tensorflow_probability/python/distributions/sample.py
def _make_summary_statistic(attr):
  """Factory for implementing summary statistics, eg, mean, stddev, mode."""
  def _fn(self, **kwargs):
    """Implements summary statistic, eg, mean, stddev, mode."""
    x = getattr(self.distribution, attr)(**kwargs)
    shape = prefer_static.concat([
        self.distribution.batch_shape_tensor(),
        prefer_static.ones(prefer_static.rank_from_shape(self.sample_shape),
                           dtype=self.sample_shape.dtype),
        self.distribution.event_shape_tensor(),
    ], axis=0)
    x = tf.reshape(x, shape=shape)
    shape = prefer_static.concat([
        self.distribution.batch_shape_tensor(),
        self.sample_shape,
        self.distribution.event_shape_tensor(),
    ], axis=0)
    return tf.broadcast_to(x, shape)
  return _fn
def _make_summary_statistic(attr):
  """Factory for implementing summary statistics, eg, mean, stddev, mode."""
  def _fn(self, **kwargs):
    """Implements summary statistic, eg, mean, stddev, mode."""
    x = getattr(self.distribution, attr)(**kwargs)
    shape = prefer_static.concat([
        self.distribution.batch_shape_tensor(),
        prefer_static.ones(prefer_static.rank_from_shape(self.sample_shape),
                           dtype=self.sample_shape.dtype),
        self.distribution.event_shape_tensor(),
    ], axis=0)
    x = tf.reshape(x, shape=shape)
    shape = prefer_static.concat([
        self.distribution.batch_shape_tensor(),
        self.sample_shape,
        self.distribution.event_shape_tensor(),
    ], axis=0)
    return tf.broadcast_to(x, shape)
  return _fn
def _make_summary_statistic ( attr ) : def _fn ( self , * * kwargs ) : """Implements summary statistic, eg, mean, stddev, mode.""" x = getattr ( self . distribution , attr ) ( * * kwargs ) shape = prefer_static . concat ( [ self . distribution . batch_shape_tensor ( ) , prefer_static . ones ( prefer_static . rank_from_shape ( self . sample_shape ) , dtype = self . sample_shape . dtype ) , self . distribution . event_shape_tensor ( ) , ] , axis = 0 ) x = tf . reshape ( x , shape = shape ) shape = prefer_static . concat ( [ self . distribution . batch_shape_tensor ( ) , self . sample_shape , self . distribution . event_shape_tensor ( ) , ] , axis = 0 ) return tf . broadcast_to ( x , shape ) return _fn
Factory for implementing summary statistics, eg, mean, stddev, mode.
Factory for implementing summary statistics eg mean stddev mode .