tensorflow_probability/python/distributions/joint_distribution_sequential.py
def _entropy(self):
    """Shannon entropy in nats."""
    if any(self._dist_fn_args):
      raise ValueError(
          'Can only compute entropy when all distributions are independent.')
    return sum(joint_distribution_lib.maybe_check_wont_broadcast(
        (d().entropy() for d in self._dist_fn_wrapped),
        self.validate_args))
def _entropy(self):
    if any(self._dist_fn_args):
      raise ValueError(
          'Can only compute entropy when all distributions are independent.')
    return sum(joint_distribution_lib.maybe_check_wont_broadcast(
        (d().entropy() for d in self._dist_fn_wrapped),
        self.validate_args))
def _entropy ( self ) : if any ( self . _dist_fn_args ) : raise ValueError ( 'Can only compute entropy when all distributions are independent.' ) return sum ( joint_distribution_lib . maybe_check_wont_broadcast ( ( d ( ) . entropy ( ) for d in self . _dist_fn_wrapped ) , self . validate_args ) )
Shannon entropy in nats.
Shannon entropy in nats .