('{} is saved'.format(pkl(model_path)))
self.model.save_parameters(params(model_path))
logging.info('{} is saved'.format(params(model_path)))
def load(self, model_path: str, **kwargs):
"""
:param model_path: the path to a pre-trained model to be loaded.
:type model_path: str
"""
with open(pkl(model_path), 'rb') as fin:
self.key = pickle.load(fin)
self.label_map = pickle.load(fin)
self.chunking = pickle.load(fin)
self.rnn_config = pickle.load(fin)
self.output_config = pickle.load(fin)
logging.info('{} is loaded'.format(pkl(model_path)))
self.model = RNNModel(rnn_config=self.rnn_config, output_config=self.output_config)
self.model.load_parameters(params(model_path), self.ctx)
# self.model.load_params(params(model_path), self.ctx)
logging.info('{} is loaded'.format(params(model_path)))
logging.info(self.__str__())
return self