#NEWLINE# @ wraps ( space . Space . make_theano_batch ) #NEWLINE# def make_theano_batch( self , name = None , dtype = None , batch_size = None ) : #NEWLINE# #INDENT# dtype = self . _clean_dtype_arg ( dtype ) #NEWLINE# broadcastable = ( [ False ] * 3 ) #NEWLINE# broadcastable [ 1 ] = ( batch_size == 1 ) #NEWLINE# broadcastable [ 2 ] = ( self . dim == 1 ) #NEWLINE# broadcastable = tuple ( broadcastable ) #NEWLINE# rval = TensorType ( dtype = dtype , broadcastable = broadcastable ) ( name = name ) #NEWLINE# if ( config . compute_test_value != 'off' ) : #NEWLINE# #INDENT# if ( batch_size == 1 ) : #NEWLINE# #INDENT# n = 1 #NEWLINE# #UNINDENT# else : #NEWLINE# #INDENT# n = 4 #NEWLINE# #UNINDENT# rval . tag . test_value = self . get_origin_batch ( batch_size = n , dtype = dtype ) #NEWLINE# #UNINDENT# return rval