mlx.core.linalg.svd

svd(a: array, compute_uv: bool = True, *, stream: None | Stream | Device = None) → Tuple[array, array, array]

The Singular Value Decomposition (SVD) of the input matrix.

This function supports arrays with at least 2 dimensions. When the input has more than two dimensions, the function iterates over all indices of the first a.ndim - 2 dimensions and for each combination SVD is applied to the last two indices.

Parameters:

• a (array) – Input array.

• compute_uv (bool, optional) – If True, return the U, S, and Vt components. If False, return only the S array. Default: True.

• stream (Stream, optional) – Stream or device. Defaults to None in which case the default stream of the default device is used.

Returns:

If compute_uv is True returns the U, S, and Vt matrices, such that A = U @ diag(S) @ Vt. If compute_uv is False returns singular values array S.

Return type:

Union[tuple(array, …), array]