class_docstr: Gamma distribution.
  
  Parameters
  ----------
  alpha
      Tensor containing the shape parameters, of shape
      `(*batch_shape, *event_shape)`.
  beta
      Tensor containing the rate parameters, of shape
      `(*batch_shape, *event_shape)`.
  F
class_docstr_tok: ["Gamma","distribution",".","Parameters","--","--","--","--","--","alpha","Tensor","containing","the","shape","parameters",",","of","shape","`","(","*","batch_shape",",","*","event_shape",")","`",".","beta","Tensor","containing","the","rate","parameters",",","of","shape","`","(","*","batch_shape",",","*","event_shape",")","`",".","F"]
code: def args(self) -> List:
      return [self.alpha, self.beta]
  
imports: from functools import partial
  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 10 for calling the Gamma obj's underlying member method code with example usage: obj.args() and returns: list