# tf.compat.v1.scatter_nd_sub

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/state_ops.py#L667-L728) |

Applies sparse subtraction to individual values or slices in a Variable.

    tf.compat.v1.scatter_nd_sub(
        ref, indices, updates, use_locking=False, name=None
    )

`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 update 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])
    op = tf.compat.v1.scatter_nd_sub(ref, indices, updates)
    with tf.compat.v1.Session() as sess:
      print sess.run(op)

The resulting update to ref would look like this:

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

See [`tf.scatter_nd`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/scatter_nd) for more details about how to make updates to
slices.

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| ## Args ||
|---|---|
| `ref` | A mutable `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`. A mutable Tensor. Should be from a Variable node. |
| `indices` | A `Tensor`. Must be one of the following types: `int32`, `int64`. A tensor of indices into ref. |
| `updates` | A `Tensor`. Must have the same type as `ref`. A tensor of updated values to add to ref. |
| `use_locking` | 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. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
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| A mutable `Tensor`. Has the same type as `ref`. ||

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