mindspore.nn.MatrixDiag

class mindspore.nn.MatrixDiag

Returns a batched diagonal tensor with a given batched diagonal values.

Assume x has $k$ dimensions $[I,J,K,...,N]$, then the output is a tensor of rank $k+1$ with dimensions $[I,J,K,...,N,N]$ where: $output[i,j,k,...,m,n]=1\{m=n\}\ast x[i,j,k,...,n]$

Inputs:

• x (Tensor) - The diagonal values. It can be one of the following data types: float32, float16, int32, int8, and uint8.

Outputs:

Tensor, has the same type as input x. The shape must be x.shape + (x.shape[-1], ).

Raises

TypeError – If dtype of x is not one of float32, float16, int32, int8 or uint8.

Supported Platforms:

Ascend

Examples

>>> x = Tensor(np.array([1, -1]), mindspore.float32)
>>> matrix_diag = nn.MatrixDiag()
>>> output = matrix_diag(x)
>>> print(output)
[[ 1.  0.]
 [ 0. -1.]]