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 __init__(self, alpha: Tensor, beta: Tensor) -> None:
      self.alpha = alpha
      self.beta = beta
  
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 1 to create a new Beta object from inherited base classes: Distribution with example: obj = Beta(alpha, beta)