builder.field("enabled", true);
                builder.startArray("items");
                builder.value("item1");
                builder.value("item2");
                builder.endArray();
                builder.startObject("nested");
                builder.field("inner", "value");
                builder.endObject();
                builder.endObject();
                return builder;

     */
    protected Object parseArray(final JsonParser jsonParser) throws IOException {
        final List<Object> list = new ArrayList<>();
        while (jsonParser.nextToken() != JsonToken.END_ARRAY) {
            if (jsonParser.getCurrentToken() == JsonToken.START_OBJECT) {
                list.add(parseObject(jsonParser));
            } else if (jsonParser.getCurrentToken() == JsonToken.START_ARRAY) {

    [`tf.experimental.numpy`](https://www.tensorflow.org/api_docs/python/tf/experimental/numpy),
    which is a NumPy-compatible API for writing TF programs. This module
    provides class `ndarray`, which mimics the `ndarray` class in NumPy, and
    wraps an immutable `tf.Tensor` under the hood. A subset of NumPy functions
    (e.g. `numpy.add`) are provided. Their inter-operation with TF facilities is
    seamless in most cases. See