The size of tensor a (128) must match the size of tensor b (64) at non-singleton dimension 1
时间: 2023-12-13 10:29:58 浏览: 63
这个错误提示是由于在进行某些操作时,两个张量的形状不匹配导致的。具体来说,这里的张量 a 和 b 在第 1 维的大小不同,因此无法进行某些操作。要解决这个问题,需要将张量 a 和 b 的形状调整为相同的。
可以使用 PyTorch 中的 reshape() 函数来调整张量的形状。例如,如果张量 a 的形状为 (128, 10) ,张量 b 的形状为 (64, 10),则可以使用以下代码将张量 a 调整为 (64, 20):
```
a = a.reshape(64, 20)
```
这样就可以使得张量 a 和 b 在第 1 维的大小相同了。
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?
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