class_docstr: Glorot with weights sampled from the Normal distribution.
  
  See :class:`Glorot` for a description of the parameters.
class_docstr_tok: ["Glorot","with","weights","sampled","from","the","Normal","distribution",".","See",":","class",":","`","Glorot","`","for","a","description","of","the","parameters","."]
code: def __init__(self, gain=1.0, c01b=False):
      super(GlorotNormal, self).__init__(Normal, gain, c01b)
  
imports: import numpy
  from .utils import floatX
  from .random import get_rng
label_desc: Use image node_id 1 to create a new GlorotNormal object from inherited base classes: Glorot with example: obj = GlorotNormal(gain, c01b)