mlx.core.random.multivariate_normal#

multivariate_normal(mean: array, cov: array, shape: Sequence[int] = [], dtype: Dtype | None = float32, key: array | None = None, stream: None | Stream | Device = None) → array#

Generate jointly-normal random samples given a mean and covariance.

The matrix cov must be positive semi-definite. The behavior is undefined if it is not. The only supported dtype is float32.

Parameters:

  • mean (array) – array of shape (..., n), the mean of the distribution.

  • cov (array) – array of shape (..., n, n), the covariance matrix of the distribution. The batch shape ... must be broadcast-compatible with that of mean.

  • shape (list(int), optional) – The output shape must be broadcast-compatible with mean.shape[:-1] and cov.shape[:-2]. If empty, the result shape is determined by broadcasting the batch shapes of mean and cov. Default: [].

  • dtype (Dtype, optional) – The output type. Default: float32.

  • key (array, optional) – A PRNG key. Default: None.

Returns:

The output array of random values.

Return type:

array