tensorflow:: ops:: ScatterNdUpdate

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

Resumen

variable según 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 \([d_0, ..., d_{Q-2}, K]\) donde 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 son Tensor de rango Q-1+PK con forma:

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 .

Argumentos:

• ámbito: Un objeto de ámbito
• 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.

Atributos opcionales (ver 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.

Devoluciones:

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

Atributos públicos

Operation operation

::tensorflow::Output output_ref

 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
)

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const 

Attrs UseLocking(
  bool x
)