class_docstr: Base class for parameter tensor initializers.
  
  The :class:`Initializer` class represents a weight initializer used
  to initialize weight parameters in a neural network layer. It should be
  subclassed when implementing new types of weight initializers.
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docstr: Makes :class:`Initializer` instances callable like a function, invoking
  their :meth:`sample()` method.
docstr_tok: ["Makes",":","class",":","`","Initializer","`","instances","callable","like","a","function",",","invoking","their",":","meth",":","`","sample","(",")","`","method","."]
code: def __call__(self, shape):
      """
      Makes :class:`Initializer` instances callable like a function, invoking
      their :meth:`sample()` method.
      """
      return self.sample(shape)
  
imports: import numpy
  from .utils import floatX
  from .random import get_rng
label_desc: Use image node_id 1 for calling the Initializer obj's underlying member method code with example usage: obj.__call__(shape) and returns: self