example:

>>> x = tf.constant([1, 2, 3])   # Shape (3,)
>>> y = tf.broadcast_to(x, [2, 3])


When doing broadcasted operations such as multiplying a tensor
by a scalar, broadcasting (usually) confers some time or space
benefit, as the broadcasted tensor is never materialized.

However, `broadcast_to` does not carry with it any such benefits.

        `MatrixBandPart`.
    *   `parallel_for`: Add converter for `MatrixDiag`.
    *   `parallel_for`: Add converters for `OneHot`, `LowerBound`, `UpperBound`.
    *   `parallel_for`: add converter for `BroadcastTo`.
    *   Add `pfor` converter for `Squeeze`.
    *   Add `RaggedTensor.placeholder()`.
    *   Add ragged tensor support to `tf.squeeze`.
    *   Update RaggedTensors to support int32 row_splits.