cupy.linalg.svd

cupy.linalg.svd(a, full_matrices=True, compute_uv=True)

Singular Value Decomposition.

Factorizes the matrix a as u * np.diag(s) * v, where u and v are unitary and s is an one-dimensional array of a’s singular values.

Parameters:

• a (cupy.ndarray) – The input matrix with dimension (M, N).
• full_matrices (bool) – If True, it returns u and v with dimensions (M, M) and (N, N). Otherwise, the dimensions of u and v are respectively (M, K) and (K, N), where K = min(M, N).
• compute_uv (bool) – If False, it only returns singular values.

Returns:

A tuple of (u, s, v) such that a = u * np.diag(s) * v.

Return type:

tuple of cupy.ndarray

See also

numpy.linalg.svd()