class_docstr: Gaussian noise generator with counter as pseudo state.
  
  Produces i.i.d. spherical Gaussian noise at each step shaped according to a
  nested structure of `tf.TensorSpec`s.
class_docstr_tok: ["Gaussian","noise","generator","with","counter","as","pseudo","state",".","Produces","i.i.d",".","spherical","Gaussian","noise","at","each","step","shaped","according","to","a","nested","structure","of","`","tf.TensorSpec","`","s","."]
docstr: Makes an initial state for the GaussianNoiseGenerator.
  
  Returns:
    A named tuple of (seeds, stddev).
docstr_tok: ["Makes","an","initial","state","for","the","GaussianNoiseGenerator",".","Returns",":","A","named","tuple","of","(","seeds",",","stddev",")","."]
code: def initialize(self):
      """Makes an initial state for the GaussianNoiseGenerator.
  
      Returns:
        A named tuple of (seeds, stddev).
      """
      if self._seed is None:
          time_now = tf.timestamp()
          residual = time_now - tf.math.floor(time_now)
          return self._GlobalState(
              tf.cast(
                  tf.stack(
                      [
                          tf.math.floor(tf.timestamp() * 1e6),
                          tf.math.floor(residual * 1e9),
                      ]
                  ),
                  dtype=tf.int64,
              ),
              tf.constant(self._noise_std, dtype=tf.float32),
          )
      else:
          return self._GlobalState(
              tf.constant(self._seed, dtype=tf.int64, shape=(2,)),
              tf.constant(self._noise_std, dtype=tf.float32),
          )
  
imports: import abc
  import collections
  from typing import Any, Callable, Collection, NamedTuple, Optional, Tuple, Union
  import tensorflow
label_desc: Use image node_id 2 for calling the GaussianNoiseGenerator obj's underlying member method code with example usage: obj.initialize() and returns: self, self