Apply a sparse update to a tensor taking the element-wise maximum.
tf.tensor_scatter_nd_max(
    tensor, indices, updates, name=None
)
  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.
| Args | |
|---|---|
| tensor | A Tensor. Tensor to update. | 
| indices | A Tensor. Must be one of the following types:int32,int64. Index tensor. | 
| updates | A Tensor. Must have the same type astensor. Updates to scatter into output. | 
| name | A name for the operation (optional). | 
| Returns | |
|---|---|
| A Tensor. Has the same type astensor. | 
    © 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/tensor_scatter_nd_max