added ..note documentation
@@ -475,6 +475,18 @@ def multivariate_normal(mean, cov, size=None, check_valid='ignore',
Returns:
cupy.ndarray: Samples drawn from the multivariate normal distribution.
+ .. note:: Default `method` is set to fastest, 'cholesky'. Cholesky
+ decomposition in CuPy will fail silently if the input covariance matrix
+ is not positive definite and give invalid results, unlike in numpy,
+ where an invalid covariance matrix will raise an exception. Setting
+ `check_valid` to 'raise' will replicate numpy behavior by checking
+ the input, but will also force device synchronization. If validity of
+ input is unknown, setting `method` to 'einh' or 'svd' and
+ `check_valid` to 'warn' will use cholesky decomposition for positive
+ definite matrices, and fallback to the specified `method` for other
+ matrices (i.e., positive semi-definite), and will warn if
+ decomposition is suspect.
+
.. seealso:: :meth:`numpy.random.multivariate_normal
<numpy.random.mtrand.RandomState.multivariate_normal>`
