def build_graph_mn(self):
# EXTERNAL MEMORY
# Embed the main input document
u = self.main_docs
if self.doc_emb_method == 'preload_update':
u = self.doc_representation
if self.doc_emb_method == 'preload_no_update':
self.doc_representation = self.main_docs
self.current_mem_size = self.mem_size
if self.design == 'one':
''' One memory: only use user or product memory network, rather than both '''
m = MemoryModel(self.config, u, self.prd_docs, self.doc_emb)
self.prediction_0 = m.pred_before_softmax
self.prediction = m.pred
self.params = [m.W]
elif self.design == 'two':
''' separate two memory: one for user, one for product '''
m_usr = MemoryModel(self.config, u, self.usr_docs, self.doc_emb)
m_prd = MemoryModel(self.config, u, self.prd_docs, self.doc_emb)
self.params = [
m_usr.W, m_prd.W, m_usr.combineWeight, m_prd.combineWeight
]
self.weight_usr = m_usr.combineWeight
self.weight_prd = m_prd.combineWeight
# Combine Two Network
self.prediction_0 = tf.add(m_usr.pred_before_softmax,
m_prd.pred_before_softmax)
self.prediction = tf.nn.softmax(self.prediction_0)
def select_card():
mm = MemoryModel.get_instance()
mouse_left_click(417, 228)
mouse_move(489, 538)
sleep(0.1)
mouse_left_click(489, 538)
sleep(0.1)
mouse_left_click(570, 233)
for p in [(360, 226),
(259, 297),
(40, 295),
(149, 158),
(92, 296),
(206, 363),
(356, 360),
(160, 226)]:
mouse_left_click(*p)
mouse_move(227, 567)
mouse_left_click(227, 567)
# 等待游戏开始
orign = mm.read_int32_from_base(0x5568)
while orign == mm.read_int32_from_base(0x5568):
pass
def main():
open_game_window()
mm = MemoryModel.get_instance()
select_card()
mm.strategy = GigaStrategy()
mm.loop_start()
