class_docstr: Initializes parameters with the identity matrix.
class_docstr_tok: ["Initializes","parameters","with","the","identity","matrix","."]
docstr: Class constructor.
  
  Args:
      local (bool, optional): Whether the layer type is local (Convolutional) or not.
                                Default is True.
      name (string, optional): Name to assign an instance of this class.
docstr_tok: ["Class","constructor",".","Args",":","local","(","bool",",","optional",")",":","Whether","the","layer","type","is","local","(","Convolutional",")","or","not",".","Default","is","True",".","name","(","string",",","optional",")",":","Name","to","assign","an","instance","of","this","class","."]
code: def __init__(self, local=True, name="Identity"):
      """
      Class constructor.
  
      Args:
          local (bool, optional): Whether the layer type is local (Convolutional) or not.
                                    Default is True.
          name (string, optional): Name to assign an instance of this class.
      """
      super(IdentityInit, self).__init__(name=name)
      self.local = local
  
imports: import numpy
  from neon import NervanaObject
  from neon.backends.backend import Tensor
label_desc: Use image node_id 1 to create a new IdentityInit object from inherited base classes: Initializer with example: obj = IdentityInit(local, name)