AttributeError: 'Model' object 沒有屬性 '_backward_hooks'

Question

嘗試實施研究論文： https://ieeexplore.ieee.org/document/9479786/使用架構訓練單調網絡：

class Model(nn.Module):
  def __init__(self, q, s):
    self.layer_s_list = [nn.Linear(5, s) for _ in range(q)]
    self.inv_w, self.inv_b = self.get_layer_weights()
      
  def forward(self, x):
    # print(inv_w[0].shape, inv_b[0].shape)
    output_lst = []
    for layer in self.layer_s_list:
      v, id = torch.max(layer(x), 1)
      output_lst.append(v.detach().numpy())
    output_lst = np.array(output_lst)
    output_lst = torch.from_numpy(output_lst)
    out, _ = torch.min(output_lst, 0)
    allo_out = F.softmax(out)
    pay_out = nn.ReLU(inplace = True)(out)
    inv_out_lst = []
    
    for q_idx in range(len(self.inv_w)):
      # print(inv_w[q_idx].shape, pay_out.shape, inv_b[q_idx].shape)
      y, _ = torch.min(torch.linalg.pinv(self.inv_w[q_idx]) * (pay_out - self.inv_b[q_idx]), 0)
      inv_out_lst.append(y.detach().numpy())
    final_out = np.array(inv_out_lst)
    final_out = torch.from_numpy(final_out)
    final_out, _ = torch.max(final_out, 1)
    return final_out, allo_out

  
  def get_layer_weights(self):
    weights_lst = []
    bias_lst = []
    for layer in self.layer_s_list:
      weights_lst.append(layer.state_dict()['weight'])
      bias_lst.append(layer.state_dict()['bias'])
    return weights_lst, bias_lst

當我初始化 the.network 並運行隨機輸入時：

q = 5
s = 10
x = torch.rand((10, 5), requires_grad = True)
net = Model(q, s)
y, z = net(x)`

它給出了以下錯誤：

AttributeError                            Traceback (most recent call last)
<ipython-input-3-aac6d239df1f> in <module>
      1 x = torch.rand((10, 5), requires_grad = True)
      2 net = Model(5, 10)
----> 3 y = net(x)

1 frames
/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in __getattr__(self, name)
   1206                 return modules[name]
   1207         raise AttributeError("'{}' object has no attribute '{}'".format(
-> 1208             type(self).__name__, name))
   1209 
   1210     def __setattr__(self, name: str, value: Union[Tensor, 'Module']) -> None:

AttributeError: 'Model' object has no attribute '_backward_hooks'

請幫助我了解此錯誤是什么以及如何解決。

Answer 1

您忘記使用其父 class nn.Module 的__init__方法初始化您的nn.Module 。 一個簡單的解決方案是在Model.__init__中添加一行：

class Model(nn.Module):
  def __init__(self, q, s):
    super(Model, self).__init__()
    self.layer_s_list = [nn.Linear(5, s) for _ in range(q)]
    self.inv_w, self.inv_b = self.get_layer_weights()