792d64bd6f64c4483af5ca1cdb7cbe22c13b5715,demo/load_model/load_and_predict.py,,,#,7

Before Change

print("This demo demonstrates how to load the pre-trained model and check whether the two sentences are continuous")

config_path, checkpoint_path, dict_path = tuple(sys.argv[1:])

model = load_trained_model_from_checkpoint(config_path, checkpoint_path, training=True)
model.summary(line_length=120)

After Change

sentence_2 = "从某种角度看屬於形式科學的一種。"
print("Tokens:", tokenizer.tokenize(first=sentence_1, second=sentence_2))
indices, segments = tokenizer.encode(first=sentence_1, second=sentence_2)
masks = np.array([[0] * len(indices)])

predicts = model.predict([np.array([indices]), np.array([segments]), masks])[1]
print("%s is random next: " % sentence_2, bool(np.argmax(predicts, axis=-1)[0]))

Instances