the size of tensor a (2048) must match the size of tensor b (768) at non-sin
时间: 2023-11-08 08:01:18 浏览: 66
出现这个错误是因为在计算中,两个张量的形状不匹配。在第一个引用中,tensor a的大小是4,而tensor b的大小是2。在第二个引用中,tensor a的大小是2048,而tensor b的大小是2088。在这两种情况下,这些大小不匹配导致了运行时错误。
要解决这个问题,你需要确保两个张量的大小是相等的。你可以使用torch.reshape()函数来改变张量的形状,或者使用torch.squeeze()函数来删除维数为1的维度。通过这些操作,你可以将两个张量调整为相同的形状,从而解决错误。
相关问题
The size of tensor a (2048) must match the size of tensor b (512) at non-singleton dimension 1
这个错误提示意味着在进行某些操作时,张量a和张量b在第1个非单例维度上的大小不匹配。在这种情况下,您需要检查张量a和张量b的形状,并确保它们在第1个非单例维度上具有相同的大小。如果它们的大小不同,则需要调整它们的大小以匹配。您可以使用PyTorch中的resize_()或view()函数来更改张量的大小。以下是一个示例代码,演示如何将张量a的大小更改为与张量b的大小匹配:
```python
import torch
a = torch.randn(2048, 10)
b = torch.randn(512, 10)
if a.size(1) != b.size(1):
a = a.resize_(a.size(0), b.size(1))
print(a.size())
```
The size of tensor a (10) must match the size of tensor b (3) at non-singleton dimension 1
The error message "The size of tensor a (10) must match the size of tensor b (3) at non-singleton dimension 1" indicates that the dimensions of tensor a and tensor b do not match at dimension 1, which prevents the operation from being completed. It seems that the number of elements in tensor a at dimension 1 is 10, while the number of elements in tensor b at dimension 1 is 3.
To fix this issue, you can either resize one of the tensors to match the other tensor's dimension at dimension 1, or reshape one of the tensors to have a different number of dimensions.
Here are some possible solutions:
1. Reshape tensor a: You can reshape tensor a to match the number of elements in tensor b at dimension 1. For example, if tensor a has a shape of (10, 5) and tensor b has a shape of (3, 5), you can reshape tensor a to have a shape of (3, 2, 5) using the reshape() function.
2. Resize tensor b: Alternatively, you can resize tensor b to match the number of elements in tensor a at dimension 1. For example, if tensor a has a shape of (10, 5) and tensor b has a shape of (3, 5), you can resize tensor b to have a shape of (10, 5) using the resize() function.
3. Verify the input data: Double-check the input data for tensor a and tensor b to ensure that they have the correct dimensions and sizes.