Applies sparse `updates`

to individual values or slices within a given

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

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 update 4 scattered elements to a rank-1 tensor to 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]) update = tf.scatter_nd_update(ref, indices, updates) with tf.Session() as sess: print sess.run(update)

The resulting update to ref would look like this:

[1, 11, 3, 10, 9, 6, 7, 12]

See `tf.scatter_nd`

for more details about how to make updates to slices.

Args | |
---|---|

`ref` | A `Tensor` of type `resource` . A resource handle. Must be from a VarHandleOp. |

`indices` | 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. |

`updates` | A `Tensor` . 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 `True` . 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). |

Returns | |
---|---|

The created Operation. |

© 2020 The TensorFlow Authors. All rights reserved.

Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/ResourceScatterNdUpdate