estimators_blog_predict.py

def text_to_index(sentence):
    # Remove punctuation characters except for the apostrophe
    translator = str.maketrans('', '', string.punctuation.replace("'", ''))
    tokens = sentence.translate(translator).lower().split()
    return np.array([1] + [word_index[t] if t in word_index else 2 for t in tokens])

def print_predictions(sentences, classifier):
    indexes = [text_to_index(sentence) for sentence in sentences]
    x = sequence.pad_sequences(indexes, 
                               maxlen=sentence_size, 
                               padding='post', 
                               value=0)
    length = np.array([min(len(x), sentence_size) for x in indexes])
    predict_input_fn = tf.estimator.inputs.numpy_input_fn(x={"x": x, "len": length}, shuffle=False)
    predictions = [p['logistic'][0] for p in classifier.predict(input_fn=predict_input_fn)]
    print(predictions)