covariance, with positive-valued diagonal
Note:
 Only one of "covariance_matrix" or "precision_matrix" or
 "scale_tril" can be specified.Using "scale_tril" will be more
 efficient: all computations internally are based on "scale_tril".
 If "covariance_matrix" or "precision_matrix" is passed instead,
 it is only used to compute the corresponding lower triangular
 matrices using a Cholesky decomposition.

arg_constraints = {'covariance_matrix': PositiveDefinite(), 'loc': IndependentConstraint(Real(), 1), 'precision_matrix': PositiveDefinite(), 'scale_tril': LowerCholesky()}
property covariance_matrix
entropy()
expand(batch_shape, _instance=None)
has_rsample = True
log_prob(value)
property mean
property mode
property precision_matrix
rsample(sample_shape=torch.Size([]))
property scale_tril
support = IndependentConstraint(Real(), 1)
property variance
NegativeBinomial