T
- data type for output()
output@Operator public final class ScatterNdNonAliasingAdd<T> extends PrimitiveOp implements Operand<T>
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 `K`th 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.
operation
Modifier and Type | Method and Description |
---|---|
Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T,U extends Number> |
create(Scope scope,
Operand<T> input,
Operand<U> indices,
Operand<T> updates)
Factory method to create a class wrapping a new ScatterNdNonAliasingAdd operation.
|
Output<T> |
output()
A `Tensor` with the same shape as `input`, containing values of `input`
updated with `updates`.
|
equals, hashCode, op, toString
public static <T,U extends Number> ScatterNdNonAliasingAdd<T> create(Scope scope, Operand<T> input, Operand<U> indices, Operand<T> updates)
scope
- current scopeinput
- A Tensor.indices
- A Tensor. Must be one of the following types: `int32`, `int64`.
A tensor of indices into `input`.updates
- A Tensor. Must have the same type as ref. A tensor of updated values
to add to `input`.public Output<T> output()
public Output<T> asOutput()
Operand
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.
asOutput
in interface Operand<T>
OperationBuilder.addInput(Output)
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