### `tf.scatter_nd_sub(ref, indices, updates, use_locking=None, name=None)` {#scatter_nd_sub}

Applies sparse subtraction between `updates` and individual values or slices

within a given variable according to `indices`.

`ref` is a `Tensor` with rank `P` and `indices` is a `Tensor` of rank `Q`.

`indices` must be integer tensor, containing indices into `ref`.
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.

The innermost dimension of `indices` (with length `K`) corresponds to
indices into elements (if `K = P`) or slices (if `K < P`) along the `K`th
dimension of `ref`.

`updates` is `Tensor` of rank `Q-1+P-K` with shape:

```
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].
```

For example, say we want to subtract 4 scattered elements from a rank-1 tensor
with 8 elements. In Python, that subtraction would look like this:

    ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8])
    indices = tf.constant([[4], [3], [1], [7]])
    updates = tf.constant([9, 10, 11, 12])
    sub = tf.scatter_nd_sub(ref, indices, updates)
    with tf.Session() as sess:
      print sess.run(sub)

The resulting update to ref would look like this:

    [1, -9, 3, -6, -4, 6, 7, -4]

See [tf.scatter_nd](#scatter_nd) for more details about how to make updates to
slices.

##### Args:


*  <b>`ref`</b>: A mutable `Tensor`. Must be one of the following types: `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`, `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`.
    A mutable Tensor. Should be from a Variable node.
*  <b>`indices`</b>: A `Tensor`. Must be one of the following types: `int32`, `int64`.
    A Tensor. Must be one of the following types: int32, int64.
    A tensor of indices into ref.
*  <b>`updates`</b>: A `Tensor`. Must have the same type as `ref`.
    A Tensor. Must have the same type as ref. A tensor of updated values
    to subtract from ref.
*  <b>`use_locking`</b>: An optional `bool`. Defaults to `False`.
    An optional bool. Defaults to True. If True, the assignment will
    be protected by a lock; otherwise the behavior is undefined,
    but may exhibit less contention.
*  <b>`name`</b>: A name for the operation (optional).

##### Returns:

  A mutable `Tensor`. Has the same type as `ref`.
  Same as ref. Returned as a convenience for operations that want
  to use the updated values after the update is done.

