thanks, but I want to assign changed a to weight of conv2  (dimension is [8,8,3,3]) but i get this error. I dont know how to save type of weights of layer to  tensor and save dimension of weights [8,8,3,3] after change it.
a0=a[:,0,:,:]
a1=a[:,1,:,:]
a2=a[:,2,:,:]
a3=a[:,3,:,:]
a4=a[:,4,:,:]
a5=a[:,5,:,:]
a6=a[:,6,:,:]
a7=a[:,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]

print(a)
model = ConvAutoencoder()
model.conv3.weight = nn.Parameter(a)



this section is error:
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-8-ff7cfd988db4> in <module>()
     30 
     31 model = ConvAutoencoder()
---> 32 model.conv3.weight = nn.Parameter(a)

/usr/local/lib/python3.7/dist-packages/torch/nn/parameter.py in __new__(cls, data, requires_grad)
     24         if data is None:
     25             data = torch.Tensor()
---> 26         return torch.Tensor._make_subclass(cls, data, requires_grad)
     27 
     28     def __deepcopy__(self, memo):

TypeError: _make_subclass(): argument 'data' (position 2) must be Tensor, not list