def loadFromHGHPIFu()

in lib/model/HGPIFuNetwNML.py [0:0]

• 26 lines of code
• 15 McCabe index (conditional complexity)

    def loadFromHGHPIFu(self, net):
        hgnet = net.image_filter
        pretrained_dict = hgnet.state_dict()            
        model_dict = self.image_filter.state_dict()

        pretrained_dict = {k: v for k, v in hgnet.state_dict().items() if k in model_dict}                    

        for k, v in pretrained_dict.items():                      
            if v.size() == model_dict[k].size():
                model_dict[k] = v

        not_initialized = set()
               
        for k, v in model_dict.items():
            if k not in pretrained_dict or v.size() != pretrained_dict[k].size():
                not_initialized.add(k.split('.')[0])
        
        print('not initialized', sorted(not_initialized))
        self.image_filter.load_state_dict(model_dict) 

        pretrained_dict = net.mlp.state_dict()            
        model_dict = self.mlp.state_dict()

        pretrained_dict = {k: v for k, v in net.mlp.state_dict().items() if k in model_dict}                    

        for k, v in pretrained_dict.items():                      
            if v.size() == model_dict[k].size():
                model_dict[k] = v

        not_initialized = set()
               
        for k, v in model_dict.items():
            if k not in pretrained_dict or v.size() != pretrained_dict[k].size():
                not_initialized.add(k.split('.')[0])
        
        print('not initialized', sorted(not_initialized))
        self.mlp.load_state_dict(model_dict)