column. review = hub.text_embedding_column( "review", "https://tfhub.dev/google/universal-sentence-encoder/1", trainable=True) features = { "review": np.array(["an arugula masterpiece", "inedible shoe leather", ...]) } labels = np.array([[1], [0], ...]) input_fn = tf.estimator.input.numpy_input_fn(features, labels, shuffle=True) estimator = tf.estimator.DNNClassifier(hidden_units, [review]) estimator.train(input_fn, max_steps=100) 젆킮얺삫 뫃퓮6OJWFSTBM4FOUFODF&ODPEFS