mindspore.Tensor.index_fill

Tensor.index_fill(dim, index, value)[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.

Parameters

  • dim (Union[int, Tensor]) – Dimension along which to fill the input Tensor. Only supports an int number or a 0-dimensional Tensor, whose data type is int32 or int64.

  • index (Tensor) – Indices of the input Tensor to fill in. The dtype must be int32.

  • value (Union[bool, int, float, Tensor]) – Value to fill the returned Tensor. If value is a Tensor, it must be a 0-dimensional Tensor and has the same dtype as self Tensor. Otherwise, the value will be cast to a 0-dimensional Tensor with the same data type as self Tensor.

Returns

Tensor, has the same dtype and shape as self Tensor.

Raises

  • TypeError – If dim is neither int number nor Tensor.

  • TypeError – When dim is a Tensor and its dtype is not int32 or int64.

  • TypeError – If index is not a Tensor.

  • TypeError – If dtype of index is not int32.

  • TypeError – If value is not a bool, int, float, or Tensor.

  • TypeError – If dtype of self Tensor and value are not the same.

  • ValueError – When dim is a Tensor and its rank is not equal to 0.

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

  • ValueError – When value is a Tensor and its rank is not equal to 0.

  • RuntimeError – If the value of dim is out the range of [-self.ndim, self.ndim - 1].

  • RuntimeError – If the values of index are out the range of [-self.shape[dim], self.shape[dim] - 1].

Supported Platforms:

GPU

Examples

>>> import mindspore
>>> import mindspore.ops as ops
>>> from mindspore import Tensor
>>> x = Tensor(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]).astype(np.float32))
>>> index = Tensor([0, 2], mindspore.int32)
>>> value = Tensor(-2.0, mindspore.float32)
>>> y = x.index_fill(1, index, value)
>>> print(y)
[[-2. 2. -2.]
 [-2. 5. -2.]
 [-2. 8. -2.]]