def predict(conf_dict):
"""
predict
"""
net = utility.import_object(
conf_dict["net_py"], conf_dict["net_class"])(conf_dict)
conf_dict.update({"num_epochs": "1", "batch_size": "1",
"shuffle": "0", "train_file": conf_dict["test_file"]})
test_datafeed = datafeeds.TFPointwisePaddingData(conf_dict)
test_l, test_r, test_y = test_datafeed.ops()
# test network
pred = net.predict(test_l, test_r)
controler.run_predict(pred, test_y, conf_dict)
def predict(conf_dict):
tf.compat.v1.reset_default_graph()
net = utility.import_object(conf_dict["net_py"],
conf_dict["net_class"])(conf_dict)
conf_dict.update({
"batch_size": "1",
"shuffle": "0",
"train_file": conf_dict["test_file"]
})
if "dropout_rate" in conf_dict:
conf_dict.update({"dropout_rate": 1.0})
test_datafeed = datafeeds.TFPointwisePaddingData(conf_dict)
test_l, test_r, test_y = test_datafeed.ops()
pred = net.predict(test_l, test_r)
controler.run_predict(pred, test_y, conf_dict)