The size of tensor a (10) must match the size of tensor b (32) at non-singleton dimension 1
时间: 2023-09-25 10:16:29 浏览: 33
这个错误通常是因为你在进行某些操作时,尝试将不同维度的张量进行运算,导致维度不匹配。在你的情况中,您正在尝试将一个大小为10的张量与一个大小为32的张量在第1个非单例维度上进行运算,这是不允许的。
您需要确保在进行运算之前,两个张量的维度是相同的。您可以使用 PyTorch 中的 reshape 或 unsqueeze 函数来调整张量的维度,以使它们匹配。在这种情况下,您可以使用 unsqueeze(1) 函数将第一个张量的维度扩展到与第二个张量相同。例如:
```
import torch
a = torch.randn(10)
b = torch.randn(32)
a = a.unsqueeze(1) # 将a的维度从[10]扩展到[10, 1]
c = a + b # 现在a和b的维度相同,可以相加了
```
这应该解决您遇到的问题。
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?