class_docstr: Beta distribution.
  
  Parameters
  ----------
  alpha
      Tensor containing the alpha shape parameters, of shape
      `(*batch_shape, *event_shape)`.
  beta
      Tensor containing the beta shape parameters, of shape
      `(*batch_shape, *event_shape)`.
  F
class_docstr_tok: ["Beta","distribution",".","Parameters","--","--","--","--","--","alpha","Tensor","containing","the","alpha","shape","parameters",",","of","shape","`","(","*","batch_shape",",","*","event_shape",")","`",".","beta","Tensor","containing","the","beta","shape","parameters",",","of","shape","`","(","*","batch_shape",",","*","event_shape",")","`",".","F"]
code: def stddev(self) -> Tensor:
      return self.F.sqrt(self.variance)
  
imports: from typing import Dict, List, Optional, Tuple
  import numpy
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from .distribution import Distribution, _sample_multiple, getF, softplus
  from .distribution_output import DistributionOutput
label_desc: Use image node_id 9 for calling the Beta obj's underlying member method code with example usage: obj.stddev() and returns: self