class_docstr: Generates a random array from a specified normal distribution.
  
  .. math::
      \mathbf x \sim {\cal N} (\mathbf 0 | \sigma^2 \mathbf I)
  
  Args:
      sigma (float): :math:`\sigma`.
      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.NormalInitializer(5e-5)
      b = I.NormalInitializer(0.0)
      h = PF.convolution(x, 64, [3, 3], w_init=w, b_init=b, pad=[1, 1], name='conv')
code: def __init__(self, sigma=1.0, rng=None):
      if rng is None:
          rng = random.prng
      self.rng = rng
      self.sigma = sigma
  
imports: import numpy
  from .None import random
label_desc: Use image node_id 1 to create a new NormalInitializer object from inherited base classes: BaseInitializer with example: obj = NormalInitializer(sigma, rng)