tensorflow:: ops:: ScatterNdUpdate

#include <state_ops.h>

Applies sparse updates to individual values or slices within a given.

Summary

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])
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:

• scope: A Scope object
• 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.

Optional attributes (see Attrs ):

• 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.

Returns:

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

Constructors and Destructors

ScatterNdUpdate (const :: tensorflow::Scope & scope, :: tensorflow::Input ref, :: tensorflow::Input indices, :: tensorflow::Input updates)
ScatterNdUpdate (const :: tensorflow::Scope & scope, :: tensorflow::Input ref, :: tensorflow::Input indices, :: tensorflow::Input updates, const ScatterNdUpdate::Attrs & attrs)

operation
output_ref

Public functions

node () const
::tensorflow::Node *
operator::tensorflow::Input () const
operator::tensorflow::Output () const

Public static functions

UseLocking (bool x)

Structs

tensorflow:: ops:: ScatterNdUpdate:: Attrs

Optional attribute setters for ScatterNdUpdate .

Public attributes

operation

Operation operation

output_ref

::tensorflow::Output output_ref

Public functions

ScatterNdUpdate

ScatterNdUpdate(
const ::tensorflow::Scope & scope,
::tensorflow::Input ref,
::tensorflow::Input indices,
)

ScatterNdUpdate

ScatterNdUpdate(
const ::tensorflow::Scope & scope,
::tensorflow::Input ref,
::tensorflow::Input indices,
const ScatterNdUpdate::Attrs & attrs
)

node

::tensorflow::Node * node() const

operator::tensorflow::Input

operator::tensorflow::Input() const

operator::tensorflow::Output

operator::tensorflow::Output() const

Public static functions

UseLocking

Attrs UseLocking(
bool x
)
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]