ScatterNdUpdate

public final class ScatterNdUpdate

Applies sparse `updates` to 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 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.

See also `tf.scatter_update` and `tf.batch_scatter_update`.

Nested Classes

class ScatterNdUpdate.Options Optional attributes for ScatterNdUpdate  

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of the tensor.
static <T extends TType> ScatterNdUpdate<T>
create(Scope scope, Operand<T> ref, Operand<? extends TNumber> indices, Operand<T> updates, Options... options)
Factory method to create a class wrapping a new ScatterNdUpdate operation.
Output<T>
outputRef()
Same as ref.
static ScatterNdUpdate.Options
useLocking(Boolean useLocking)

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "ScatterNdUpdate"

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static ScatterNdUpdate<T> create (Scope scope, Operand<T> ref, Operand<? extends TNumber> indices, Operand<T> updates, Options... options)

Factory method to create a class wrapping a new ScatterNdUpdate operation.

Parameters
scope current scope
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 ref.
updates A Tensor. Must have the same type as ref. A tensor of updated values to add to ref.
options carries optional attributes values
Returns
  • a new instance of ScatterNdUpdate

public Output<T> outputRef ()

Same as ref. Returned as a convenience for operations that want to use the updated values after the update is done.

public static ScatterNdUpdate.Options useLocking (Boolean useLocking)

Parameters
useLocking 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.