# tf.raw_ops.ScatterUpdate

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Applies sparse updates to a variable reference.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.ScatterUpdate`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/ScatterUpdate)

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    tf.raw_ops.ScatterUpdate(
        ref, indices, updates, use_locking=True, name=None
    )

This operation computes

        # Scalar indices
        ref[indices, ...] = updates[...]

        # Vector indices (for each i)
        ref[indices[i], ...] = updates[i, ...]

        # High rank indices (for each i, ..., j)
        ref[indices[i, ..., j], ...] = updates[i, ..., j, ...]

This operation outputs `ref` after the update is done.
This makes it easier to chain operations that need to use the reset value.

If values in `ref` is to be updated more than once, because there are
duplicate entries in `indices`, the order at which the updates happen
for each value is undefined.

Requires `updates.shape = indices.shape + ref.shape[1:]` or `updates.shape = []`.
![](https://www.tensorflow.org/images/ScatterUpdate.png)

See also `tf.batch_scatter_update` and `tf.scatter_nd_update`.

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| ## Args ||
|---|---|
| `ref` | 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 the first dimension of `ref`. |
| `updates` | A `Tensor`. Must have the same type as `ref`. A tensor of updated values to store in `ref`. |
| `use_locking` | 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 ||
|---|---|
| A mutable `Tensor`. Has the same type as `ref`. ||

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