mindspore.ops.scatter_nd_add

mindspore.ops.scatter_nd_add(input_x, indices, updates, use_locking=False)[source]

Perform a sparse addition update on input_x based on the specified indices and update values.

\[\text{input_x}[\text{indices}[i, ..., j]] \mathrel{+}= \text{updates}[i, ..., j]\]

Warning

This interface is deprecated and will be removed after version 2.9.0.

Note

Support implicit type conversion and type promotion.
The dimension of indices is at least 2, and its shape must be indices.shape[-1] <= len(indices.shape).
The shape of updates is indices.shape[:-1] + input_x.shape[indices.shape[-1]:].

Parameters

input_x (Union[Parameter, Tensor]) – The input parameter or tensor.
indices (Tensor) – The specified indices.
updates (Tensor) – The update values.
use_locking (bool, optional) – Whether to protect the assignment by a lock. Default: False .

Returns

Tensor

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> input_x = mindspore.Parameter(mindspore.tensor([1, 2, 3, 4, 5, 6, 7, 8],
...                               mindspore.float32), name="x")
>>> indices = mindspore.tensor([[2], [4], [1], [7]], mindspore.int32)
>>> updates = mindspore.tensor([6, 7, 8, 9], mindspore.float32)
>>> output = mindspore.ops.scatter_nd_add(input_x, indices, updates, False)
>>> print(output)
[ 1. 10.  9.  4. 12.  6.  7. 17.]
>>> input_x = mindspore.Parameter(mindspore.tensor(mindspore.ops.zeros((4, 4, 4)), mindspore.int32))
>>> indices = mindspore.tensor([[0], [2]], mindspore.int32)
>>> updates = mindspore.tensor([[[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3], [4, 4, 4, 4]],
...                            [[5, 5, 5, 5], [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]]], mindspore.int32)
>>> output = mindspore.ops.scatter_nd_add(input_x, indices, updates, False)
>>> print(output)
[[[1 1 1 1]
  [2 2 2 2]
  [3 3 3 3]
  [4 4 4 4]]
 [[0 0 0 0]
  [0 0 0 0]
  [0 0 0 0]
  [0 0 0 0]]
 [[5 5 5 5]
  [6 6 6 6]
  [7 7 7 7]
  [8 8 8 8]]
 [[0 0 0 0]
  [0 0 0 0]
  [0 0 0 0]
  [0 0 0 0]]]