def gen_text():
mpath = model_path+"gru"
model = Model.load(mpath)
print("loadding model finished")
outshape = (4, 7)
print("vocab size: ", vocab.size())
def do_gen(txt):
#编码
#pdb.set_trace()
res = vocab.encode(sentence=txt)
m, n = outshape
for i in range(m*n - 1):
in_batch = np.array(res).reshape((1, -1))
preds = model.predict(in_batch)
#取最后一维的预测结果
preds = preds[:, -1]
outs = dlmath.categories_sample(preds, 1)
res.append(outs[0,0])
#pdb.set_trace()
txt = ""
for i in range(m):
txt = txt + ''.join(vocab.decode(res[i*n:(i+1)*n])) + "\n"
return txt
starts = ['云', '故', '画', '花']
for txt in starts:
model.reset()
res = do_gen(txt)
print(res)
def test_save_load(self):
print("test model save and load")
fpath = "./models/testmodel"
self.model.save(fpath)
model = Model.load(fpath)