Our paper: https://arxiv.org/pdf/1811.06837.pdf
In folder model/, to train a new model
python3 run.py train [dev|test] [tree|var|func]
tree for nonterminal nodes, var for variable nodes, and func for function nodes.
dev and test denote the evaluation set.
After tree, var, and func were trained.
In folder predict/
python3 run.py [pre|eval]
- NLTK 3.2.1
- Tensorflow 1.3.1
- Python 3.5
- Ubuntu 16.04
- Java 1.8
We successly generated.
class BootyBayBodyguard(MinionCard ) :
def __init__ (self) :
super().__init__("Booty Bay Bodyguard", 5, CHARACTER_CLASS.ALL, CARD_RARITY.COMMON)
def create_minion (self, player) :
return Minion(5, 4, taunt = True)
Example Code:
class BootyBayBodyguard(MinionCard ) :
def __init__ (self) :
super().__init__("Booty Bay Bodyguard", 5, CHARACTER_CLASS.ALL, CARD_RARITY.COMMON)
def create_minion (self, player) :
return Minion(5, 4, taunt = True)
Our model tends to generate a structrual correct code, which leads to a higher StrAcc but a similar BLEU compared with previous works.
Code we generated.
class AnnoyoTron(MinionCard ) :
def __init__ (self) :
super().__init__("Annoy-o-Tron", 2, CHARACTER_CLASS.ALL, CARD_RARITY.COMMON, minion_type = MINION_TYPE.MECH, divine_shield = True)
def create_minion (self, player) :
return Minion(1, 2, taunt = True, divine_shield = True)
Example Code:
class AnnoyoTron(MinionCard ) :
def __init__ (self) :
super().__init__("Annoy-o-Tron", 2, CHARACTER_CLASS.ALL, CARD_RARITY.COMMON, minion_type = MINION_TYPE.MECH)
def create_minion (self, player) :
return Minion(1, 2, divine_shield = True, taunt = True)