class_docstr: Uniform distribution.
  
  Parameters
  ----------
  low
      Tensor containing the lower bound of the distribution domain.
  high
      Tensor containing the higher bound of the distribution domain.
  F
class_docstr_tok: ["Uniform","distribution",".","Parameters","--","--","--","--","--","low","Tensor","containing","the","lower","bound","of","the","distribution","domain",".","high","Tensor","containing","the","higher","bound","of","the","distribution","domain",".","F"]
code: def mean(self) -> Tensor:
      return (self.high + self.low) / 2
  
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 7 for calling the Uniform obj's underlying member method code with example usage: obj.mean() and returns: unknown