class_docstr: Initializes a blob using uniform distribution between the set bounds.
  
  :param lower_bound: The lower bound of the distribution.
  :type lower_bound: float, default=-1.0
  :param upper_bound: The upper bound of the distribution.
  :type upper_bound: float, default=1.0
  :param random_generator: Sets the random numbers generator to be used.
      By default, the standard NeoML randomizer with default seed is used.
  :type random_generator: object, default=None 
class_docstr_tok: ["Initializes","a","blob","using","uniform","distribution","between","the","set","bounds",".",":","param","lower_bound",":","The","lower","bound","of","the","distribution",".",":","type","lower_bound",":","float",",","default=-1.0",":","param","upper_bound",":","The","upper","bound","of","the","distribution",".",":","type","upper_bound",":","float",",","default=1.0",":","param","random_generator",":","Sets","the","random","numbers","generator","to","be","used",".","By","default",",","the","standard","NeoML","randomizer","with","default","seed","is","used",".",":","type","random_generator",":","object",",","default=None"]
docstr: Sets the distribution upper bound.
          
docstr_tok: ["Sets","the","distribution","upper","bound","."]
code: def upper_bound(self, value):
      """Sets the distribution upper bound."""
      self._internal.set_upper_bound(value)
  
file_path: neoml/NeoML/Python/neoml/Dnn/Initializer.py
imports: import neoml
  import neoml.PythonWrapper
  import neoml.Random
label_desc: Use image node_id 5 for calling the Uniform obj's underlying member method code with example usage: obj.upper_bound(value) without return types