def __init__()

in LaNAS/one-shot_LaNAS/LaNAS/MCTS.py [0:0]

• 28 lines of code
• 8 McCabe index (conditional complexity)

    def __init__(self, search_space, trainer, tree_height ):        
        self.ARCH_CODE_LEN           =  int( len( search_space["b"] ) / 2 )
        self.SEARCH_COUNTER          =  0
        self.samples                 =  {}
        self.nodes                   =  []
        # search space is a tuple, 
        # 0: left side of the constraint, i.e. A
        # 1: right side of the constraint, i.e. b
        self.search_space            =  search_space
        self.Cp                      =  10
        self.trainer                 =  trainer
        # pre-defined for generating masks for supernet
        
        print("architecture code length:", self.ARCH_CODE_LEN )
        # set random seed
        np.random.seed(seed=int(time.time() ) )
        random.seed(datetime.now() )
        
        #initialize the a full tree
        total_nodes = 2**tree_height - 1
        for i in range(1, total_nodes + 1):
            is_good_kid = False
            if (i-1)  > 0 and (i-1) % 2 == 0:
                is_good_kid = False
            elif (i -1) > 0:
                is_good_kid = True
            parent_id = i // 2  - 1
            if parent_id == -1:
                self.nodes.append( Node( None, is_good_kid, self.ARCH_CODE_LEN, True ) )
            else:
                self.nodes.append( Node(self.nodes[parent_id], is_good_kid, self.ARCH_CODE_LEN, False) )
        
        self.ROOT = self.nodes[0]
        self.CURT = self.ROOT
        
        print('='*10 + 'search space start' + '='*10)
        print("total architectures: 2^", len(search_space) )
        print('='*10 + 'search space end  ' + '='*10)