p_eval, h_eval, y_eval = load_char_data('input/dev.csv', data_size=None)
p_holder = tf.placeholder(dtype=tf.int32,
shape=(None, args.seq_length),
name='p')
h_holder = tf.placeholder(dtype=tf.int32,
shape=(None, args.seq_length),
name='h')
y_holder = tf.placeholder(dtype=tf.int32, shape=None, name='y')
dataset = tf.data.Dataset.from_tensor_slices((p_holder, h_holder, y_holder))
dataset = dataset.batch(args.batch_size).repeat(args.epochs)
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()
model = Graph()
saver = tf.train.Saver()
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
config.gpu_options.per_process_gpu_memory_fraction = 0.9
with tf.Session(config=config) as sess:
sess.run(tf.global_variables_initializer())
sess.run(iterator.initializer,
feed_dict={
p_holder: p,
h_holder: h,
y_holder: y
})
steps = int(len(y) / args.batch_size)
try:
legacy_init_op = tf.group(tf.tables_initializer(),
name='legacy_init_op')
builder = saved_model_builder.SavedModelBuilder(export_path)
builder.add_meta_graph_and_variables(
session, [tag_constants.SERVING],
clear_devices=True,
signature_def_map={
signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY:
model_signature,
},
legacy_init_op=legacy_init_op)
builder.save()
except Exception as e:
print("Fail to export saved model, exception: {}".format(e))
if __name__ == "__main__":
graph2 = tf.Graph()
with graph2.as_default():
m = Graph()
saver = tf.train.Saver()
with tf.Session(graph=graph2) as session:
saver.restore(session, "model/dssm_9.ckpt") #加载ckpt模型
export_model(session, m)
#load_pb()