thanks a lot, but this error occured in my code:
a0=a[0,0,:,:]
a1=a[1,1,:,:]
a2=a[2,2,:,:]
a3=a[3,3,:,:]
a4=a[4,4,:,:]
a5=a[5,5,:,:]
a6=a[6,6,:,:]
a7=a[7,7,:,:]
a0=a1
a1=a2
a2=a3
a3=a4
a4=a5
a5=a6
a6=a7
a7=a0
a=[a0,
    a1,
    a2,
    a3,
    a4,
    a5,
    a6,
    a7]


model = ConvAutoencoder()
model.conv3.weight = nn.Parameter(a[0][1])

with torch.no_grad():                                                                     #3
    for data in test_loader:    
         data = torch.tensor(data[0])    
         
         output = model(data)     

    plt.imshow(output[0,0])


this is error section:
RuntimeError                              Traceback (most recent call last)
<ipython-input-18-55487faab0c0> in <module>()
      3          data = torch.tensor(data[0])
      4 
----> 5          output = model(data)
      6 
      7     plt.imshow(output[0,0])

4 frames
/usr/local/lib/python3.7/dist-packages/torch/nn/modules/conv.py in _conv_forward(self, input, weight, bias)
    394                             _pair(0), self.dilation, self.groups)
    395         return F.conv2d(input, weight, bias, self.stride,
--> 396                         self.padding, self.dilation, self.groups)
    397 
    398     def forward(self, input: Tensor) -> Tensor:

RuntimeError: weight should have at least three dimensions