Apply a sparse update to a tensor taking the element-wise maximum.
Returns a new tensor copied from `tensor` whose values are element-wise maximum between tensor and updates according to the indices.
>>> tensor = [0, 0, 0, 0, 0, 0, 0, 0] >>> indices = [[1], [4], [5]] >>> updates = [1, -1, 1] >>> tf.tensor_scatter_nd_max(tensor, indices, updates).numpy() array([0, 1, 0, 0, 0, 1, 0, 0], dtype=int32)
Refer to tf.tensor_scatter_nd_update for more details.
Public Methods
| Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
| static <T, U extends Number> TensorScatterMax<T> | |
| Output<T> |
output()
A new tensor copied from tensor whose values are element-wise maximum between tensor and updates according to the indices.
|
Inherited Methods
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.
public static TensorScatterMax<T> create (Scope scope, Operand<T> tensor, Operand<U> indices, Operand<T> updates)
Factory method to create a class wrapping a new TensorScatterMax operation.
Parameters
| scope | current scope |
|---|---|
| tensor | Tensor to update. |
| indices | Index tensor. |
| updates | Updates to scatter into output. |
Returns
- a new instance of TensorScatterMax
public Output<T> output ()
A new tensor copied from tensor whose values are element-wise maximum between tensor and updates according to the indices.