lstm.py
def save_model(self):
        """ Save current model's architecture and weights.
        """
        path = self.model_dir + "/" + self.name

        # create folder for the model, if it does not exist
        Path(path).mkdir(parents=True, exist_ok=True)

        # save model's architecture
        model_json_dict = json.loads(self.model.to_json())

        with open(path + "/" + self.name + ".json", "w") as output_file:
            json.dump(model_json_dict, output_file)

        # save model's weights
        self.save_model_weights()

        return
 Save current model's architecture and weights.
        
Save current model's architecture and weights.
Save current model ' s architecture and weights .
def save_model(self):
        path = self.model_dir + "/" + self.name
        Path(path).mkdir(parents=True, exist_ok=True)
        model_json_dict = json.loads(self.model.to_json())
        with open(path + "/" + self.name + ".json", "w") as output_file:
            json.dump(model_json_dict, output_file)
        self.save_model_weights()
        return
def save_model ( self ) : path = self . model_dir + "/" + self . name Path ( path ) . mkdir ( parents = True , exist_ok = True ) model_json_dict = json . loads ( self . model . to_json ( ) ) with open ( path + "/" + self . name + ".json" , "w" ) as output_file : json . dump ( model_json_dict , output_file ) self . save_model_weights ( ) return
Save current model's architecture and weights.
Save current model ' s architecture and weights .
""" Save current model's architecture and weights.
        """ # create folder for the model, if it does not exist
 # save model's architecture
 # save model's weights

self