def main():
g = Graph(is_training=False)
# Load vocab
pnyn2idx, idx2pnyn, hanzi2idx, idx2hanzi = load_vocab()
with g.graph.as_default():
sv = tf.train.Supervisor()
with sv.managed_session(config=tf.ConfigProto(
allow_soft_placement=True)) as sess:
# Restore parameters
sv.saver.restore(sess, tf.train.latest_checkpoint(hp.logdir))
print("Restored!")
# Get model
mname = open(hp.logdir + '/checkpoint',
'r').read().split('"')[1] # model name
while True:
line = input("请输入测试拼音：")
if len(line) > hp.maxlen:
print('最长拼音不能超过50')
continue
x = load_test_string(pnyn2idx, line)
#print(x)
preds = sess.run(g.preds, {g.x: x})
#got = "".join(idx2hanzi[str(idx)] for idx in preds[0])[:np.count_nonzero(x[0])].replace("_", "")
got = "".join(
idx2hanzi[idx]
for idx in preds[0])[:np.count_nonzero(x[0])].replace(
"_", "")
print(got)
def main():
g = Graph(is_training=False)
# Load vocab
pnyn2idx, idx2pnyn, hanzi2idx, idx2hanzi = load_vocab()
with g.graph.as_default():
sv = tf.train.Supervisor()
with sv.managed_session(config=tf.ConfigProto(allow_soft_placement=True)) as sess:
# Restore parameters
sv.saver.restore(sess, tf.train.latest_checkpoint(hp.logdir)); print("Restored!")
# Get model
mname = open(hp.logdir + '/checkpoint', 'r').read().split('"')[1] # model name
while True:
line = input("请输入测试拼音：")
if len(line) > hp.maxlen:
print('最长拼音不能超过50')
continue
x = load_test_string(pnyn2idx, line)
#print(x)
preds = sess.run(g.preds, {g.x: x})
#got = "".join(idx2hanzi[str(idx)] for idx in preds[0])[:np.count_nonzero(x[0])].replace("_", "")
got = "".join(idx2hanzi[idx] for idx in preds[0])[:np.count_nonzero(x[0])].replace("_", "")
print(got)
## 部署版本模型测试
from pd_model import seq2seq
import numpy as np
from hyperparams import Hyperparams as hp
from prepro import *
from data_load import load_vocab, load_test_data, load_test_string
model = seq2seq(model_path='./log/qwerty/deploy.pb')
pnyn2idx, idx2pnyn, hanzi2idx, idx2hanzi = load_vocab()
while True:
line = input("请输入测试拼音：")
if len(line) > hp.maxlen:
print('最长拼音不能超过50')
continue
x = load_test_string(pnyn2idx, line)
#print(x)
preds = model.inference(x)
got = "".join(idx2hanzi[idx]
for idx in preds[0])[:np.count_nonzero(x[0])].replace(
"_", "")
print(got)