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：

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())

相关问题

The size of tensor a (25) must match the size of tensor b (2048) at non-singleton dimension 1 什么错误

这个错误是由于张量（tensor）a和b在非单例维度1上的尺寸不匹配引起的。具体来说，张量a在维度1上的尺寸为25，而张量b在维度1上的尺寸为2048。这意味着在执行某个操作时，要求这两个张量在该维度上具有相同的尺寸，但它们的尺寸不匹配，因此导致错误。你需要调整其中一个张量的尺寸，使得它与另一个张量在维度1上具有相同的尺寸才能解决这个问题。

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?