The size of tensor a (2) must match the size of tensor b (60) at non-singletondimension 1
时间: 2023-12-13 11:34:31 浏览: 26
这个错误通常是由于两个张量的形状不匹配导致的。在这种情况下,张量a的第二个维度的大小为2,而张量b的第二个维度的大小为60。要解决这个问题,你需要调整其中一个张量的形状,使它们匹配。你可以使用PyTorch中的view()函数来更改张量的形状。以下是一个例子:
```python
import torch
a = torch.randn(3, 2)
b = torch.randn(4, 60)
# 将张量a的形状更改为(3, 1, 2)
a = a.view(3, 1, 2)
# 将张量b的形状更改为(4, 1, 60)
b = b.view(4, 1, 60)
# 现在张量a和张量b的形状匹配了
c = torch.cat([a, b], dim=1)
print(c.shape) # 输出:torch.Size([3, 2, 62])
```
在这个例子中,我们使用view()函数将张量a的形状更改为(3, 1, 2),将张量b的形状更改为(4, 1, 60)。然后,我们使用torch.cat()函数将它们连接在一起,得到一个形状为(3, 2, 62)的张量。
相关问题
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.
The size of tensor a (32) must match the size of tensor b (512) at non-singleton dimension 1
The error message "The size of tensor a (32) must match the size of tensor b (512) at non-singleton dimension 1" indicates that there is a size mismatch between two tensors in dimension 1. In order to perform operations between tensors, their sizes must match along all dimensions except for the singleton dimensions.
To resolve this error, you can check the shape of tensor a and tensor b along dimension 1 and ensure they have the same size. If they don't have the same size, you may need to reshape or resize one or both tensors to match their sizes.
Related questions:
1. How can I check the shape of a tensor in PyTorch?
2. How do I resize or reshape a tensor in PyTorch?
3. What are singleton dimensions in tensors?