python - AttributeError：'str'对象在pytorch中没有属性'dim'

Question

将模型预测发送到模型时，我在 PyTorch 中得到以下错误输出。有谁知道发生了什么？

以下是我创建的架构模型，在错误输出中，它显示 x = self.fc1(cls_hs) 行中存在问题。

class BERT_Arch(nn.Module):

    def __init__(self, bert):
      
      super(BERT_Arch, self).__init__()

      self.bert = bert 
      
      # dropout layer
      self.dropout = nn.Dropout(0.1)
      
      # relu activation function
      self.relu =  nn.ReLU()

      # dense layer 1
      self.fc1 = nn.Linear(768,512)
      
      # dense layer 2 (Output layer)
      self.fc2 = nn.Linear(512,2)

      #softmax activation function
      self.softmax = nn.LogSoftmax(dim=1)

    #define the forward pass
    def forward(self, sent_id, mask):

      #pass the inputs to the model  
      _, cls_hs = self.bert(sent_id, attention_mask=mask)
      print(mask)
      print(type(mask))
      
      x = self.fc1(cls_hs)

      x = self.relu(x)

      x = self.dropout(x)

      # output layer
      x = self.fc2(x)
      
      # apply softmax activation
      x = self.softmax(x)

      return x

/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in linear(input, weight, bias)
   1686         if any([type(t) is not Tensor for t in tens_ops]) and has_torch_function(tens_ops):
   1687             return handle_torch_function(linear, tens_ops, input, weight, bias=bias)
-> 1688     if input == 2 and bias is not None:
   1689         print(input)
   1690         # fused op is marginally faster
AttributeError: 'str' object has no attribute 'dim'

标签： pythonpython-3.xtensorflowmachine-learningbert-language-model

Answer 1

如果您使用transformers==3.0.0，一切都应该正常！

转换器有一些更新==4.0.0

要获取transformers==3.0.0，可以使用以下命令：

!pip install transformers==3.0.0