class_docstr: `Reducer` that computes running variance.
  
  This is a special case of `CovarianceReducer` with `event_ndims=0`, provided
  for convenience. See `CovarianceReducer` for more information.
  
  `VarianceReducer` is also meant to fit into the larger streaming MCMC
  framework. For more generic streaming variance needs, see
  `RunningVariance` in `tfp.experimental.stats`.
code: def __init__(self, transform_fn=_get_sample, ddof=0, name=None):
      super(VarianceReducer, self).__init__(
          event_ndims=0,
          transform_fn=transform_fn,
          ddof=ddof,
          name=name or "variance_reducer",
      )
  
imports: import collections
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.mcmc import reducer
  from tensorflow_probability.python.experimental.stats import sample_stats
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.mcmc.internal import util
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 to create a new VarianceReducer object from inherited base classes: CovarianceReducer with example: obj = VarianceReducer(transform_fn, ddof, name)