class_docstr: Generates a random array from a specified integer uniform distribution.
  
  .. math::
      \mathbf x \sim {\cal U} ([a, b))
  
  Args:
      lim (:obj:`tuple` of :obj:`int`): A tuple of two ints, :math:`(a, b)`.
      rng (numpy.random.RandomState): Random number generator.
  
  Example:
  
  .. code-block:: python
  
      import nnabla as nn
      import nnabla.parametric_functions as PF
      import nnabla.initializer as I
  
      x = nn.Variable([60,1,28,28])
      w = I.UniformIntInitializer() # this generates uniform integer distribution within the default range of (0,10)
      b = I.UniformIntInitializer((-1,1))
      h = PF.convolution(x, 64, [3, 3], w_init=w, b_init=b, pad=[1, 1], name='conv')
code: def __repr__(self):
      return "{}({})".format(self.__class__.__name__, repr(self.lim))
  
imports: import numpy
  from .None import random
label_desc: Use image node_id 2 for calling the UniformIntInitializer obj's underlying member method code with example usage: obj.__repr__() and returns: str