def _get_rvss(minibatch_RVs, local_RVs, observed_RVs, minibatch_tensors, total_size):
 if (minibatch_RVs is not None):
  _value_error(isinstance(minibatch_RVs, list), 'minibatch_RVs must be a list.')
  _value_error(((local_RVs is None) and (observed_RVs is None)), ('When minibatch_RVs is given, local_RVs and ' + 'observed_RVs must be None.'))
  s = (floatX(total_size) / minibatch_tensors[0].shape[0])
  local_RVs = OrderedDict()
  observed_RVs = OrderedDict([(v, s) for v in minibatch_RVs])
 else:
  _value_error((isinstance(local_RVs, OrderedDict) and isinstance(observed_RVs, OrderedDict)), 'local_RVs and observed_RVs must be OrderedDict.')
 return (local_RVs, observed_RVs)

def _get_rvss ( minibatch_RVs , local_RVs , observed_RVs , minibatch_tensors , total_size ) : if ( minibatch_RVs is not None ) : _value_error ( isinstance ( minibatch_RVs , list ) , 'minibatch_RVs must be a list.' ) _value_error ( ( ( local_RVs is None ) and ( observed_RVs is None ) ) , ( 'When minibatch_RVs is given, local_RVs and ' + 'observed_RVs must be None.' ) ) s = ( floatX ( total_size ) / minibatch_tensors [ 0 ] . shape [ 0 ] ) local_RVs = OrderedDict ( ) observed_RVs = OrderedDict ( [ ( v , s ) for v in minibatch_RVs ] ) else : _value_error ( ( isinstance ( local_RVs , OrderedDict ) and isinstance ( observed_RVs , OrderedDict ) ) , 'local_RVs and observed_RVs must be OrderedDict.' ) return ( local_RVs , observed_RVs )
returns local_rvs and observed_rvs .