cannot assign 'str' object to buffer 'weight' (torch Tensor or None required)

This error message suggests that you are trying to assign a string object to a buffer called 'weight', but the buffer expects a torch Tensor or None object instead.

To fix this error, you need to make sure that the value you are assigning to the 'weight' buffer is a tensor or None object. You can do this by converting the string object to a tensor using the appropriate method in the torch library. For example, you can use the `torch.tensor()` method to create a tensor from a list or a numpy array.

Alternatively, you can initialize the 'weight' buffer with None and assign it a tensor object later in your code when it is available.

相关问题

net[0].weight = torch.tensor([[3.0, 4.0]])报cannot assign 'torch.FloatTensor' as parameter 'weight' (torch.nn.Parameter or None expected)

这个错误提示表明，`net[0].weight`不是一个`torch.nn.Parameter`对象，因此无法通过直接赋值的方式修改它的值。要解决这个问题，你可以将`net[0].weight`转换为`torch.nn.Parameter`对象，然后再进行赋值操作。具体的代码如下：

import torch
import torch.nn as nn

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.fc1 = nn.Linear(2, 1)

    def forward(self, x):
        x = self.fc1(x)
        return x

# 创建模型
net = Net()

# 将net[0].weight转换为torch.nn.Parameter对象
net[0].weight = nn.Parameter(torch.tensor([[1.0, 2.0]]))

# 打印模型
print(net)

运行上述代码，输出的模型参数应该为：

Net(
  (fc1): Linear(in_features=2, out_features=1, bias=True)
)