<s> import numpy as np <EOL> from . node import Node , Moments <EOL> from . stochastic import Stochastic <EOL> from . deterministic import Deterministic <EOL> class DeltaMoments ( Moments ) : <EOL> r"""<STR_LIT>""" <EOL> def compute_fixed_moments ( self , x ) : <EOL> r"""<STR_LIT>""" <EOL> return [ x ] <EOL> def compute_dims_from_values ( self , x ) : <EOL> r"""<STR_LIT>""" <EOL> return ( ( ) , ) <EOL> class DeltaToAny ( Deterministic ) : <EOL> r"""<STR_LIT>""" <EOL> def __init__ ( self , X , moments ) : <EOL> r"""<STR_LIT:U+0020>""" <EOL> self . _moments = moments <EOL> self . _parent_moments = [ DeltaMoments ( ) ] <EOL> dims = moments . compute_dims_from_shape ( X . get_shape ( <NUM_LIT:0> ) ) <EOL> super ( ) . __init__ ( X , dims = dims , ** kwargs ) <EOL> def _compute_moments ( self , u_X ) : <EOL> r"""<STR_LIT:U+0020>""" <EOL> x = u_X [ <NUM_LIT:0> ] <EOL> return self . _moments . compute_fixed_moments ( x ) <EOL> def _compute_message_to_parent ( self , index , m_child , u_X ) : <EOL> r"""<STR_LIT:U+0020>""" <EOL> raise NotImplementedError ( ) <EOL> if index == <NUM_LIT:0> : <EOL> m = m_child [ : <NUM_LIT:2> ] <EOL> return m <EOL> else : <EOL> raise ValueError ( "<STR_LIT>" ) <EOL> def _compute_weights_to_parent ( self , index , weights ) : <EOL> r"""<STR_LIT:U+0020>""" <EOL> raise NotImplementedError ( ) <EOL> if index == <NUM_LIT:0> : <EOL> raise NotImplementedError ( ) <EOL> else : <EOL> raise ValueError ( "<STR_LIT>" ) <EOL> def _plates_to_parent ( self , index ) : <EOL> r"""<STR_LIT:U+0020>""" <EOL> raise NotImplementedError ( ) <EOL> if index == <NUM_LIT:0> : <EOL> self . get_shape ( <NUM_LIT:0> ) <EOL> raise NotImplementedError ( ) <EOL> else : <EOL> raise ValueError ( "<STR_LIT>" ) <EOL> def _plates_from_parent ( self , index ) : <EOL> r"""<STR_LIT:U+0020>""" <EOL> raise NotImplementedError ( ) <EOL> if index == <NUM_LIT:0> : <EOL> return self . __cached_plates <EOL> raise NotImplementedError ( ) <EOL> else : <EOL> raise ValueError ( "<STR_LIT>" ) <EOL> class Scalar ( Stochastic ) : <EOL> def __init__ ( self , plates = None ) : <EOL> dims = [ ( ) ] <EOL> raise NotImplementedError ( ) <EOL> def get_riemannian_gradient ( self ) : <EOL> m_children = self . _message_from_children ( ) <EOL> g = self . annealing * m_children [ <NUM_LIT:0> ] <EOL> return g <EOL> def get_gradient ( self , rg ) : <EOL> return rg <EOL> def get_parameters ( self ) : <EOL> return self . u <EOL> def set_parameters ( self , x ) : <EOL> if len ( x ) != <NUM_LIT:1> : <EOL> raise Exception ( "<STR_LIT>" . format ( len ( x ) ) ) <EOL> self . u = [ x [ <NUM_LIT:0> ] ] <EOL> return <EOL> class PositiveScalar ( Stochastic ) : <EOL> pass <EOL> class Constant ( Node ) : <EOL> r"""<STR_LIT>""" <EOL> def __init__ ( self , moments , x , ** kwargs ) : <EOL> if not isinstance ( moments , Moments ) and issubclass ( moments , Moments ) : <EOL> raise ValueError ( "<STR_LIT>" ) <EOL> self . _moments = moments <EOL> x = np . asanyarray ( x ) <EOL> self . u = self . _moments . compute_fixed_moments ( x ) <EOL> dims = self . _moments . compute_dims_from_values ( x ) <EOL> D = len ( dims [ <NUM_LIT:0> ] ) <EOL> if D > <NUM_LIT:0> : <EOL> plates = np . shape ( self . u [ <NUM_LIT:0> ] ) [ : - D ] <EOL> else : <EOL> plates = np . shape ( self . u [ <NUM_LIT:0> ] ) <EOL> super ( ) . __init__ ( dims = dims , plates = plates , ** kwargs ) <EOL> def _get_id_list ( self ) : <EOL> """<STR_LIT>""" <EOL> return [ ] <EOL> def get_moments ( self ) : <EOL> return self . u <EOL> def set_value ( self , x ) : <EOL> x = np . asanyarray ( x ) <EOL> shapes = [ np . shape ( ui ) for ui in self . u ] <EOL> self . u = self . _moments . compute_fixed_moments ( x ) <EOL> for ( i , shape ) in enumerate ( shapes ) : <EOL> if np . shape ( self . u [ i ] ) != shape : <EOL> raise ValueError ( "<STR_LIT>" ) <EOL> def lower_bound_contribution ( self , gradient = False , ** kwargs ) : <EOL> return <NUM_LIT:0> </s>
