TypeError: nll_loss_nd(): argument 'input' (position 1) must be Tensor, not numpy.ndarray
时间: 2024-04-30 09:22:48 浏览: 17
This error occurs because the input argument to the function nll_loss_nd() should be a Tensor object, but instead, it is a numpy array. To fix this error, you can convert the numpy array to a Tensor object using the torch.Tensor() method before passing it to the nll_loss_nd() function. For example:
```
import torch
import numpy as np
# create a numpy array
arr = np.array([[0.1, 0.2, 0.7], [0.3, 0.5, 0.2]])
# convert numpy array to a Tensor object
input_tensor = torch.Tensor(arr)
# call the nll_loss_nd() function with the Tensor object as input
loss = torch.nn.functional.nll_loss_nd(input_tensor, target_tensor)
```
In this example, we use the torch.Tensor() method to convert the numpy array 'arr' to a Tensor object 'input_tensor' before passing it to the nll_loss_nd() function.