<s> import numpy as np <EOL> import theano <EOL> floatX = theano . config . floatX <EOL> class WeightInitializer : <EOL> def __init__ ( self , random_seed = None ) : <EOL> self . rng = np . random . mtrand . RandomState ( random_seed ) <EOL> def __call__ ( self , shared_var ) : <EOL> dim = shared_var . get_value ( ) . shape <EOL> shared_var . set_value ( self . _generate_array ( dim ) ) <EOL> return shared_var <EOL> def _generate_array ( self , dim ) : <EOL> raise NotImplementedError ( "<STR_LIT>" ) <EOL> @ staticmethod <EOL> def _init_range ( dim ) : <EOL> return np . sqrt ( <NUM_LIT> / sum ( dim ) ) <EOL> class UniformInitializer ( WeightInitializer ) : <EOL> def _generate_array ( self , dim ) : <EOL> init_range = self . _init_range ( dim ) <EOL> return np . asarray ( self . rng . uniform ( low = - init_range , high = init_range , size = dim ) , dtype = floatX ) <EOL> class ZerosInitializer ( WeightInitializer ) : <EOL> def _generate_array ( self , dim ) : <EOL> return np . zeros ( dim , dtype = floatX ) <EOL> class DiagonalInitializer ( WeightInitializer ) : <EOL> def _generate_array ( self , dim ) : <EOL> return np . eye ( dim , dtype = floatX ) <EOL> class OrthogonalInitializer ( WeightInitializer ) : <EOL> def _generate_array ( self , dim ) : <EOL> max_dim = max ( dim ) <EOL> uniform_initer = UniformInitializer ( ) <EOL> uniform_initer . rng = self . rng <EOL> return np . asarray ( np . linalg . svd ( uniform_initer ( ( max_dim , max_dim ) ) ) [ <NUM_LIT:2> ] [ : dim [ <NUM_LIT:0> ] , : dim [ <NUM_LIT:1> ] ] , dtype = floatX ) <EOL> class GaussienInitializer ( WeightInitializer ) : <EOL> def _generate_array ( self , dim ) : <EOL> return np . asarray ( self . rng . normal ( loc = <NUM_LIT:0> , scale = self . _init_range ( dim ) , size = dim ) , dtype = floatX ) </s>
