mindspore.ops.FillDiagonal

class mindspore.ops.FillDiagonal(fill_value, wrap=False)[source]

Fill the main diagonal of a tensor that has at least 2-dimensions. When dims>2, all dimensions of input must be of equal length. This function modifies the input tensor in-place, and returns the input tensor.

Parameters

  • fill_value (float) – The fill value.

  • wrap (bool, optional) – the diagonal wrapped after N columns for tall matrices. Default: False.

Inputs:

  • input_x (Tensor) - The shape of tensor is \((x_1, x_2, ..., x_R)\). The data type must be float32, int32 or int64.

Outputs:

  • y (Tensor) - Tensor, has the same shape and data type as the input x.

Raises

  • TypeError – If data type of input_x is not one of the following: float32, int32, int64.

  • ValueError – If the dimension of input_x is not greater than 1.

  • ValueError – If the size of each dimension is not equal, when the dimension is greater than 2.

Supported Platforms:

GPU CPU

Examples

>>> x = Tensor(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]).astype(np.float32))
>>> fill_value = 9.9
>>> fill_diagonal = ops.FillDiagonal(fill_value)
>>> y = fill_diagonal(x)
>>> print(y)
[[9.9 2.  3. ]
 [4.  9.9 6. ]
 [7.  8.  9.9]]
>>> x = Tensor(np.array([[0, 0, 0], [1, 1, 1], [2, 2, 2], [3, 3, 3], [4, 4, 4], [5, 5, 5]]).astype(np.int32))
>>> fill_value = 9.0
>>> fill_diagonal = ops.FillDiagonal(fill_value)
>>> y = fill_diagonal(x)
>>> print(y)
[[9 0 0]
 [1 9 1]
 [2 2 9]
 [3 3 3]
 [4 4 4]
 [5 5 5]]
>>> x = Tensor(np.array([[0, 0, 0], [1, 1, 1], [2, 2, 2], [3, 3, 3],
...                      [4, 4, 4], [5, 5, 5], [6, 6, 6]]).astype(np.int64))
>>> fill_value = 9.0
>>> wrap = True
>>> fill_diagonal = FillDiagonal(fill_value, wrap)
>>> y = fill_diagonal(x)
>>> print(y)
[[9 0 0]
 [1 9 1]
 [2 2 9]
 [3 3 3]
 [9 4 4]
 [5 9 5]
 [6 6 9]]