feature_column_ops_test.py 文件源码

def testOneHotColumnFromSparseColumnWithHashBucket(self):
    hash_buckets = 10
    ids_tensor = tf.SparseTensor(
        values=["c", "b",
                "a", "c", "b",
                "b"],
        indices=[[0, 0, 0], [0, 1, 0],
                 [1, 0, 0], [1, 0, 1], [1, 1, 0],
                 [3, 2, 0]],
        shape=[4, 3, 2])

    hashed_ids_column = tf.contrib.layers.sparse_column_with_hash_bucket(
        "ids", hash_buckets)
    one_hot_column = tf.contrib.layers.one_hot_column(hashed_ids_column)
    columns_to_tensors = {"ids": ids_tensor}
    model_input_tensor = tf.contrib.layers.sequence_input_from_feature_columns(
        columns_to_tensors, [one_hot_column])

    with self.test_session() as sess:
      tf.global_variables_initializer().run()
      tf.initialize_all_tables().run()
      model_input = sess.run(model_input_tensor)

    expected_input_shape = np.array([4, 3, hash_buckets])
    self.assertAllEqual(expected_input_shape, model_input.shape)