letianlee / bert-jittor Goto Github PK

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AttributeError                            Traceback (most recent call last)
<ipython-input-120-5962eb72d2ee> in <module>
      4 # 加载 BERT 模型
      5 configuration = BertConfig()
----> 6 model = BertClassification(configuration)
      7 model.load_state_dict(jt.load("jittorhub://pretrained_bert.bin")) # 加载预训练的参数
      8 

~/.cache/jittor/notebook/hw4/bert_model.py in __init__(self, config)
    103         self.class_weight = config.class_weight
    104 
--> 105         self.bert = BertModel(config)
    106         self.dropout = nn.Dropout(config.hidden_dropout_prob)
    107         self.classifier = nn.Linear(config.hidden_size, config.num_labels)

~/.cache/jittor/notebook/hw4/bert_model.py in __init__(self, config, add_pooling_layer)
    148         self.pooler = BertPooler(config) if add_pooling_layer else None
    149 
--> 150         self.init_weights()
    151 
    152     def execute(

~/.cache/jittor/notebook/hw4/bert_model.py in init_weights(self)
     82     def init_weights(self):
     83         # Initialize weights
---> 84         self.apply(self._init_weights)
     85 
     86     def _init_weights(self, module):

/usr/local/lib/python3.8/dist-packages/jittor/__init__.py in apply(self, func)
    886     def apply(self, func):
    887         for m in self.modules():
--> 888             func(m)
    889 
    890     def load_parameters(self, params):

~/.cache/jittor/notebook/hw4/bert_model.py in _init_weights(self, module)
     91                 module.bias.zero_()
     92         elif isinstance(module, nn.Embedding):
---> 93             module.weight.trunc_normal_(mean=0.0, std=self.config.initializer_range)
     94         elif isinstance(module, nn.LayerNorm):
     95             module.bias.zero_()

AttributeError: 'jittor_core.Var' object has no attribute 'trunc_normal_'