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

Bei*_*hao 5 python machine-learning python-3.x tensorflow bert-language-model

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事吗?

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

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
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/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'
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小智 5

如果您使用 Transformer==3.0.0,一切都应该正常工作!

Transformers==4.0.0 有一些更新

要获得 Transformers==3.0.0,可以使用以下命令:

!pip install transformers==3.0.0
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Bei*_*hao 2

找出原因。是因为变形金刚版本升级了。把我的版本换成旧版本就可以解决这个问题。