mindspore.Tensor.index_fill_

Tensor.index_fill_(dim, index, value) → Tensor[source]

Fills the elements under the dim dimension of the self Tensor with the input value by selecting the indices in the order given in index.

Warning

This is an experimental API that is subject to change or deletion.

Note

While calculating the gradient of value , the value of index must be in the range [0, self.shape[dim]) , if it is out of range, the result is undefined.

Parameters

  • dim (int) – Dimension along which to fill the self Tensor.

  • index (Tensor) – Indices of the self Tensor to fill in. The index must be a 0D or 1D Tensor with dtype int32 or int64.

  • value (Union[Tensor, Number, bool]) – Value to fill the self Tensor. The value is a number or a bool or a tensor whose data type is number or bool. If value is a Tensor, it must be a 0D Tensor.

Returns

Tensor, the shape and the data type are the same as those of self .

Raises

  • TypeError – If the data type of index is not int32 or int64.

  • RuntimeError – If dim is out of range \([-self.ndim, self.ndim)\).

  • RuntimeError – If the rank of index is greater than 1.

  • RuntimeError – If value is a Tensor and its rank is not equal to 0.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> from mindspore import Tensor
>>> import numpy as np
>>> x = Tensor(np.array([[1, 2, 3], [4, 5, 6]]), mindspore.int32)
>>> dim = 1
>>> index = Tensor(np.array([0, 2]), mindspore.int32)
>>> value = Tensor(0, mindspore.int32)
>>> output = x.index_fill_(dim, index, value)
>>> print(output)
[[ 0  2  0]
 [ 0  5  0]]
>>> print(x)
[[ 0  2  0]
 [ 0  5  0]]