Applies sparse addition to input using individual values or slices

from updates according to indices indices. The updates are non-aliasing: input is only modified in-place if no other operations will use it. Otherwise, a copy of input is made. This operation has a gradient with respect to both input and updates.

input is a Tensor with rank P and indices is a Tensor of rank Q.

indices must be integer tensor, containing indices into input. 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 (P-K)-dimensional slices (if K < P) along the Kth dimension of input.

updates is Tensor of rank Q-1+P-K with shape:

$$[d_0, ..., d_{Q-2}, input.shape[K], ..., input.shape[P-1]].$$

For example, say we want to add 4 scattered elements to a rank-1 tensor to 8 elements. In Python, that addition would look like this:

input = tf.constant([1, 2, 3, 4, 5, 6, 7, 8]) indices = tf.constant([[4], [3], [1], [7]]) updates = tf.constant([9, 10, 11, 12]) output = tf.scatter_nd_non_aliasing_add(input, indices, updates) with tf.Session() as sess: print(sess.run(output))

The resulting value output would look like this:

[1, 13, 3, 14, 14, 6, 7, 20]

See tf.scatter_nd for more details about how to make updates to slices.

Public Methods

 Output asOutput() Returns the symbolic handle of a tensor. static ScatterNdNonAliasingAdd create(Scope scope, Operand input, Operand indices, Operand updates) Factory method to create a class wrapping a new ScatterNdNonAliasingAdd operation. Output output() A Tensor with the same shape as input, containing values of input updated with updates.

Public Methods

public Output<T> asOutput()

Returns the symbolic handle of a 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.

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

Parameters
scope current scope A Tensor. A Tensor. Must be one of the following types: int32, int64. A tensor of indices into input. A Tensor. Must have the same type as ref. A tensor of updated values to add to input.
Returns
• a new instance of ScatterNdNonAliasingAdd

public Output<T> output()

A Tensor with the same shape as input, containing values of input updated with updates.

[]
[]