class_docstr: A running variance computation.
  
  This is just an alias for `RunningCovariance`, with the `event_ndims` set to 0
  to compute variances.
  
  `RunningVariance` is meant to serve general streaming variance needs.
  For a specialized version that fits streaming over MCMC samples, see
  `VarianceReducer` in `tfp.experimental.mcmc`.
docstr: Starts a `RunningVariance` from an example.
  
  Args:
    example: A `Tensor`.  The `RunningVariance` will accept samples
      of the same dtype and broadcast-compatible shape as the example.
  
  Returns:
    var: An empty `RunningVariance`, ready for incoming samples.  Note
      that by convention, the supplied example is used only for
      initialization, but not counted as a sample.
docstr_tok: ["Starts","a","`","RunningVariance","`","from","an","example",".","Args",":","example",":","A","`","Tensor","`",".","The","`","RunningVariance","`","will","accept","samples","of","the","same","dtype","and","broadcast-compatible","shape","as","the","example",".","Returns",":","var",":","An","empty","`","RunningVariance","`",",","ready","for","incoming","samples",".","Note","that","by","convention",",","the","supplied","example","is","used","only","for","initialization",",","but","not","counted","as","a","sample","."]
code: def from_example(cls, example):
      """Starts a `RunningVariance` from an example.
  
      Args:
        example: A `Tensor`.  The `RunningVariance` will accept samples
          of the same dtype and broadcast-compatible shape as the example.
  
      Returns:
        var: An empty `RunningVariance`, ready for incoming samples.  Note
          that by convention, the supplied example is used only for
          initialization, but not counted as a sample.
      """
      return super().from_example(example, event_ndims=0)
  
imports: import functools
  import math
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.mcmc import diagnostic
  from tensorflow.python.util import nest
label_desc: Use image node_id 2 for calling the RunningVariance obj's underlying member method code with example usage: obj.from_example(cls, example) and returns: super