ScatterNdUpdate

tensorflow C++ API

tensorflow::ops::ScatterNdUpdate

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 Kth 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:

`python 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.

Arguments:

• 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.

ScatterNdSub block

Source link : https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_state.cpp

Argument:

• Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
• Input ref: connect Input node.
• Input indices: connect Input node.
• Input updates: connect Input node.
• ScatterNdUpdate::Attrs attrs : Input attrs in value. ex)use_locking_ = true;

Return:

• Output output : Output object of ScatterNdUpdate class object.

Result:

• std::vector(Tensor) product_result : Returned object of executed result by calling session.

Using Method

*Assign에 연결된 ClientSession은 Assign값을 확인하기 위해 작성된 temp입니다. ClientSession은 처리순서가 있으므로 테스트시 생성을 마지막에 작성하여 사용합니다