were grown equal to those dark ones which in the four first Observations
encompassed them, that is to say, the white Spot was grown a white Ring
equal to the first of those dark Rings, and the first of those luminous
Rings was now grown equal to the second of those dark ones, and the
second of those luminous ones to the third of those dark ones, and so

*   `tf.saved_model.SaveOptions`

    * `SaveOptions` now takes a new argument called
      `experimental_debug_stripper`. When enabled, this strips the debug nodes
      from both the node defs and the function defs of the graph. Note that
      this currently only strips the `Assert` nodes from the graph and
      converts them into `NoOp`s instead.

*   `tf.data`

    * `tf.data` now has an `autotune_options.initial_parallelism` option to

>>> updates = tf.constant([9, 10, 11, 12])
>>> tensor = tf.ones([8], dtype=tf.int32)
>>> updated = tf.tensor_scatter_nd_add(tensor, indices, updates)
>>> updated
<tf.Tensor: shape=(8,), dtype=int32,
numpy=array([ 1, 12,  1, 11, 10,  1,  1, 13], dtype=int32)>

We can also, insert entire slices of a higher rank tensor all at once. For
example, if we wanted to insert two slices in the first dimension of a