code: def __init__(self, dim: int) -> None:
      self.args_dim = {"mu": dim, "Sigma": dim * dim}
      self.distr_cls = MultivariateGaussian
      self.dim = dim
      self.mask = None
  
imports: import math
  from typing import Optional, Tuple
  import numpy
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.linalg_util import lower_triangular_ones
  from .distribution import Distribution, _sample_multiple, getF
  from .distribution_output import DistributionOutput
label_desc: Use image node_id 1 to create a new MultivariateGaussianOutput object from inherited base classes: DistributionOutput with example: obj = MultivariateGaussianOutput(dim)