mindspore.ops.inplace_update
- mindspore.ops.inplace_update(x, v, indices)[source]
Updates specified values in x to v according to indices.
Warning
This is an experimental API that is subject to change or deletion.
Note
indices can only be indexed along the highest dimension.
- Parameters
x (Tensor) – A tensor which to be inplace updated. It can be one of the following data types: float32, float16 and int32.
v (Tensor) – A tensor with the same type as x and the same dimension size as x except the first dimension, which must be the same as the size of indices.
indices (Union[int, tuple[int], Tensor]) – Determines which rows of x to update with v, should be several int. It is an int or tuple or tensor with one dimension, whose value is in [-x.shape[0], x.shape[0]). If it is a tuple or Tensor, the size of 'indices' should be the same as the first dimension of 'v'.
- Returns
Tensor, with the same type and shape as the input x.
- Raises
- Supported Platforms:
GPU
CPU
Examples
>>> import numpy as np >>> import mindspore >>> from mindspore import Tensor, ops >>> indices = (0, 1) >>> x = Tensor(np.array([[1, 2], [3, 4], [5, 6]]), mindspore.float32) >>> v = Tensor(np.array([[0.5, 1.0], [1.0, 1.5]]), mindspore.float32) >>> output = ops.inplace_update(x, v, indices) >>> print(output) [[0.5 1. ] [1. 1.5] [5. 6. ]]