estimators_blog_input_function.py

x_len_train = np.array([min(len(x), sentence_size) for x in x_train_variable])
x_len_test = np.array([min(len(x), sentence_size) for x in x_test_variable])

def parser(x, length, y):
    features = {"x": x, "len": length}
    return features, y

def train_input_fn():
    dataset = tf.data.Dataset.from_tensor_slices((x_train, x_len_train, y_train))
    dataset = dataset.shuffle(buffer_size=25000)
    dataset = dataset.batch(100)
    dataset = dataset.map(parser)
    dataset = dataset.repeat()
    iterator = dataset.make_one_shot_iterator()
    return iterator.get_next()

def eval_input_fn():
    dataset = tf.data.Dataset.from_tensor_slices((x_test, x_len_test, y_test))
    dataset = dataset.batch(100)
    dataset = dataset.map(parser)
    iterator = dataset.make_one_shot_iterator()
    return iterator.get_next()