class_docstr: Initialize parameter sampling from the uniform
  distribution.
  
  Parameters
  ----------
  minval : int, float
      Minimum possible value.
  
  maxval : int, float
      Maximum possible value.
  
  seed : None or int
      Random seed. Integer value will make results reproducible.
      Defaults to ``None``.
  
  Methods
  -------
  {Initializer.Methods}
class_docstr_tok: ["Initialize","parameter","sampling","from","the","uniform","distribution",".","Parameters","--","--","--","--","--","minval",":","int",",","float","Minimum","possible","value",".","maxval",":","int",",","float","Maximum","possible","value",".","seed",":","None","or","int","Random","seed",".","Integer","value","will","make","results","reproducible",".","Defaults","to","``","None","``",".","Methods","--","--","--","-","{","Initializer.Methods","}"]
code: def __repr__(self):
      return "{}({}, {})".format(
          classname(self), self.minval, self.maxval
      )
  
imports: import abc
  import six
  import numpy
  import tensorflow
  from neupy.core.docs import SharedDocsABCMeta
label_desc: Use image node_id 3 for calling the Uniform obj's underlying member method code with example usage: obj.__repr__() and returns: str